Keywords: 5 hydroxymethylcytosine 5mC: 5 methyl-Cytosine BCL2 apoptosis regulator BER: base excision repair BMPs: bone morphogenic proteins chromobox homolog 2 coiled-coil serine rich protein MRE11 homolog, double strand break repair nuclease Nijmegen breakage syndrome protein 1, Nibrin nuclear factor, erythroid 2

CFSs: common fragile sites CGIs: CpG islands ChIP: chromatin immunoprecipitation CHK2: checkpoint kinase 2 CHR: chromosome CITED2: Cbp/p300 interacting transactivator with Glu/Asp-rich carboxy

These words that mark the beginning of this manuscript are the ones that I last put down on paper. The three years that were rich in experiences and meetings are coming to an end. So, here I would like to thank all the people that have helped me and who surrounded me during this extraordinary experience, Ph.D.

First of all, I would like to express my deep thanks to all the members of the jury who agreed to evaluate my thesis work. I would like to thank Pr. Xavier Coumoul and Dr. Jiri Zavadil for having accepted to be reviewers for this work, as well as Dr. Ayhan Kocer, Dr. Sophie Langouët and Pr. Luc Paillard for having examined this thesis.

Then, I would like to warmly thank the direction of the unit, in particular Dr. Bernard Jégou and Dr. Michel Samson. Thank you for establishing Irset and for making it the unit that it is today, it is a privilege to have been able to work in such a pleasant environment and conditions.

My thanks then goes to the organizations that co-funded my thesis, Inserm and the Région Bretagne, without whom this work would not have been possible. I would like to warmly thank my thesis supervisor, Dr. Fatima Smagulova. A very big thank you for welcoming me into your team when I was just a young student who had just left the university. You have made me grow enormous scientifically and you have had the patience, much needed it must be said, to teach "wet lab" biology and much more. For all this, I thank you. Your devotion to science has been a profound source of inspiration for me which has kept me always giving my best. I was truly honored to be able to carry out my thesis work under your supervision.

I would also like to extend my sincere thanks to Dr. Shereen D'Cruz, postdoc, with whom I have had the great pleasure of working on a daily basis. Thank you for your boundless kindness and for all the help you have always agreed to give me. Thank you to you for being there to share the moments of doubt as well as the happiest ones.

I would like to thank Dr. Luc Multigner for giving me the benefit of all his expertise on chlordecone. Thank you for trusting us by allowing us to work on the samples of the TIMOUN cohort. I would also like to say a big thank you to Christine Monfort. Thank you for your availability and for the invaluable help you gave me in finding the samples. I also take this opportunity to thank all the people working at Irset. Thank you, in particular, to all the people on the first floor, members of teams 6 and 9, whom I had the pleasure to see daily.

I would like to thank the Irset secretaries for their good humor and their work which has made my life so much easier. Thanks to Brigitte, Catherine, Christelle, Laurence, Mathilde, Sonia and Véronique for your help. Thanks also to Jeannick and Valérie.

Thank you, Laurent, for your advice and the time you devoted for proofreading this manuscript.

And what would the life of an institute be without the boundless energy of doctoral students? My thoughts are first with the seniors, those who were a source of motivation and about whom I thought a lot when writing my thesis: Charly, Estelle, Julie D, Julie F and Laëtitia. Thank you for all the convivial moments we shared outside the lab. A very special thank you to Nathan, my scrabi-san. Your contagious good humor and your limitless motivation allowed us to experience excellent moments that I cherish dearly. Thank you also to all the interns and postdoc who worked in our team: Abderrahman, Aymeric, Chloé, Colin, Elena, Katia, Laura, Marion, Ouzna and Sébastien. I really enjoyed working and partying with you! I would also like to thank all my young colleagues still present at Irset, or freshly graduated: Annabelle, Antonio, Aurore, Edith, Hà, Indusha, Janaina, Judikaël, Juliette, Laurianne, Léa, Leïla, Maryne, Morgane, Nadège, Noriane, Pauline and Salomé. It was really great to be surrounded by so good people and to have had the chance to share so many good times (as well as many beers, haha) with you! Special mention to Salomé, you were there from the start to finish of my thesis (with just a little hole in the middle haha) and your constant enthusiasm has been so precious to me in the less easy times. Thank you very much.

While I am not writing about each of you, you all have a place in my thoughts and in my happy memories of the past three years.

I also would like to thank Gwendoline who has particularly helped me with the analyses since joining our team. Thanks again for your help! I wish you the best for your Ph.D. Rémi, I did not mention you as a member of Irset, although I am lucky enough to see you there every day.

I would like to sincerely thank you for everything you have done for me since the days I know you, particularly, during my first two years of thesis! I cannot wait to put an end to this pandemic and to go back to music festival with you.

I also would like to thank those whom I have met because of you, and who have given me a most pleasant living environment. I am obviously thinking of the merry fellows of 81 rue de Lorient, my neighbors and all their great friends! Thank you, you have helped to make my life so much sweeter these last months! Finally, I would like to thank from the bottom of my heart all the people who have shared my life for many years and who have always supported me despite the distance and the lack of news. I cannot wait to come visit you, meet up with you and share so much with you again. And I am proud to be able to tell 5. The main histone variants and the modifications during histone-to-protamine transition.. Table 6. Prostate-secreted components of the human seminal plasma. . 10. Recurrent genes affected by de novo variants located on X chromosome. .......................

Résumé en français

I. Introduction

Les mécanismes épigénétiques sont essentiels pour l'établissement de l'identité cellulaire au cours du développement. Ces marques épigénétiques sont maintenues au sein de la cellule tout au long de la vie d'un l'individu. Les mécanismes de mémoire épigénétique comprennent la méthylation de l'ADN, les modifications post-traductionnelles de la queue des histones ainsi les ARN non codants. Depuis de nombreuses années, l'accumulation d'évidences tend à montrer que des facteurs environnementaux ou le mode de vie, notamment l'alimentation, le tabagisme, la pratique d'une activité physique régulière ou encore l'exposition à des produits chimiques industriels, ménagers et agricoles, pourraient influencer les mécanismes épigénétiques cellulaires.

Certains composés chimiques toxiques sont qualifiés de perturbateurs endocriniens.

Ces composés, naturels ou de synthèses, présentent la faculté d'interagir avec le système endocrinien, et d'induire par ce biais des effets néfastes sur l'organisme exposé. Ces composés sont particulièrement dangereux car de très faibles quantités peuvent entrainer des effets importants. Il est, par conséquent, urgent de mieux comprendre les conséquences à long terme des perturbateurs endocriniens sur la santé humaine.

Parmi les composés perturbateurs endocriniens, le chlordécone (CD) est particulièrement préoccupant car il a été utilisé de manière intensive pendant deux décennies dans les bananeraies des Antilles françaises, en Guadeloupe et à la Martinique. Bien qu'interdit il y a plus de 25 ans, en 1993, le CD reste aujourd'hui un problème majeur de santé publique car ses propriétés physico-chimiques en fond un composé extrêmement stable dans l'environnement, capable de se bioaccumuler dans la chaine alimentaire (dans les légumes racines, le poisson ou la viande). Ainsi, les populations antillaises sont constamment exposées à cette molécule, principalement au travers de leur alimentation et via la consommation d'eau polluée.

La production de CD de l'usine principale située à Hopewell aux Etats-Unis a été arrêtée en 1975, suite à l'hospitalisation de plusieurs travailleurs présentant des troubles neurologiques. Les principaux symptômes rapportés étaient une nervosité accrue, des tremblements, une perte de poids, une perte de mémoire à court terme et des mouvements oculaires incontrôlés (opsoclonus). Suite à cet incident, l'agence de protection environnementale (EPA) américaine a interdit la production, la vente et l'utilisation du CD aux Etats-Unis en 1977. Les travailleurs exposés à de fortes doses (concentration supérieure à 600 ng/mL dans le sang) ont fait l'objet d'un suivi médical. Il a été constaté que 60% d'entre eux présentaient une hépatomégalie. Toutefois, ces changements anormaux se sont résolus dans les années suivant l'arrêt de l'exposition. En outre, il a été rapporté des problèmes de fertilité chez certains travailleurs. Il a notamment été observé une baisse de libido, sans changement des taux d'hormones sexuelles, ainsi qu'une diminution de moitié du nombre de spermatozoïdes et de leur motilité chez les travailleurs présentant des concentrations sanguines de CD supérieures à 1 mg/L. Ces effets se sont résorbés avec le temps, suite à l'arrêt de l'exposition. Par conséquent, les effets sanitaires du CD restent, de nos jours, particulièrement préoccupants, notamment à cause de la stabilité de ce composé dans l'environnement. En effet, ses propriétés physico-chimiques en fond une molécule extrêmement stable dans l'environnement, capable de se bioaccumuler dans la chaine alimentaire (dans les légumes racines, le poisson ou la viande). Ainsi, les populations antillaises de la Martinique et la Guadeloupe sont constamment exposées à cette molécule, principalement au travers de leur alimentation et via la consommation d'eau polluée.

Les

Des travaux menés par des épidémiologistes de l'Irset, au début des années 2010, à la Guadeloupe ont révélé que l'exposition CD au cours de la vie adulte était associée à une augmentation du risque de cancer de la prostate. Il est aujourd'hui unanimement reconnu qu'il existe certaines fenêtres d'exposition au cours desquelles la sensibilité aux perturbateurs endocrinien est accrue. C'est notamment le cas de la période du développement foeto-embryonnaire. La majorité des participants de l'étude mentionnée précédemment étaient nés avant l'introduction du CD aux Antilles. Ainsi, dans le but d'étudier les effets de l'exposition périnatale au CD sur la grossesse et sur le développement de l'enfant, la cohorte mère-enfant TIMOUN a été mise en place à la Guadeloupe en 2004. Les premiers résultats, publiés dans la première moitié des années 2010, suggèrent que l'exposition maternelle est positivement associée à un risque accru de prématurité. Il n'a pas été rapporté d'association entre exposition et risque de malformations congénitales. Néanmoins, le suivi longitudinal des enfants jusqu'à l'âge de 7 ans a permis de mettre en évidence qu'à l'âge de 3 mois, l'exposition prénatale au CD (mesuré dans le sang de cordon à la naissance) était associée à une augmentation des concentrations circulantes de TSH (hormone thyréostimuline). De plus, à l'âge de 7 mois puis de 18 mois, cette exposition a été retrouvée associée à une réduction du score de préférence visuelle pour la nouveauté ainsi qu'à un plus faible score sur l'échelle du développement de la motricité fine, uniquement chez les enfants de sexe masculin.

L'ensemble de ces observations suggère que l'exposition au CD, au cours du développement prénatal, entraine des effets délétères, plus tard, lors de la vie des individus. Pour comprendre si ces effets peuvent être médiés par des processus épigénétiques, nous avons étudié le profil de la marque H3K4me3 à partir de la chromatine extraite du sang de cordon ombilical. H3K4me3 correspond à l'ajout de trois groupes méthyl au niveau de la lysine 4 de l'histone H3. Il s'agit d'une marque épigénétique associée à un état permissif de la chromatine, permettant la transcription des gènes. Dans le but de déterminer si l'exposition au CD au cours du développement foeto-embryonnaire, caractérisé par une importante prolifération cellulaire, pouvait avoir des effets génotoxique et mutagène, nous avons également réalisé le séquençage de l'ensemble des régions codantes du matériel génétique extrait à partir du sang de cordon ombilical de nouveau-nés de sexe masculin.

Afin d'essayer d'élucider les mécanismes moléculaires impliqués dans les phénotypes observés, nous avons, en outre, mis en place des études expérimentales chez la souris. Dans le but d'étudier les effets épigénétiques induits par l'exposition au CD, nous avons exposé des souris gestantes à une faible dose de CD au cours d'une période de sensibilité, la transition de la lignée somatique vers la lignée germinale. Durant cet événement, les cellules germinales en devenir subissent une reprogrammation épigénétique leur permettant de se défaire de l'épigénome somatique afin de pouvoir acquérir un profil épigénétique propre à la lignée germinale.

Tout dysfonctionnement lors de ce processus peut potentiellement avoir des conséquences sur la génération suivante, en entrainant des altérations épigénétiques dans les futurs spermatozoïdes.

Les travaux réalisés au cours de ma thèse visaient donc à déterminer la capacité du CD à perturber les principales marques épigénétiques du système reproducteur chez les souris directement exposées. Puis, dans un second temps, nous souhaitions étudier la possibilité que ces changements puissent être hérités par les générations suivantes, en l'absence de nouvelle exposition, par un processus appelé héritage épigénétique transgénérationnel.

II. Matériel et Méthodes

Au cours de mes travaux de thèse, nous avons eu recours à diverses techniques expérimentales afin de tester nos hypothèses de travail. Nous avons notamment étudié la mor- De même, dans le but de confirmer les niveaux protéiques des marques histones observés en immunofluorescence, nous avons eu recours à des méthodes d'immunoprécipitation de la chromatine (ChIP). Cette méthode présente le grand avantage de déterminer précisément les régions génomiques couvertes par les marques épigénétiques, ainsi que la proportion de cellules la possédant au sein de l'échantillon. Ainsi, nous avons extrait la chromatine à partir de nombreux organes (testicules, ovaires, prostate, sperme, sang de cordon). Les complexes ADN-protéines furent immuno-précipités à l'aide d'anticorps spécifiques certifiés « ChIP grade », avant d'être élués. Les protéines furent ensuite dégradées et l'ADN purifié. Comme pour l'analyse de l'expression génique, nous avons à nouveau, utilisé à la fois des méthodes ciblées (ChIP-qPCR) et à haut-débit (ChIP-seq).

Afin d'identifier les variants génétiques potentiellement induits dans le sang de cordon par l'exposition prénatale au CD chez les garçons de la cohorte TIMOUN, nous avons procédé à l'extraction de l'ADN à partir ces cellules nucléées du sang de cordon et du sang périphérique de la mère. A partir de l'ADN génomique des enfants nous avons ensuite capturé l'exome complet par hybridation via l'utilisation de sondes complémentaires, tandis que nous avons capturé spécifiquement l'exome du chromosome X pour les mères. Les librairies préparées à partir de ces échantillons ont finalement été séquencées (Exome-seq).

Les détails expérimentaux sont minutieusement décrits dans chacun des articles inclus dans la section « Résultats » de ce manuscrit. Les méthodes présentées dans ce résumé, sont celles auxquelles nous avons eu le plus souvent recours lors de mes trois années de thèse, néanmoins, d'autres techniques ont pu être utilisées et sont également décrites dans les articles concernés. Les procédés d'analyses bio-informatiques sont également abordés plus en détails dans la section « Matériels et Méthodes ».

Il est évident que la recherche scientifique repose sur de l'entraide et de la collaboration. Je n'ai, par conséquent, pas obtenu seul l'intégralité des résultats présentés dans ce manuscrit. L'ensemble des expérimentations animales furent réalisées par les membres de l'équipe « Méiose, Epigénétique, Reproduction » dont je fais partie. Je n'ai pour ma part, participé que de manière très minime et ponctuelle à ces procédures. Ma formation initiale étant la bio-informatique, j'ai plutôt été impliqué dans les processus d'analyse de données de NGS. J'ai, toutefois, eu la chance de me former à la biologie de paillasse au cours de mes trois années de thèse. J'ai notamment participé à l'extraction d'acides nucléiques, ainsi qu'à certains ChIP, immunomarquages, préparation de librairies NGS et réalisation de PCR. De plus, j'ai réalisé les diverses analyses découlant de ces expérimentations : observation au microscope, analyse d'image, quantification de cellules ou de niveau de fluorescence, etc. Afin de déterminer si l'exposition gestationnelle au CD pouvait affecter les marques histones nous avons une distribution de l'histone tri-méthylée H3K4me3 à l'échelle du génome.

III. Résultats et Discussion

Pour cela, nous avons effectué un ChIP-seq à partir de testicules entiers des souris mâles F1 et F3. L'analyse de ces données a révélé que, pour de nombreux loci, l'intensité du signal de ChIP, qui reflète la proportion de cellules possédant cette marque histone, était statistiquement différentes entre les deux groupes de souris. En outre, un quart à un tiers de ces régions différentielles présentaient un signal nul, dans l'une ou l'autre des conditions testées. Cette observation suggère que l'exposition au CD pourrait entrainer un ajout de novo ou au contraire une suppression complète de cette marque histone au sein de certaines régions du génome, et ainsi perturber le réseau transcriptionnel testiculaire. Au total, c'est une cinquantaine de régions différentielles qui ont été retrouvées à la fois chez les mâles F1 et F3. Les gènes associés à ces régions génomiques étaient impliqués dans diverses fonctions telles que l'adhésion et le cycle cellulaire, ou encore la régulation de la transcription. De manière remarquable ces régions semblent être des cibles des régulateurs clés POU5F1 et ZFP57. L'analyse de données disponibles dans la littérature a également révélé que plus de la moitié des gènes cibles de ZFP57 conservent des histones dans les spermatozoïdes, alors que la grande majorité des histones y sont remplacées par des protamines. En outre, ces histones sont détectables dans les premiers stades du développement embryonnaires. Ainsi toutes modifications épigénétiques affectant ces régions seraient susceptibles d'être transmises à la génération suivante.

Dans le but de vérifier si l'expression de Zfp57 était affectée par le CD au moment de l'établissement de l'empreinte parentale, nous avons quantifié son expression dans les testicules des mâles F1 à E15,5. Nous avons observé une diminution de 25% de son niveau d'expression, qui se traduisait aussi par une réduction de l'expression de certains de ses gènes cibles (Itga6 et Ctnnbl1 par exemple).

Puisque le CD est capable de se lier aux récepteurs aux oestrogènes, nous nous sommes demandés si les régions différentielles identifiées par ChIP-seq étaient enrichies en sites de liaison pour ESR1. Par l'utilisation du motif de reconnaissance de ESR1, nous avons prédit un nombre important de sites de liaison au sein des régions différentielles identifiées notamment chez les mâles F1. Certaines de ces prédictions furent ensuite confirmées expérimentalement par ChIP-qPCR à partir de testicules foetaux.

Une des limitations de cette étude est l'utilisation de l'ensemble du testicule comme matériel de départ pour identifier les changements épigénétiques et les changements d'expression génique. En effet, bien que les changements observés en F3 ne puissent survenir que par la lignée germinale, nous ne pouvons pas attribuer les changements observés en F1 à un type cellulaire spécifique. Afin de lier avec davantage de précisions, et de manière directe, les changements entre les générations étudiées, il serait nécessaire d'effectuer des ChIP à partir des spermatozoïdes de souris. Toutefois, nous avons prédit qu'environ 40% gènes régulés par les régions différentielles, notamment des gènes cibles de ZFP57, préservent leurs histones dans le sperme. Ainsi, nous suggérons qu'au moins certains changements épigénétiques induits par l'exposition au CD, peuvent être transmis à la génération suivante via la fraction génomique des spermatozoïdes qui conservant les histones. Cependant, nous ne pouvons pas exclure le fait que certaines modifications pourraient être dérivées secondairement des tissus somatiques de l'organisme, eux-mêmes issus de la fécondation de l'oeuf par le spermatozoïde paternel.

Bien que les mécanismes épigénétiques sous-jacents restent encore incompris, notre étude a permis de révéler que l'exposition au CD au cours du développement affecte le système de reproduction chez les souris mâles jusqu'à trois générations après l'exposition initiale, malgré une dose inférieure à la LOAEL.

B. Effets transgénérationnels induits par le chlordécone dans la prostate

Nous souhaitions ici étudier la possibilité que le CD induise des effets épigénétiques transgénérationnels au sein d'un tissu somatique. Chez l'homme, l'exposition au CD au cours de la vie adulte est associée au risque de cancer de la prostate. Nous avons, par conséquent, souhaité étudier la capacité du CD à induire des effets néfastes sur cet organe, en mettant une fois de plus l'accent sur les aspects épigénétiques. Le protocole expérimental mis en place lors de ce travail de recherche est similaire à celui présenté dans la partie précédente.

Pour identifier les effets du CD sur la morphologie de la prostate, nous avons réalisé des coupes histologiques que nous avons colorées à l'hématoxyline et à l'éosine. Pour chaque souris, la prostate a été classée comme présentant un phénotype PIN (néoplasie prostatique intraépithéliale) ou non. Les lésions PIN sont caractérisées par une prolifération accrue des cellules épithéliales, les cellules formant des couches multiples avec des noyaux et des nucléoles plus sombres et plus grand qu'à la normale. Les coupes de prostates de souris témoins ont montré une architecture tissulaire normale, avec des acini de taille modérée à grande, bordés d'un épithélium cuboïdal ou cylindrique. En revanche, les sections de prostate d'individus issus de souris ayant ingéré du CD présentaient une prolifération des cellules épithéliales, caractérisée par la formation de plusieurs couches superposées de cellules épithéliales présentant un élargissement nucléaire. Bien ce que phénotype ait pu être observé chez certaines souris témoins, la fréquence était six à huit supérieures pour les souris exposées au CD, que ce soit en F1 ou en F3.

Afin de comprendre les mécanismes moléculaires associés aux changements phénotypes observés dans la génération F3, nous avons effectué une analyse transcriptomique par RNA-seq à partir de la prostate des mâles F3. Cette analyse a révélé qu'un peu plus de 200 gènes étaient exprimés de manière différentielle entre les conditions expérimentales. Parmi ceux-ci, nous avons identifié des gènes sur-exprimés dans la prostate de souris exposées au CD. Ces gènes étaient principalement associés au développement de structures anatomiques, au développement de l'épithélium ou impliqués dans des processus cognitifs. De manière remarquable nous avons constaté que plusieurs gènes du cluster HoxA étaient dérégulés. Ces gènes jouent un rôle fondamental dans les processus de régulation du développement et leur dérégulation chez l'adulte a été observée dans plusieurs types de cancers, dont des cancers hormono-dépendants. Par une approche ciblée basée sur des méthodes de PCR quantitative nous avons confirmé que certains de ces gènes étaient également déjà dérégulés dans la prostate des souris F1 exposées au CD.

Puisque nous avons observé des changements morphologiques de la prostate, ainsi que des modifications de l'expression génique, nous avons souhaité examiner le statut de certaines marques épigénétiques pouvant être liées au niveau d'expression des gènes. Pour cela nous avons réalisé des immunomarquages de coupes de prostate contre des marques histones associées à de la chromatine permissive (H3K4me3 et H4ac) ou répressive (H3K27me3). Nos analyses ont révélé une diminution du niveau globale de H4ac et H3K27me3, tandis que celui de H3K4me3 était augmenté dans la prostate des souris F1.

L'analyse de la prostate des souris F3 n'a pas révélé de changement significatif, suggérant que les effets s'étaient résorbés et que si certains avaient persisté ils ne devaient représenter qu'une fraction limitée du génome.

Etant donné que H3K4me3 est une marque épigénétique associée à l'activation transcriptionnelle et que son niveau était globalement augmenté dans la prostate des souris exposées au CD, nous avons souhaité évaluer la distribution de cette marque à l'échelle du génome. Pour cela nous avons réalisé un ChIP-seq à partir de chromatine extraite de prostate de souris F1. Nos analyses ont révélé que plus de 750 loci étaient affectés par l'exposition au CD. Les régions touchées, présentant les différences les plus importantes, étaient notamment liées à des gènes impliqués dans le développement de la prostate (Fgfr2, Foxa1, Hoxa13, Sox9, Stat5a), la morphogénèse des tissus (Etv2, Hoxa11, Jag2, Myc, Ncoa3) et la régulation de la différentiation des cellules souches (Tacstd2, Tbx5, Tgfbr3, Zfp36l2). De façon remarquable, nous avons observé que le niveau de H3K4me3 était globalement augmenté au niveau d'un locus de 115kb couvrant le cluster de gènes HoxA, dont l'expression de certains membres de cette famille de gènes était augmentée dans la prostate des souris F3. Nous avons, par conséquent, voulu mesurer l'intensité du niveau de H3K4me3 pour ce locus dans la prostate des souris F3. L'analyse par PCR quantitative a révélé une augmentation de ce niveau, suggérant que cette altération du paysage épigénétique prostatique pourrait être à l'origine des dérégulations transcriptomiques observées, et donc de modifications morphologiques. C. Effets épigénétiques induits par le chlordécone dans l'ovaire de souris Suite à l'observation de ces nombreux effets du CD sur le système reproducteur mâle, nous nous sommes demandé si les femelles étaient également affectées par une telle exposition. Ainsi, nous avons souhaité évaluer la capacité du CD à induire des changements au niveau de l'ovaire. La procédure expérimentale est similaire aux deux études précédentes.

Toutefois, nos investigations se sont focalisées sur les effets induits par une exposition directe au CD (souris F1). Par conséquent, nous n'avons pas généré de souris de génération F3.

Afin de révéler si l'exposition au CD induisait une augmentation du stress oxydatif, nous avons analysé les niveaux de 8-oxo-G (8-hydroxyguanine), l'une des lésions les plus courantes produites dans l'ADN, dans les noyaux structurellement préservés obtenus à partir d'ovaires embryonnaires (E15,5). L'analyse quantitative a révélé une augmentation d'un facteur 1,4 du niveau de 8-oxo-G dans le noyau des cellules issues de souris exposées au CD.

De plus, nous avons observé une augmentation d'un facteur 2 de l'expression génique de NUDT1, responsable de l'élimination de 8-oxo-G. Ces données suggèrent que l'exposition au CD au cours du développement favorise l'augmentation de stress oxydatif dans les ovocytes embryonnaires.

Nous avions préalablement observé une augmentation des défauts méiotiques chez les mâles suite à l'exposition au CD au cours du développement. Nous avons souhaité savoir si ces effets étaient également retrouvées chez la femelle. Ainsi, nous avons préparé des étalements cellulaires à partir d'ovaires embryonnaires à E15,5 et E17,5 afin de suivre la dynamique de réparation des DSBs (marquage anti-DMC1) en cours de la prophase I de la méiose.

Nos analyses ont révélé que le nombre moyen de foyers de DMC1 était 1,7 fois plus important dans les ovaires E15,5 des souris exposées au CD. Cette différence entre les deux groupes d'animaux était toujours observée à E17,5, ce qui suggère que dans les ovaires de souris exposées, le processus de réparation de l'ADN a été compromis, de la même manière que nous avions pu l'observer chez les mâles. Toutefois, les niveaux d'expression de gènes impliqués dans la réparation de l'ADN (Dmc1, Mre11a, Rad51) n'étaient pas affectés par l'exposition.

Après l'induction de DSBs, une cascade de signalisation médiée par l'ubiquitine aboutit à l'assemblage de plusieurs protéines de réparation sur le site du dommage. Notamment, PRC1 (Polycomb Repressive Complex 1) catalyse la mono-ubiquitination de H2A sur le résidu K119 (H2Aub), une modification de la chromatine impliquée dans la régulation de l'expression des gènes ainsi que dans la réponse aux dommages et la réparation de l'ADN. Ainsi, dans le but de déterminer si l'exposition au CD pouvait altérer cette voie de signalisation, nous avons marqué des étalements de cellules d'ovaire foetaux (E15,5) pour H2Aub. Nos analyses ont révélé une augmentation des niveaux de H2Aub au cours des différentes phases de la prophase I (leptotène et zygotène), aussi bien pour les cellules de la lignée germinale que les cellules somatiques. Nous avons également déterminé que l'expression de l'ubiquitine kinase Rnf8, responsable de l'introduction de H2Aub, a triplé dans les ovaires des souris exposées.

Ces résultats suggèrent que l'augmentation de H2Aub pourrait être expliquée par la génotoxicité induite par l'exposition au CD.

Il existe une relation fonctionnelle entre les marques répressives H3K27me3 et H2Aub.

En effet, l'introduction de H2Aub par PRC1 fournit un site de liaison pour PRC2 qui est responsable de l'introduction de H3K27me3. Ainsi, puisque nous avons observé une augmentation de H2Aub, nous avons souhaité évaluer le niveau de H3K27me3 dans les ovaires foetaux.

L'analyse quantitative des images d'immunofluorescence a révélé une augmentation de H3K27me3 du même ordre de grandeur que celle observée pour H2Aub. Cette augmentation était accompagnée d'une surexpression de Ezh2, le composant fonctionnel du PCR2 responsable de l'introduction de la marque H3K27me3.

Afin de compléter l'analyse du paysage épigénétique des ovaires foetaux, nous avons également évalué le niveau des marques histones H3K4me3 et l'hyperacétylation de l'histone H4, plutôt associées avec un état permissif de la chromatine. Comme pour les deux marques histones précédentes, les cellules somatiques semblaient ne pas affectées par l'exposition au CD, tandis que les ovocytes provenant de souris exposées présentaient une réduction du niveau global de H3K27me3 et H4ac. Les données sur l'ensemble de ces marques histones suggèrent que l'exposition au CD pourrait être responsable de la transition d'un état permissif de la chromatine vers un état plus répressif de celle-ci.

Nous avions précédemment observé une altération globale de l'expression génique au sein des testicules issues de mâles exposés au CD. Ainsi, dans le but de déterminer si ces gènes pouvaient également être affectés dans les organes reproducteurs femelles, nous avons mesuré l'expression génique à partir des ARN extrait des ovaires foetaux. Nos analyses ont révélé que l'exposition au CD entrainait un silençage complet de certains gènes (Rcbtb2, Rbpms) qui étaient sous-exprimés dans le testicule des souris adultes exposées au CD. Nous avons également rapporté la surexpression de Foxo3, un facteur de transcription impliqué dans le développement ovarien.

Dans le but de comprendre comment l'exposition embryonnaire au CD affecte la fonction ovarienne chez les adultes, nous avons évalué le jour d'ouverture vaginale qui signe le début de la puberté chez la souris. Il s'avère que l'exposition au CD est associée à un retard pubertaire par rapport aux souris du groupe témoin. Afin d'étudier les mécanismes moléculaires sous-jacents nous avons mesuré le niveau d'expression de certains gènes au premier oestrus. Nos données montrent une réduction d'expression de marqueurs de cellules germinales (Ddx4), de gènes impliqués dans la voie de signalisation des oestrogènes (Esr2, Inha), dans la réparation de l'ADN (Mre11a, Rad51, Rcbtb2), dans la réponse au stress oxydatif (Nudt1) et dans la méthylation de l'histone H3 (Wdr5). Cette réduction d'expression peut s'expliquer par la transition vers un état chromatidien moins permissif précédemment observé dans les ovaires foetaux et qui était maintenu dans les ovaires adultes, comme nous l'avons montré par des techniques d'immunohistochimie sur des coupes d'ovaires. La réalisation d'un ChIP-seq contre la marque H3K4me3, nous a permis de révéler que les gènes cibles de ZFP57 D. Altérations épigénétiques induites par le chlordécone dans le sang de cordon ombilical de jeunes garçons Outre nos travaux sur le modèle murin, nous avons étudié les altérations des modifications d'histones chez les humains exposés in utero au CD. Ce travail a été réalisé sur du sang de cordon ombilical de jeunes garçons inclus dans la cohorte mère-enfant TIMOUN, pour lesquels la concentration interne en CD est connue. Suite à nos observations chez la souris, nous avons émis l'hypothèse que l'exposition au CD au cours du développement humain pouvait affecter les mécanismes épigénétiques importants pour la régulation de l'expression génique.

Nos travaux se sont focalisés sur des individus de sexe masculin, puisque ceux-ci présentent spécifiquement des troubles l'activité motrice dans les premiers mois de leur vie. De plus, les hommes exposés au CD au cours de la vie adulte ont un risque élevé de développer un cancer de la prostate. Afin de tester notre hypothèse, nous avons donc réalisé diverses analyses à partir des cellules nuclées extraites du sang de cordon ombilical des nouveau-nés. D'après les concentrations sanguines de CD, les échantillons furent séparés en deux groupes, correspondant à des individus faiblement ou fortement exposés au CD. Les données de l'étude chez l'homme ont été complétées par des travaux réalisés sur la lignée cellulaire humaine Ke37, afin d'identifier le mécanisme d'action impliqué. Les cellules furent exposées ou non à une dose de CD relevante vis-à-vis des niveaux d'exposition observés dans la population antillaise.

Dans un premier temps nous avons examiné les niveaux de marques histones impliqués dans le contrôle de la réparation de l'ADN (H4ac), dans la transcription (H3K4me3) et le silençage épigénétique (H3K9me3). Leur quantification dans les cellules de sang de cordon a révélé une réduction globale des marques H3K4me3 et H3K9me3. Afin de déterminer les régions génomiques possiblement altérées par l'exposition au CD, nous avons réalisé un ChIPseq contre la marque H3K4me3. L'analyse de ces données a révélé que les régions affectées étaient particulièrement étendues (>4kb). Le niveau de H3K4me3 était majoritairement réduit, en accord avec les données d'immunofluorescence et les régions altérées abritaient de nombreux gènes codants pour des facteurs de transcription (ARID2, ARID5B, ETS1, ZNF131, NRBF2) ainsi que des gènes encodant des facteurs chromatiniens (CHD2, KMT2E). Les régions arborant une augmentation de cette marque abritaient quant à elles, des gènes codant pour des facteurs de transcription impliqués dans le développement (WNT4, SOX18, JAG2). D'une manière générale, les régions présentant un niveau différentiel de H3K4me3 étaient enrichies en gènes impliqués dans la ségrégation des chromosomes, l'organisation de la chromatine ou le cycle cellulaire. De plus, les protéines encodées par ces gènes comptent de nombreux partenaires de JARID2 et ESR1. En résumé, nos données montrent que l'exposition in utero au CD provoque une diminution globale du l'occupation de H3K4me3, notamment dans les gènes associés à l'organisation de la chromatine, à la réparation de l'ADN, au cycle cellulaire et dans les gènes potentiellement régulés par ESR1. Dans le même temps, la marque H3K9me3 était globalement diminuée au niveau des régions centromériques enrichies en satellites.

Etant donné que H3K9me3 est important pour la fonction des télomères, nous nous sommes ensuite demandé si la diminution de cette marque pouvait être associée à une altération de la longueur des télomères. Pour cela, nous avons quantifier la longueur relative des télomères par une approche de PCR quantitative à partir d'ADN extrait de cellules de sang de cordon. Nos données montrent que l'exposition au CD est associée avec une augmentation d'un facteur 1,7 de la longueur relative des télomères. Parmi l'ensemble des régions présentant une altération de H3K4me3, certaines étaient associées à des gènes impliqués dans la maintenance des télomères (ATM, POT1, PKIB, PRIM1 et 2, RCF3, BRCA2, XRN1). Alors que l'occupation de H3K4me3 à proximité de ces gènes a globalement diminué chez les nouveau-nés exposés au CD, le signal H3K4me3 avait augmenté au niveau du promoteur de TERT, la reverse transcriptase responsable de l'élongation des télomères, suggérant que son niveau d'expression pouvait être augmenté.

Etant donné qu'un élément de réponse aux oestrogènes est présent dans le promoteur du gène codant pour la télomérase (TERT), il est suggéré que les oestrogènes pourraient directement stimuler son expression. Cela a d'ailleurs été observé dans plusieurs lignées cellulaires. Bien que l'activité de la télomérase soit réprimée dans la plupart des tissus somatiques, dans les tissus hautement prolifératifs tels que le système hématopoïétique, le système digestif et la peau, le gène TERT est toujours exprimé, rendant possible la régulation de son expression par les oestrogènes.

Puisque nous avons observé une réduction du niveau de H3K9me3 suite à l'exposition au CD, nous avons voulu déterminer si l'activité des retro-éléments pouvait en être induite.

Pour cela, nous avons eu recours à des digestions enzymatiques afin d'évaluer le niveau de méthylation de trois cytosines localisées dans le promoteur des éléments répétés LINE L1.

Nous avons, ainsi, mis en évidence que l'une des cytosines présentait une réduction du niveau de méthylation dans le sang de cordon des individus exposés à des doses plus importantes de CD, suggérant que l'exposition au CD pouvait conduire à une hypométhylation au moins au niveau de certaines régions. Les données de ChIP-seq montrent également des modifications, aussi bien des augmentations que des diminutions, de l'occupation de la marque H3K4me3au niveau des LINE L1, suggérant une possible dérégulation de leur état transcriptionnel. Dans le but de vérifier cette hypothèse, nous avons quantifié le niveau d'expression des LINE L1 dans les cellules Ke37. Nos analyses ont montré que les niveaux des deux cadres ouverts de lectures correspondant aux LINE L1 étaient augmentés dans les cellules exposées au CD par rapport aux cellules témoins. Ainsi, nos données suggèrent que l'exposition au CD pourrait déclencher l'augmentation de la transcription des rétrotransposons LINE L1, via une diminution de la méthylation au niveau de certains de leurs promoteurs.

Nos données concordent avec plusieurs études ayant montré que l'exposition à des substances toxiques environnementales telles que l'arsenic ou la pollution de l'air, entraine une diminution de la méthylation des LINE L1. Il est suggéré que les dommages oxydatifs de l'ADN affectent la capacité des méthyltransférases à interagir avec l'ADN, entrainant des niveaux de méthylation plus faibles aux sites CpG. Afin de confirmer in vitro les effets observés sur la marque H3K4me3 dans le sang de cordon, nous avons évalué l'occupation de cette marque au niveau de plusieurs promoteurs dans des cellules Ke37. En parallèle, nous avons mesuré le niveau d'expression de ces mêmes gènes puisque la marque H3K4me3 est normalement associée à la transcription. De manière surprenante, l'exposition des cellules Ke37 à deux doses de CD différentes (une dose faible et une élevée) entraîne des effets différents sur la transcription. En effet, l'exposition à la dose la plus faible est caractérisée par une surexpression de certains gènes impliqués dans la réparation de l'ADN (BRCA1), le cycle cellulaire (ARID2) ou la structure de la chromatine (KMT2E). Au contraire, l'exposition à la dose la plus élevée de CD entraine une diminution de leur expression. D'autres gènes, comme ESR1, ne sont dérégulés qu'à la dose la plus faible.

Comme attendu, l'analyse de l'occupation de H3K4me3 au niveau du promoteur des gènes a révélé pour la majorité d'entre eux une corrélation avec le niveau d'expression du gène.

Nous suggérons que la diminution globale des marques histones observée dans cette étude pourrait être la conséquence d'une réponse cellulaire au stress génotoxique induit par le CD. En effet, il a précédemment été rapporté que dans des conditions toxiques la transcription des gènes est globalement réduite.

Nos données suggèrent que l'exposition au CD conduit à des altérations des marques épigénétiques qui régulent l'activation et la répression des gènes. Une dérégulation de ces mécanismes peut augmenter le risque d'instabilité génétique.

E. Altérations génétiques induites par le chlordécone dans le sang de cordon ombilical de jeunes garçons L'ultime partie du travail effectué au cours de ma thèse a consisté en l'étude des altérations génétiques induites par l'exposition au CD. En effet, les travaux menés sur le modèle murin nous ont permis de mettre en évidence la capacité du CD à induire un stress oxydatif et à déréguler les mécanismes de réparation de l'ADN. Ainsi, nous avons émis l'hypothèse que l'exposition prénatale au CD pouvait peut-être entrainer un événement de mutagenèse. Afin de tester notre hypothèse, nous avons analysé les séquences codantes (exomes) de 24 individus de la cohorte TIMOUN. Les ADN génomiques ont été extraits à partir des cellules nucléées du sang de cordon ombilical pour les enfants ou bien du sang périphérique pour les mères. Les 24 individus sélectionnés étaient répartis en trois groupes (faiblement, moyennement ou fortement exposés) selon leur niveau d'exposition déterminé à partir de leur concentration sanguine en CD.

La comparaison de l'exome des individus de la cohorte TIMOUN, par rapport au génome de référence hg38, nous a permis d'identifier près de 3 millions de variants génétiques. La grande majorité d'entre eux sont des polymorphismes d'un seul nucléotide (SNP). Afin de déterminer parmi ceux-ci, quels pouvaient être les variants d'origine somatique, c'est-à-dire non hérités via les gamètes, nous avons déterminé la fréquence allélique de chacun de ces variants dans la population générale. Ainsi, parmi tous les SNP détectés, nous avons exclu l'ensemble des variants ayant une fréquence allélique supérieure à 0,01%.

Dans le but d'obtenir un aperçu de l'impact potentiel des variants sur la structure des protéines, nous avons prédit l'effet de ces mutations par des approches bio-informatiques, et nous avons classifié les variants selon leur éventuelle dangerosité. En nous focalisant plus précisément sur les variants considérés comme délétères (pertes de codon start, gain de codon stop, décalage du cadre de lecture), nous avons identifié que les gènes mutés codent pour des protéines impliquées dans des fonctions hépatiques importantes, des fonctions de transport ainsi que dans le métabolisme. Certaines des mutations identifiées affectaient des gènes connus pour être exprimés de manière aberrante dans des adénocarcinomes (FXR1, CREB1, CEACAM7, PTGES3 ou CAMP).

Dans la cohorte TIMOUN, des prélèvements sanguins maternels étaient disponibles. Afin d'identifier avec davantage de certitude les variants de novo d'origine somatique chez les jeunes garçons, nous avons analysé les variants localisés dans les régions codantes des deux chromosomes X maternels. Les individus de sexe masculin n'ont qu'un seul chromosome X d'origine maternel, le second chromosome sexuel étant le Y hérité du père. Par conséquent, toutes les mutations qui n'ont pas été détectées chez les mères, mais uniquement chez leur fils, sont très probablement généré de novo lors de l'exposition au CD au cours du développement. En appliquant cette nouvelle étape de filtration des données, nous avons détecté environ 15 000 mutations potentiellement dommageables localisées sur le chromosome X. Pour mieux comprendre le mécanisme d'action du CD sur le génome, nous avons recherché les gènes qui accumulaient des mutations chez plusieurs individus. Nous avons ainsi mis en évidence que les gènes impliqués dans les processus de signalisation, l'organogénèse, le transport et le métabolisme étaient fréquemment mutés après une exposition prénatale au CD.

Différents processus mènent à des événements de mutagénèse. Ces différentes voies génèrent une combinaison unique de mutation appelée « signature mutationnelle ». Nous avons donc déterminé la signature mutationnelle induite par l'exposition au CD, en identifiant la proportion de chacune des 96 substitutions potentielles en tenant compte du contexte trinucléotidiques du variant. Nous avons détecté que les substitutions C > T et T > C sont les mutations de novo les plus fréquemment identifiées chez les individus exposés au CD. Le processus de mutation sous-jacent à la première signature mutationnelle (C > T) est probablement la désamination de la 5-méthylcytosine au niveau des dinucléotides CpG, conduisant à des mésappariements C/T qui ne sont pas réparés avant la réplication de l'ADN. Très souvent, la désamination des cytosines conduit à la formation d'uraciles. Une glycosylase, nommée UNG, est capable d'exciser l'uracile au sein de l'ADN entrainant l'apparition d'un site abasique. Dans l'ADN double-brin, ces sites sont aisément réparés par le système BER via l'introduction de cytosines à l'aide de la complémentarité de la guanine présente sur le brin complémentaire. Au contraire, la désamination d'une cytosine sur un ADN simple-brin est difficile à réparer par manque du brin complémentaire. Ainsi, la conversion des cytosines en thymines induite par l'exposition au CD pourrait être due à des imperfections dans la réparation menée par le système BER. Toutefois, des travaux complémentaires seront nécessaires pour révéler précisément le rôle des systèmes de réparation de l'ADN dans la mutagénèse induite par le CD. [START_REF] Griffith | The Significance of Pneumococcal Types[END_REF], they showed that transmission of purified DNA from virulent Pneumococcus strain to a non-virulent strain was necessary and sufficient for the nonvirulent strain to acquire virulent phenotype [START_REF] Avery | STUDIES ON THE CHEMICAL NATURE OF THE SUBSTANCE INDUCING TRANSFORMATION OF PNEUMOCOCCAL TYPES : INDUCTION OF TRANSFORMATION BY A DESOXYRI-BONUCLEIC ACID FRACTION ISOLATED FROM PNEUMOCOCCUS TYPE III[END_REF]. The evidence that DNA is the carrier of genetic information was not obvious at this time, because the idea that proteins are main transmitters of genetic information was dominant. A little less than a decade later, in 1953, James Watson and Francis Crick have suggested a model describing the structure of DNA as a double helix [START_REF] Watson | Molecular structure of nucleic acids; a structure for deoxyribose nucleic acid[END_REF]. This model resulted from the genius and simple observation of experiments and models proposed by others. Particularly, they observed that triple helix model proposed by Linus Pauling and Robert Corey [START_REF] Pauling | Structure of the nucleic acids[END_REF], which suggested that DNA could be composed of a three-chain helix with the bases facing outward and the phosphates in the core, could be not correct. They proposed a new structure of DNA which was based on observation of un-ionized phosphates, which have equilibrated the charge of DNA. Besides, the negative charge of the phosphates near the axis in previous model would create constrain between DNA and phosphate, and thereby it would make this structure unstable.

IV. Conclusion

Later, the X-ray diffraction picture obtained by Rosalind Franklin from high hydrated level of DNA and the exchanges with Erwin Chargaff confirmed the proposed model of DNA.

Nucleotides are structural units of DNA

DNA is a nucleic acid composed of two chains that coil around each other to form a double helix. The two strands of the DNA are oriented in the opposite direction and are said "anti-parallel". Each strand is an assembly of monomeric structure called nucleotides, that are constituted of three elements: one nitrogenous base also known as nucleobases (Adenine (A), Cytosine (C), Guanine (G) or Thymine (T)), one sugar (deoxyribose) and one phosphate group.

The association of two nucleotides on the same DNA strand, by a phosphodiester bond, forms a di-nucleotide (Figure 1).

Adenine and Guanine are purines. They have a double-ring structure, with a pyrimidine ring fused to an imidazole ring and are characterized by their NH2 group, at the C6 carbon in Adenine and C2 in Guanine. The Adenine is the only nucleobase that does not contain an oxygen atom. Cytosine and Thymine are pyrimidines. These two bases have a single pyrimidine-ring structure. The nucleobases form the hydrogen bonds between DNA strands to ensure the stability of the double helix. This unit of two bases from each strand is called a base pair (bp) and is always composed of one purine and one pyrimidine. This "lock-and-key" pattern of base pairing is fixed and it is called base complementarity. The Watson and Crick complementarity is as follows: Adenine is paired with Thymine and forms two hydrogen bonds, while Cytosine is paired with Guanine and forms three hydrogen bonds. Other non-canonical base pairs exists leading to disrupted double helix of DNA, and will be described in the next part of this manuscript.

The nucleobases can be chemically modified and that would lead to non-canonical bases such as 5-methylcytosine or 5-hydroxymethylcytosine (add of a methyl (CH3) or a hydroxymethyl (CH2OH) group at the C5 carbon of the pyrimidine ring of the Cytosine). These epigenetic modifications and their impact on the regulation of the genome will be described in a chapter dedicated for epigenetics, further in this manuscript.

The conformation of DNA described by Watson and Crick, called B-DNA, is the most common form of DNA in the living world [START_REF] Ghosh | A glossary of DNA structures from A to Z[END_REF]. This structure results in a higher accessibility of nucleobases from outside the double helix within the major groove, allowing the interactions with proteins. Interactions between DNA and proteins are essential for important biological processes such as regulation of the transcription, replication or DNA repair. It is within these grooves that the DNA-protein interactions occur through the formation of specific (hydrogen) and unspecific (van der Walls) binding.

Other DNA conformations use the same nucleotides and molecular bonds, but the three-dimensional structure of the helix is different. At least six different DNA conformations (designated A, B, C, D, E, and Z) have been suggested, but only the A, Z, and B conformations were found in nature (Figure 2). From [START_REF] Ghosh | A glossary of DNA structures from A to Z[END_REF].

Compaction and organization of the mammalian genome

Every mammalian cell, except gametes (spermatozoa and egg), possesses two copies of the genetic material. One copy is inherited from the mother, the other one from the father.

Thus, the mammalian genome is therefore called diploid. Considering only one of these two copies, the genome (said haploid genome) of Homo sapiens is approximately 3.3 billion bp large. The human genome is subdivided into 22 pairs of autosome chromosomes and 1 pair of sex chromosomes. Chromosomes are condensed structures that associate a DNA fragment with packaging proteins in a chromatin fiber, which organizes genetic material in a highly ordered structure.

The first level of DNA compaction is the organization into a nucleosome. A nucleosome is a nucleoprotein complex that constitutes about 145-147bp of DNA, wrapped approximately 1.67 times around a histone octamer [START_REF] Luger | Crystal structure of the nucleosome core particle at 2.8 A resolution[END_REF]. Histones are small highly basic proteins; they are rich in lysine and arginine. Histones are encoded by genes which cluster along the chromosomes and, in general, the encoding genes are intron-less.

In a canonical nucleosome, this octamer consists of 2 copies of each of the core histones H2A, H2B, H3 and H4. These core particles are linked to each other by linker histone H1. The main association between histones and DNA are made through structurally conserved histone-fold domains, which organize around 120bp of DNA, and the remaining 13bp at each end is bound by the N-terminal alpha-helix, which is unique to H3 [START_REF] Luger | Crystal structure of the nucleosome core particle at 2.8 A resolution[END_REF]. Nucleosome represents the basic repeating unit of chromatin.

The linker Histone H1 binds the nucleosome at the entry and exit sites of DNA, thus locking DNA and allowing the formation of higher order structure.

Histone tails could be post-translationally modified by adding chemical groups to their tails. These modifications include methylation, acetylation, phosphorylation, ubiquitination, SUMOylation, and others. Histone modifications regulate many processes such as transcription, DNA repair, chromosome condensation and spermatogenesis and oogenesis-specific modifications for the gametogenesis. Detailed information would be provided in the upcoming chapters.

Considering that a base pair has an average length of 0.34 nm, each diploid cell contains approximately 2 meters of DNA [(0.34x10 -9 ) × (6.10 9 )]. In the nucleus, DNA is therefore extremely compacted, condensed and the genome is packed into chromatin. The nucleosomes are folded back to form 30 nanometers of heterochromatin fibers which itself forms loops in an average length of about 300 nanometers. The loops are, in turn, compressed and folded to form fibers that are 250 nm thick. This tightly coiled structure forms the chromatids of a chromosome (Figure 3).

Features of the human genome

The haploid human genome has a length of approximately 3.3 10 9 bp (i.e., 3.3Gb). This total length is divided into 23 autosome chromosomes (numbered from 1 to 22) and 1 allosome chromosome (X or Y). The autosome chromosome numbering is defined according to their length, the chromosome 1 is the longest (around 250 million bp) and chromosome 22 is the shortest (around 51 million bp). In somatic cells, chromosomes are present in the form of 23 pairs of homologous chromosomes. The allosome chromosomes differ by their size, as chromosome X is 2.7 times longer than chromosome Y, and by their gene content. Nevertheless, they share homologous sequences in two regions called "pseudo-autosomal regions" (PAR), PAR1 and PAR2, that are localized at both extremities of the X and Y-chromosomes.

Only a small portion of the genome can be transcribed into mRNA and translated into proteins. These 60Mb (2% of the genome) is said to be "coding" in comparison to the majority of the "non-coding" sequences.

The portion of the gene which is translated into a protein is called the coding DNA sequence. The coding DNA sequence (CDS) of a gene corresponds to the exonic part that starts with a start codon, ATG or AUG in the mRNA molecule, encoding for a methionine and ends with a stop codon (TAA, TAG, TGA) and corresponds to the mature mRNA, which after splicing, is translated into a protein by the ribosome. Both extremities of an mRNA are flanked with untranslated transcribed regions (UTR), referred as 5' UTR and 3' UTR. These regions play a role in the regulation of the genetic expression and as their name indicates, they are not translated and do not belong to the coding sequences.

Main elements of the non-coding part of the genome will be briefly presented. They include DNA that codes for non-coding RNAs (ncRNAs), repetitive DNA elements, pseudogenes as well as DNA sequences located at particular regions such as telomeres and centromeres. The proportion of each of these elements within the human genome is provided in Figure 4.

A ncRNA is an RNA resulting from DNA transcription that is not further translated into a protein by the ribosomes. There is large diversity in the functions of ncRNA. This includes ribosomal RNA (rRNA), transfer RNA (tRNA), micro RNA (miRNA), long non-coding RNA (lncRNA), piwi-interacting RNA (piRNA), small interfering RNA (siRNA), small nuclear RNA (snRNA), small nucleolar RNA (snoRNA), small Cajal body-specific RNA (scaRNA), extracellular RNA (exRNA).

Repetitive elements are the most abundant sub-category of non-coding DNA. They can be subdivided into two types according to their sequence features. First is the interspersed repetitive DNA, whose sequences repeats in different non-adjacent regions of the genomes.

This class includes microsatellite (2-6 bp repeats, mostly 1 to 4 nucleotide repeats), minisatellite (15-40 bp repeats) and satellite (100 bp repeats) DNA. Interspersed repetitive DNA differs from the second class named tandem repeat DNA, in which the repeated motifs are directly adjacent to each other. Some transposable elements (TEs), retro-elements (RE) and endogenous retrovirus (ERVs) do not produce a functional protein. Among them are Alu repeat elements that are part of the SINEs (short interspersed nuclear elements), and cover approximately 11% of the genome [START_REF] Batzer | Alu repeats and human genomic diversity[END_REF]. According to an estimate, the largest part of the human genome (around half of this total size) is constituted of repetitive sequences [START_REF] Batzer | Alu repeats and human genomic diversity[END_REF][START_REF] Schmid | Sequence organization of the human genome[END_REF]. Some of these repeats do not have functional activity while other have [START_REF] Britten | Transposable element insertions have strongly affected human evolution[END_REF][START_REF] Jurka | Repetitive sequences in complex genomes: structure and evolution[END_REF].

Notably, Line L1 (L1), is the most abundant retroelement (18-20% of mammalian genomes) and it contains 5'UTR and two open reading frame (ORF) sequences. Only a small fraction of L1 elements is capable of retro-transposition and cause genome rearrangements.

For example, L1Base 2 database (available at: http://l1base.charite.de/), contains 146 L1s with full sequence and 107 more with intact ORF2, which is responsible for retro-transposition, suggesting that there are more than 250 potentially active L1 elements in Homo sapiens.

Other characteristic elements that belong to the non-coding part of the genome are pseudogenes. They are genes which were altered during evolution and which accumulated some inactivation mutations. A pseudogene is defined as any genomic sequence that is similar to another gene but is defective [START_REF] Vanin | Processed pseudogenes: characteristics and evolution[END_REF]. Pseudogenes are classified into two mains classes: processed and unprocessed pseudogenes. First class is derived from the retro-transposition of processed mRNAs [START_REF] Esnault | Human LINE retrotransposons generate processed pseudogenes[END_REF], while those from the second are derived from segmental duplication. There are other classes of pseudogenes which are less abundant.

For example, "unitary pseudogenes" are normally generated by inactivation of a unique copy gene, and therefore no functional copy of the gene in the genome exists. Finally, some rare pseudogenes correspond to unfunctional genes based on their sequence in the reference genome, but these genes could be functional in certain individuals [START_REF] Frankish | GENCODE reference annotation for the human and mouse genomes[END_REF][START_REF] Pei | The GENCODE pseudogene resource[END_REF]. 14,324 pseudogenes are annotated in human genome according to the GENCODE database (V35, August 2020), with 75% of them accounting for processed pseudogenes. From [START_REF] Gregory | Synergy between sequence and size in Large-scale genomics[END_REF].

The ends of chromosomes consist of repeated sequences called telomeres, which are designed to protect the chromosome ends. Indeed, the abrupt termination of chromosomes could be considered by cellular DNA repair system as a double-stranded break (DSB) in DNA, and their repair activities will lead to chromosome fusions. During DNA replication, the lagging strand is synthesized using Okazaki fragments which need the binding of RNA primers downstream of the neo-synthetized DNA fragment. As a consequence, at each duplication, the ends of the chromosome are shortened. Therefore, telomeres are buffers used to preserve the coding regions from truncation and their limited length determines a lifespan of the cell. Telomere shortening is associated with cellular senescence.

The sequence 5'-TTAGGG-3' is repeated several thousands of times at telomeres in human cells, ranging from 3 to 12kb in length. However, telomere length varies considerably between cell types and can be altered by environmental factors. Telomere sequence is transcribed into an RNA named TERRA (TElomeric Repeat-containing RNA), which interact with the proteins of the Shelterin complex, which serves to protect the telomeres from DNA repair mechanisms and also to inhibit telomerase activity and therefore to avoid the abnormal telomere elongation. Any deregulation of proteins of the Shelterin complex leads to telomere fusions. From the other hand, telomeres could be elongated. Telomerase, a reverse transcriptase, can elongate telomeres, by adding the 6-nucleotides repeat to the telomere end. This enzyme is expressed at very low level or even not at all in most of the somatic cells, with the exception of B lymphocytes [START_REF] Martens | Telomere maintenance in human B lymphocytes[END_REF] and some other tissues. The enzyme is aberrantly overexpressed in many cancers and thereby cells become immortal.

Alternatively, telomeres could also be extended through another mechanism called alternative telomere lengthening. This phenomenon is based on recombination events and is mostly observed in cancerous cells. This mechanism occurs also physiologically in pluripotent stem cells. However, even if underlying molecular mechanisms are not clear, they are considered to be different in cancer cells and pluripotent stem cells. Indeed, cancer cells exhibit heterogeneous telomeres, telomeric sister chromatin exchanges and dysfunctional telomeres, but these features are not found in pluripotent stem cells [START_REF] Zhao | Alternative Lengthening of Telomeres (ALT) in Tumors and Pluripotent Stem Cells[END_REF].

Another important element of chromosomes is the centromere region. The centromere enables the correct segregation of genetic material between daughter cells following cell division. DNA at the centromere is constituted of repeat tandem sequences (satellites). Centromeric chromatin is characterized by the incorporation of the histone H3 variant CENP-A (centromere protein A), a replacement of H3, as well as H3K4me2 mark associated with active chromatin [START_REF] Schalch | Structure of centromere chromatin: from nucleosome to chromosomal architecture[END_REF]. However, centromere is not homogeneously covered and some regions display high H3K9me3 and low H3K4me2 [START_REF] Ribeiro | A super-resolution map of the vertebrate kinetochore[END_REF]. This genetic locus can be subdivided into two parts: the centromere core, marked by CENP-A nucleosomes, and the peri-centromeric region that flanks centromere upon both directions, which is associated with heterochromatin features (H3K9me2/3). Core centromere is the attachment site for the kinetochore while pericentromeric regions are responsible for sister chromatid cohesion.

Comparative genomics: How mouse genome differs from human genome?

In the early 2000s, the mouse was the second mammalian species whose genome was sequenced (International Human Genome Sequencing Consortium, 2001;[START_REF] Venter | The sequence of the human genome[END_REF].

Mouse is a common animal model used in many in vivo biological experiments due to high reproducibility of results and possibility to perform gene ablation experiments. Besides that, they have metabolic pathways very similar to human. Many inbred and outbred strains are available. Comparative analysis of two genomes revealed that humans and mice share a similar genetic background, and around 90% of their genome can be portioned into regions of conserved synteny (Mouse Genome Sequencing Consortium et al., 2002). Thus, the divergence between two species mainly occurred in ancestors in non-coding regions.

Around 40% of the nucleotides of the 3.1Gb-human genome can be aligned to the 2.7Gb-mouse genome. Table 1 gives a summarized overview of the both reference genomes.

Table 1. Similarity between human and mouse genomes. From [START_REF] Breschi | Comparative transcriptomics in human and mouse[END_REF].

B. The alterations of nucleic sequence and mutations

Every second, DNA in each cell is damaged. This happens at a frequency of the order of tens of thousands of times per cell per day [START_REF] De Bont | Endogenous DNA damage in humans: a review of quantitative data[END_REF][START_REF] Lindahl | Instability and decay of the primary structure of DNA[END_REF]. DNA damages can be caused by endogenous, or either by exogenous factors.

Damage of the DNA

The majority of endogenous DNA damage comes from the interaction of DNA with its immediate surrounding molecules, such as reactive oxygen species (ROS) that are produced in the cells due to electron transfer chain reactions in mitochondria, which is required to produce energy in the form of ATP as well as due to physiological metabolic processes in the cells.

It is widely accepted that the frequencies of genetic mutations are greatly increased by influence of various environmental factors including exposure to UV-light, chemicals, radiation, hormones and by social lifestyle factors. The accumulation of somatic mutations in oncogenes and tumor suppressor genes could result in the conversion of normal cells to malignant. The genes required for maintaining the genome integrity such as DNA repair, homologous recombination, cell cycle, epigenetic modifiers are the most common cancer driver genes.

On an average, human genome contains around 4 million germline sequence variants compared to the reference genome (1000 Genomes Project Consortium et al., 2012). Although variants in protein-coding regions have received the most attention, numerous studies have noted the importance of non-coding variants in cancer [START_REF] Khurana | Role of non-coding sequence variants in cancer[END_REF]. The mutation events are random and could be theoretically generated in any genomic region, however, some regions in the genome are more mutation-prone. So called "late replicating" and "heterochromatin-rich" regions have more mutations than early replicating euchromatic regions [START_REF] Stamatoyannopoulos | Human mutation rate associated with DNA replication timing[END_REF]. The most plausible explanation for the occurrence of mutations at error-prone regions is that the DNA repair is less efficient or use error-prone mechanisms for DNA repair. Moreover, at heterochromatin regions, DNA is less accessible to DNA repair factors due to compact structure of chromatin. For example, it has been shown that laminaassociated heterochromatin at the nuclear periphery is more vulnerable to mutation generation compared to euchromatin regions [START_REF] García-Nieto | Carcinogen susceptibility is regulated by genome architecture and predicts cancer mutagenesis[END_REF]. From the other hand, mutations at late replicating regions face stalling of the replication forks, have exhausted dNTP pool that consequently lead to the accumulation of single-stranded DNA (ssDNA) regions. SsDNA is more susceptible to endogenous and environmental damage, and can potentiate mutagenesis directly [START_REF] Stamatoyannopoulos | Human mutation rate associated with DNA replication timing[END_REF].

Besides genomic location, mutations have some predisposition to nucleotide sequences. For example, whole genome sequencing in a cohort of 221 melanoma samples detected that the vast majority of highly recurrent mutation promoter sites were found in conjunction with TTCCG, the motif recognized by ETS (Erythroblast Transformation Specific) factors, suggesting that ETS binding affects the mutational landscape of melanoma [START_REF] Elliott | Elevated pyrimidine dimer formation at distinct genomic bases underlies promoter mutation hotspots in UV-exposed cancers[END_REF].

It was proposed that Nucleotide Excision Repair (NER) mechanism was impaired near ETS binding sites, and thereby, can further generate mutations at recurrent hotspot positions [START_REF] Elliott | Elevated pyrimidine dimer formation at distinct genomic bases underlies promoter mutation hotspots in UV-exposed cancers[END_REF].

Some other factors such as chromatin environment and epigenetic factors could contribute to mutation landscape. Analysis of induced mutations in cell lines showed that H3K36me3 chromatin is normally protected from somatic mutations because of increased NER activity [START_REF] Li | The histone mark H3K36me3 regulates human DNA mismatch repair through its interaction with MutSα[END_REF]. However, exposure to some carcinogens results in increased activity of non-canonical, error-prone, DNA Mismatch repair (MMR) pathway involving an interaction with hMSH6 PWWP domain of hMutSα. The absence of this interaction results in an increased relative mutation rate in H3K36me3-marked regions [START_REF] Peña-Diaz | Noncanonical mismatch repair as a source of genomic instability in human cells[END_REF]. Therefore, some environmental carcinogens could redistribute mutations to the more important regions of the genome at transcribed regions.

Several environmental factors are known to be source of the mutation induction. The ultraviolet (UV) light is one most common mutagen. For example, in UV-induced melanoma, mutations were detected in CDKN2A, PTPRT, GRIN2A, DCC, and GRM3 genes [START_REF] Gorlov | Human genes differ by their UV sensitivity estimated through analysis of UV-induced silent mutations in melanoma[END_REF].

Some other environmental chemicals such as asbestos could lead to induction of mutation [START_REF] Sneddon | Whole exome sequencing of an asbestos-induced wild-type murine model of malignant mesothelioma[END_REF]. Importantly, asbestos induces malignant pleural mesotheliomas (MPMs) in mice, and the tumors are almost identical to those found in humans [START_REF] Davis | Establishment of a murine model of malignant mesothelioma[END_REF]. In humans, whole-exome sequencing of DNA from 22 MPMs and their matched blood samples identified 517 somatic mutations across 490 mutated genes. Integrative analysis of mutations and somatic copy-number variants revealed frequent alterations in BAP1, NF2, CDKN2A, and CUL1 genes [START_REF] Guo | Whole-exome sequencing reveals frequent genetic alterations in BAP1, NF2, CDKN2A, and CUL1 in malignant pleural mesothelioma[END_REF]. Frequent inactivation of SETDB1 mutations was detected in MPMs in another study [START_REF] Hylebos | The Genetic Landscape of Malignant Pleural Mesothelioma: Results from Massively Parallel Sequencing[END_REF].

The consummation of plant supplements in herbal medicine that contains aristolochic acid, is associated with urothelial carcinoma of the upper urinary tract (UTUC). Exome sequencing of UTUCs from 19 individuals exposed to aristolochic acid revealed a large number of somatic mutations with patterns of mutations that was distinct from the ones observed in other tumors, such as UV-induced and tobacco smoke-induced cancers. The mutations were predominantly located on the non-transcribed strand, with a strong preference for deoxyadenosine in a consensus sequence (T/CAG) motif which overlaps with the canonical splice acceptor site [START_REF] Hoang | Mutational signature of aristolochic acid exposure as revealed by whole-exome sequencing[END_REF].

Aflatoxins produced by the fungi Aspergillus flavus and Aspergillus parasiticus are considered to be another source of natural carcinogens. Millions of people worldwide are exposed to Aflatoxins. It was found that in hepatocarcinomas (HCCs) associated with Aflatoxin exposure, the mutation frequently contained C>A transversions, which were also often detected within the sequence motif GCN. In another study associated with Aflatoxin exposure, frequent mutations in the adhesion G protein-coupled receptor B1 gene (ADGRB1) was detected, and the presence of this mutation was associated with increased capillary density of tumor tissue [START_REF] Zhang | Genetic Features of Aflatoxin-Associated Hepatocellular Carcinoma[END_REF]. It is suggested that mutations in this gene are associated with increased vascularization and expression of PD-L1 in HCC tissues [START_REF] Zhang | Genetic Features of Aflatoxin-Associated Hepatocellular Carcinoma[END_REF].

Growing body of evidences suggests that urbanistic pollution Particulate Matter with the size of 2.5µm (PM2.5) have strong impact on human health. Exposure to PM2.5 increases DNA damage and causes alterations in DNA damage response genes as well [START_REF] Chu | Personal exposure to PM2.5, genetic variants and DNA damage: a multi-center population-based study in Chinese[END_REF].

Occupational exposure to pesticides had a significant effect on the frequency of micronuclei [START_REF] Sailaja | Genotoxic evaluation of workers employed in pesticide production[END_REF], suggesting that exposure to pesticides could be genotoxic as well.

In a study that screened somatic mutations in TP53 in lung cancer patients, the pesticide exposure is proposed to be one of the potential reasons of induction of tumorigenesis [START_REF] Bumroongkit | TP53 gene mutations of lung cancer patients in upper northern Thailand and environmental risk factors[END_REF].

Certain life-style factors such as tobacco consumption could be also implicated in increasing the risk of cancerogenic mutations. The analysis of somatic mutations in 5,243 cancers of types showed that tobacco smoking confers an elevated risk of cancer induction. The indirect activation of DNA editing by APOBEC cytidine deaminases contribute to mutational process [START_REF] Alexandrov | Mutational signatures associated with tobacco smoking in human cancer[END_REF]. In smoking-related head and neck squamous cell carcinomas (HNSCCs) loss of TP53 function was often reported and there is strong variation in CDKN2 copy number (Cancer Genome Atlas Network, 2015).

Mutational signatures

The "mutational signatures" were established for 35 cancer types in a large study that analyzed 4,938,362 somatic substitutions and small insertions/ deletions from 7,042 primary cancers and re-sequenced matched DNA from normal tissue from the same patient [START_REF] Alexandrov | Signatures of mutational processes in human cancer[END_REF]. All classes of mutations and their sequence context or the transcriptional strand on which it occurs were reanalyzed and based on this analysis, more than 21 mutational signatures were defined. For example, predominant C>T changes were detected in signatures 1A/ B, 6, 7, 11, 15, 19. It is suggested that signature 1A/B is probably related to the elevated rate of deamination of 5-methyl-cytosine which results in C to T transitions which predominantly occurs at NpCpG trinucleotides. Notably, signature 2 is characterized primarily by C>T and C>G mutations at TpCpN trinucleotides. It was suggested that high activity of members of the APOBEC family of cytidine deaminases, which convert cytidine to uracil, is involved in this process.

Besides small variants such as SNPs, large Structural Variants (SV) such as deletions, duplications, inversions and translocations could be generated when exposed to environmental toxicants. Those mutations are commonly associated with homologous recombination mechanisms and they are increased with the presence of repeated elements at both sites of breakage point. Substantial numbers of larger deletions (up to 50 bp) with overlapping microhomology at breakpoint junctions were found in breast, ovarian and pancreatic cancers with major contributions from signature 3. In those cancers, BRCA1 and BRCA2 were inactive due to mutations. From the other hand, BRCA1 and BRCA2 proteins are implicated in homologous recombination, and their inactivation could be responsible for triggering error-prone alternative DNA repair mechanisms.

Thus, mutation signatures analysis revealed that each type of cancer could have one or more signatures, and the mechanisms underlying the mutation induction include deamination of Cytosine, involvement of error prone mechanisms of DNA repair, transcription biased DNA repair. However, for many environmental agents, the mechanisms and capacity to induce somatic mutations remains largely unknown.

Mechanisms of DNA repair

In the cell, DNA repair is based on several mechanisms that allow to deal with DNA damage. The DNA damage response is a set of mechanisms that sense DNA damage, signal its presence and promote the subsequent repair. The precise recruitment of factors involved in the response to DNA damage is regulated in time and space. The recruited factors and activation of the subsequent pathways depend on the nature of the damage as well as the cell cycle phase. For example, base excision repair (BER), corrects oxidative, deamination, alkylation and abasic single base damage that are not perceived as significant distortions of the DNA helix. This pathway is mainly active during G1 phase. Another pathway involved in singlestrand DNA damage repair is the NER which is implicated in the removal of bulky lesions that result from UV radiation or exposure to chemotherapeutic agents.

In addition to these single-stranded breaks, the cell suffers from most toxic damage:

double-stranded DNA breaks. These breaks are potentially more damaging to the cell since it 52 can no longer use the information from the complementary strand to repair the injury. To face this type of damage, the cell once again possesses a wide range of mechanisms, more or less faithful in their way of resolving the lesion. The two most important pathways for DSB repair are homologous recombination (HR) and non-homologous end joining (NHEJ). HR is the most reliable mechanism since it relies on the use of a homologous chromosome to repair the break, while NHEJ directly binds the both ends of the break without using a template. The latter is therefore considered to be an error-prone mechanism. An overview of DNA repair pathways and the implicated factors is provided in Figure 5. There are some excellent reviews dedicated to this complex but fascinating subject which will not be detailed further in this manuscript. For example, see [START_REF] Chatterjee | Mechanisms of DNA damage, repair, and mutagenesis[END_REF] and [START_REF] Haber | DNA repair: the search for homology[END_REF]. Although the cell is armed with a myriad of repair mechanisms, there are times when these factors fail during the repair process, either by not properly repairing the lesion or by simply not detecting it. In either of these cases, if the cell is not directed to the apoptosis pathway, the programmed cell death, then the resulting mutation is passed on to daughter cells.

There are various types of mutations. Indeed, they can affect a single nucleotide or a set of several nucleotides. The consequences of the mutation can also be diverse: change of 53 amino acid in the protein sequence, shift of the reading frame, formation of preliminary stop codon or protein translation loss.

Point mutations and short indels

The first class is composed of short variants. This class of variants includes point mutations, i.e., the substitution of a nucleotide for another, as well as short insertions or deletions (indels) (Figure 6). Point mutations can be subdivided into two groups: transition and transver- Short indels that occur within a coding sequence can lead to either a frameshift mutation, if the number of nucleotides inserted or deleted is not a multiple of three, or if there is an insertion or deletion of one or more amino acids within the protein. In this last case the mutation is called in-frame. As for point mutations, effects of short indels are variable, with frameshift mutations being, in general, more deleterious than in-frame ones.

54

Large structural variants

Structural variant (SV) is defined as a genomic region that displays a modification in copy number, orientation (inversions) or chromosomal location (translocation), between individuals, or generally compared to the reference genome (Figure 7). The change in copy number can be a gain, such as an insertion or a duplication of a genomic locus, or a loss (deletion).

These cases of unbalanced SV are gathered within the term CNV (copy number variations).

Several mutational mechanisms can lead to the generation of SV. These include recombination errors, such as non-allelic homologous recombination which results from the misalignment of very similar sequences during cell division, notably in the case of segmental duplications or long stretches of homology (Alu sequences or L1 elements). This usually results in SVs sharing the same breakpoints, leading to recurrent and large SVs [START_REF] Conrad | Origins and functional impact of copy number variation in the human genome[END_REF] Errors generated in DNA break repair is another mechanism that leads to SV. If doublestranded DNA breaks occur in the absence of homologous copy, error-prone mechanisms, such as NHEJ or microhomology-mediated end joining (MMEJ), are used to repair the break.

NHEJ introduces short insertion or deletion at the breakpoint junction, while MMEJ often leads to translocations and causes deletion at the breakpoint; and is therefore source of genomic instability [START_REF] Escaramís | A decade of structural variants: description, history and methods to detect structural variation[END_REF]. Errors during DNA replication is also a source of SV. For example, microhomology-mediated break-induced replication (MMBIR) can lead to various complex chromosomal rearrangements and trigger genomic instability. This mechanism results from a template-switching mutation event [START_REF] Hastings | Mechanisms of change in gene copy number[END_REF].

Figure 7. Different types of large structural variants. Adapted from [START_REF] Escaramís | A decade of structural variants: description, history and methods to detect structural variation[END_REF].

There are regions of the profound chromosomal instability, known as common fragile sites (CFSs), which gets activated in tumors and lead to altered genetic information during the replication [START_REF] Bignell | Signatures of mutation and selection in the cancer genome[END_REF]. Very often, these are very large genes with higher AT content, which are prone to replication fork stalling (McAvoy et al., 2007a(McAvoy et al., , 2007b;;[START_REF] Smith | Large common fragile site genes and cancer[END_REF].

The activity of HR at common fragile sites could initiate cancer. For example, genes at CFS, such as FHIT and WWOX are tumor suppressors and are often deleted in many cancers [START_REF] Ishii | Expression of FRA16D/WWOX and FRA3B/FHIT genes in hematopoietic malignancies[END_REF][START_REF] Paige | WWOX: a candidate tumor suppressor gene involved in multiple tumor types[END_REF][START_REF] Pichiorri | Fhit tumor suppressor: guardian of the preneoplastic genome[END_REF], most likely due to replication stress [START_REF] Okumura | Fragile gene product, Fhit, in oxidative and replicative stress responses[END_REF]. The regions of CFSs are conserved between species. For example, our analysis of very large genes in the mouse genome with increased AT content, revealed that these are genes are often deleted in cancers in humans (

Pcdh15

A secreted isoform is a potential marker for NK/T cell lymphomas. [START_REF] Rouget-Quermalet | Protocadherin 15 (PCDH15): a new secreted isoform and a potential marker for NK/T cell lymphomas[END_REF]

Pde4d

The protein promotes proliferation and angiogenesis of lung cancer by crosstalk with HIF. [START_REF] Pullamsetti | Phosphodiesterase-4 promotes proliferation and angiogenesis of lung cancer by crosstalk with HIF[END_REF]

Gpc6

The protein plays a role in migration of carcinoma cells is a prerequisite for the metastatic dissemination of solid tumors. [START_REF] Yiu | NFAT promotes carcinoma invasive migration through glypican-6[END_REF] Fhit Spanning fragile site and it is a renal carcinomaassociated breakpoint, is is abnormal in digestive tract cancers, lung cancer, Merkel cell carcinoma and breast carcinomas. [START_REF] Malak | FHIT Gene Expression in Acute Lymphoblastic Leukemia and its Clinical Significance[END_REF][START_REF] Negrini | The FHIT gene at 3p14.2 is abnormal in breast carcinomas[END_REF][START_REF] Ohta | The FHIT gene, spanning the chromosome 3p14.2 fragile site and renal carcinoma-associated t(3;8) breakpoint, is abnormal in digestive tract cancers[END_REF]Sozzi et al., 1996a[START_REF] Sozzi | The FHIT gene 3p14.2 is abnormal in lung cancer[END_REF]

Prkg1

Novel kinase fusion transcripts found in endometrial cancer. [START_REF] Tamura | Novel kinase fusion transcripts found in endometrial cancer[END_REF] 6. The 1,000 and 2,504 Genomes project

The 1,000 genomes project is a project that spanned 7 years, between 2008 and 2015, which aimed to identify as many relatively common genetic variants as possible in the populations studied (i.e., with a frequency of at least 1%). In this project, five major populations were considered, including populations in or with ancestry from Europe, East Asia, South Asia, West Africa and America. This was the first large-scale project to sequence the genome of a significant number of individuals. The aim of the International Genome Sample Resource (IGSR)

was to quickly provide this data to the entire international scientific community.

Nonetheless, despite the dramatic drop in sequencing costs, it was not possible to sequence all the genomes in the collection to a very great depth. The project was therefore subdivided into 4 distinct phases with different objectives, considering different strategies and depth of sequencing. The first pilot phase was carried out in order to determine if the detection of common variants was possible with a coverage comprised between 2 and 4X. For this, 180 complete genomes were sequenced with a low coverage (2-4X), 2 trios (mother-father-child)

were sequenced to reach a coverage between 20 and 60X; and finally, for 900 individuals, 1,000 gene regions were sequenced to obtain 50x coverage.

Analysis of the data helped to identify approximately 15 million SNPs, 1 million small insertions / deletions (indels of 1 to 50bp) and 20,000 SV. The results, published in 2010 in Nature, made it possible to determine that there are highly variable regions in the genome (human leukocyte antigen (HLA), or sub-telomeric regions) while others were particularly conserved (e.g. a region around 3p21). It also demonstrated that populations with African ancestors exhibited the highest number of new SNPs, thus reflecting the greater genetic diversity of African population [START_REF] Durbin | A map of human genome variation from population-scale sequencing[END_REF].

This first step confirmed the robustness of the sequencing methods, both whole-genome shotgun or targeted approaches. In addition, this study validated the effectiveness of algorithms and bioinformatic methods dedicated to calling variants. Finally, the main objective was achieved since it was confirmed that low coverage sequencing is effective in detecting variations at the genomic scale, while the use of targeted methods allow the precise detection of rare variants in regions of interest, encoding proteins. All these aspects made it possible to move forward to the next phases of the 1,000 Genomes project.

The final data set after all three phases of the project contains data for 2,504 individuals originated from 26 populations [START_REF] Auton | A global reference for human genetic variation[END_REF][START_REF] Sudmant | An integrated map of structural variation in 2,504 human genomes[END_REF]. For every individual low coverage data and exome sequences are available. Besides, for 24 individuals, high coverage sequencing was also performed to validate the obtained results. All the identified

II. Epigenetics, the role in regulation of gene expression

It was in 1942 that Conrad Waddington, a developmental biologist, coined the term "epigenetics" [START_REF] Waddington | The epigenotype. 1942[END_REF], to establish causal relations between the genotype and the phenotype, in order to understand the mechanisms of the development. He proposed in 1942, the word "epigenetics", which described all the processes linking the genotype and phenotype together. A new discipline was born, although the definition of epigenetics has evolved in the following years. Today, the term of epigenetics is rather used to define the changes in gene expression or chromatin structure which do not result from changes in the primary DNA sequence.

The role of the main effectors of the epigenetics, DNA methylation, histone modifications and lncRNAs, will be introduced in the following sections. An extensive summary of their known functions in the physiological and pathological context will be described, starting with the most studied epigenetic mark, DNA methylation.

A. DNA methylation and hydroxymethylation

DNA methylation refers to the methylation (addition of -CH3 group) of the fifth carbon of cytosines (5mC), and this process is catalyzed by a family of enzymes known as DNA methyltransferases (DNMTs). In eukaryotes, this chemical modification is mostly found at CpG dinucleotides. These modifications were first observed in 1948 [START_REF] Hotchkiss | The quantitative separation of purines, pyrimidines, and nucleosides by paper chromatography[END_REF], while a putative role in gene regulation was proposed 25 years later [START_REF] Holliday | DNA Modification Mechanisms and Gene Activity during Development[END_REF]. Confirmation of a functional link between DNA methylation and gene repression was confirmed a few years later [START_REF] Razin | DNA methylation and gene function[END_REF]. Silencing of gene expression via DNA methylation can result from the recruitment of chromatin remodelers to form heterochromatin. For example, it has been shown that DNMTs function in complex with histone-modifying enzymes, H3K9

(Histone 3, Lysine 9) methyltransferases [START_REF] Estève | Direct interaction between DNMT1 and G9a coordinates DNA and histone methylation during replication[END_REF] and histone deacetylases [START_REF] Fuks | DNA methyltransferase Dnmt1 associates with histone deacetylase activity[END_REF].

DNA methylation is a fundamental process involved in development as well as in several other processes including, for example, genomic imprinting, X-chromosome inactivation (XCI), repression of transposable elements or carcinogenesis. The role of DNA methylation in these processes would be discussed in the following sections.

In mammals, the genome content generally has a lower frequency of CpGs compared to the expected frequency of this dinucleotide. An exception is observed in genomic regions, called CpG islands (CGIs) which consist of relatively short regions (approximately 1kb) that are enriched in CpGs. Formal definition of CGIs is based on three criteria to describe these regions: size of the region should be at least 200bp, the G/C content should be at least 50% and the ratio between observed and the expected CpG frequency should be at least 0.6 [START_REF] Gardiner-Garden | CpG Islands in vertebrate genomes[END_REF]. Around 60-70% of the ~25,000 known genes in the human genomes possess CGIs at their promoter [START_REF] Saxonov | A genome-wide analysis of CpG dinucleotides in the human genome distinguishes two distinct classes of promoters[END_REF]. Approximately half of the CGIs are located at the transcription start site (TSS), while 25% are intragenic and 25% intergenic [START_REF] Deaton | CpG islands and the regulation of transcription[END_REF]. Transcription of the remaining genes is initiated via TATA boxes. Independently from these CpG dinucleotides, methylation can also occur at other sites.

For example, it has been shown that non-CpG sites are methylated in neurons, pluripotent stem cells and ovaries [START_REF] Jang | CpG and Non-CpG Methylation in Epigenetic Gene Regulation and Brain Function[END_REF][START_REF] Laurent | Dynamic changes in the human methylome during differentiation[END_REF][START_REF] Lister | Human DNA methylomes at base resolution show widespread epigenomic differences[END_REF].

In humans, a small fraction of the genome with 5mC and representing less than 1% of all the nucleotides in the genome are largely localized outside the CGIs [START_REF] Rollins | Large-scale structure of genomic methylation patterns[END_REF].

However, this fraction represents between 70 and 80% of the CpG dinucleotides [START_REF] Blackledge | CpG island chromatin[END_REF], which regulate the gene expression.

DNA methyltransferases

DNMTs are the enzymes responsible for the introduction of methylation marks on the DNA. They catalyze the transfer of a methyl group from S-adenosylmethionine (SAM) to the fifth carbon of a cytosine. The family of DNMTs is composed of 5 members: DNMT1, DNMT2, DNMT3A, DNMT3B and DNMT3L. Canonical DNMTs that exhibit a functional enzymatic activity include DNMT1, which is considered to be the maintenance methyltransferase and DNMT3A/B that introduce de novo methylation. These enzymes are characterized by their Nterminal domain, involved in several regulatory functions, and the highly conserved C-terminal domain which is the catalytical domain [START_REF] Jurkowska | Structure and function of mammalian DNA methyltransferases[END_REF] (Figure 8).

It was shown that DNMT1 has a 24-fold preference for hemi-methylated sites, compared to unmethylated DNA [START_REF] Hermann | The Dnmt1 DNA-(cytosine-C5)-methyltransferase methylates DNA processively with high preference for hemimethylated target sites[END_REF]. This observation suggests the involvement of DNMT1 in the maintenance of methylation rather than in de novo methylation, although it was also shown that it can methylate DNA de novo. During cell replication, DNMT1 is responsible for the maintenance of methylation through the recognition of hemi-methylated CpG sites by UHRF1. DNMT1 localizes to the new synthetized DNA strand and is associated with the replication complex during S, G2 and M phases of the cell cycle [START_REF] Easwaran | Replication-independent chromatin loading of Dnmt1 during G2 and M phases[END_REF].

In mammals, the DNMT3 subfamily is composed of three members: DNMT3A, DNMT3B and DNMT3L. The two first possess an active methyltransferase activity, on the contrary to the last one. These DNMTs are involved in DNA methylation during development, in gametogenesis or in cancerogenesis, through their de novo methylation activity. DNMT3L acts 62 as a stimulator of DNMT3A/B's catalytic activity but does not have a catalytic domain by itself.

For example, it has been shown that the formation of DNMT3A-DNMT3L complex accelerates DNA binding of DNMT3A by 20 times [START_REF] Gowher | Mechanism of stimulation of catalytic activity of Dnmt3A and Dnmt3B DNA-(cytosine-C5)-methyltransferases by Dnmt3L[END_REF]. Knock out of DMT3L leads to meiotic failures, suggesting that DNM3L is essential during meiosis [START_REF] Bourc'his | Meiotic catastrophe and retrotransposon reactivation in male germ cells lacking Dnmt3L[END_REF]. Recently, a new DNMT3C was identified and this enzyme plays a role during development [START_REF] Barau | The DNA methyltransferase DNMT3C protects male germ cells from transposon activity[END_REF][START_REF] Jain | rahu is a mutant allele of Dnmt3c, encoding a DNA methyltransferase homolog required for meiosis and transposon repression in the mouse male germline[END_REF].

The last member of DNMT family, which was first identified in the yeast, is DNMT2. It does not possess any methyltransferase activity, and its involvement in DNA methylation is still unclear [START_REF] Jeltsch | Mechanism and biological role of Dnmt2 in Nucleic Acid Methylation[END_REF]. From [START_REF] Maresca | DNA methyltransferase 1 mutations and mitochondrial pathology: is mtDNA methylated? Front[END_REF].

Demethylation of DNA

Demethylation of the DNA can typically be divided into two types: the active and the passive (Figure 9). The latter consists of non-maintenance of the methylation following DNA replication, leading to a progressive dilution of the methylation after each round of cell division.

Thus, a decrease in DNMT1 expression or of its enzymatic activity can result in a global hypomethylation of DNA.

On the contrary, the active demethylation of DNA is not dependent on DNA replication nor the cell cycle. This process is based on the enzymatic activity of the TET (Ten-eleventranslocation) family members. These enzymes possess the ability to convert 5mC to 5hmC and other downstream derivatives (such as 5-formylcytosine and 5-carboxycytosine), which can then be eliminated through different ways. The subsequent suppression of modified cytosines is based either on the BER or NER pathways, or by passive demethylation.

Figure 9. Overview of DNA methylation and demethylation. From [START_REF] Bommarito | The Role of DNA Methylation in Gene Regulation[END_REF].

In the first case, oxidation of 5mC by TET proteins generates substrates for thymine DNA glycosylase (TDG)-dependent BER which can replace 5mC with Cytosine [START_REF] Weber | Biochemical reconstitution of TET1-TDG-BER-dependent active DNA demethylation reveals a highly coordinated mechanism[END_REF]. Moreover, AID/APOBEC deaminases can also deaminate directly the 5mC or the 5hmC resulting from the TET's activity, leading to a T/G or U/G mismatch, respectively. These mismatches can then be taken in charge by the BER system. In the second case, Gadd45a

(Growth Arrest and DNA Damage Inducible Alpha), which lacks enzymatic activity, interacts with the NER endonuclease XPG (Xeroderma pigmentosum group G complementing factor) [START_REF] Barreto | Gadd45a promotes epigenetic gene activation by repair-mediated DNA demethylation[END_REF], which excises the methylated nucleotide and replaces it by a cytosine, suggesting that the NER pathway could be implicated in active demethylation of DNA. Another active demethylation can occur via DNA demethylase activity of DNMTs. Indeed, it was shown in vitro that DNMT1 and DNMT3A/B can directly remove the methyl group from cytosines in the presence of Ca 2+ ion and under non-reducing condition [START_REF] Chen | DNA 5-Methylcytosine Demethylation Activities of the Mammalian DNA Methyltransferases[END_REF].

Role of DNA methylation in heterochromatin and cell identity

Heterochromatin is an inaccessible chromatin state characterized by highly compact chromatin structure which is enriched with DNA methylation as well as histone repressive marks such as H3K9me3, and heterochromatin protein HP1. Heterochromatin is responsible for repression of the transcription and stability of the chromatin. Histone methylation plays a role of "molecular anchor" to recruit proteins that directly modify chromatin or recruit co-factors that are in charge of this process. For example, H3K9me provides a binding site for the Wsi/HP1 chromodomain to recruit these factors to heterochromatic loci [START_REF] Grewal | Heterochromatin revisited[END_REF].

Swi6/HP1 has the ability to bind to numerous proteins that are implicated in heterochromatin formation, including histone deacetylases (HDAC).

The interpretation of the DNA methylation within the cell is complex. Today, at least two different mechanisms are retained: first is the recruitment of methyl-CpG-binding domain (MBD) proteins, which can recruit other factors implicated in the remodeling of the chromatin, such as HDACs or histone methylases, to the methylated CpGs. For example, MeCP2 (methyl-CpG binding protein 2) and MBD1 are known to be responsible for heterochromatin silencing through their interactions with repressive histone methylation and chromatin remodeling binding partner HP1. The second mode of action is based on the interference that DNA methylation creates with transcription factor binding. This is because changes in the structure of chromatin by DNA methylation limit the access of transcription factors to regulatory sequences.

Enrichment of H3K9me3 at pericentric region is highly correlated with DNA methylation level [START_REF] Cedar | Linking DNA methylation and histone modification: patterns and paradigms[END_REF]. It has been reported that DNA maintenance mediated by DNMT1 is regulated by UHRF1 (Ubiquitin-like with PHD and RING finger domains) [START_REF] Bostick | UHRF1 Plays a Role in Maintaining DNA Methylation in Mammalian Cells[END_REF][START_REF] Sharif | The SRA protein Np95 mediates epigenetic inheritance by recruiting Dnmt1 to methylated DNA[END_REF]. Recently, evidence showing direct link between H3K9me3 and DNMT1-mediated DNA methylation have been reported [START_REF] Ren | Direct readout of heterochromatic H3K9me3 regulates DNMT1-mediated maintenance DNA methylation[END_REF]. Therefore, it appears that the cross-talk between DNA methylation and repressive histone marks is fundamental in maintaining the heterochromatin state.

Role of the DNA methylation at gene regulatory elements

The development of next generation sequencing (NGS) methods in the last two decades also enabled to the study of DNA methylation at the genome-wide level. The sequencing of bisulfite-converted DNA, which allows the detection of 5mC and 5hmC, permitted to determine the cellular methylome profile [START_REF] Cokus | Shotgun bisulphite sequencing of the Arabidopsis genome reveals DNA methylation patterning[END_REF][START_REF] Lister | Human DNA methylomes at base resolution show widespread epigenomic differences[END_REF]. The increasing amount of available data helps to discover main features of genome organization such as the genome compartmentalization, and to reveal the mechanisms of gene expression regulation.

The following sections are dedicated to the description of the role of DNA methylation in these different regions, starting with regulatory elements.

Enhancers, as well as repressors, are defined as distal cis-acting genomic regions containing transcription factor binding sites, whose binding and co-factors' recruitment influence the expression of the target gene [START_REF] Shlyueva | Transcriptional enhancers: from properties to genome-wide predictions[END_REF]. These regions have a tendency to be globally depleted in CpG dinucleotides, and are not characterized by a specific methylation status, but rather display variable methylation levels [START_REF] Lister | Human DNA methylomes at base resolution show widespread epigenomic differences[END_REF]. Nevertheless, it was shown that active enhancers were associated with 5hmC [START_REF] Sérandour | Dynamic hydroxymethylation of deoxyribonucleic acid marks differentiation-associated enhancers[END_REF], suggesting the existence of a dynamic process of methylation/demethylation of the DNA, that could be potentially mediated by TET proteins [START_REF] Williams | TET1 and hydroxymethylcytosine in transcription and DNA methylation fidelity[END_REF]. In other words, at a given time some CpG sites are methylated and other are not. Results from an ENCODE study showed the existence of a negative correlation between transcription factor expression levels and 5mC content at these transcription factor binding sites [START_REF] Thurman | The accessible chromatin landscape of the human genome[END_REF]. This observation suggests that the deposition of 5mC could directly result from the absence of transcription factors binding. A schematic representation of DNA methylation at the gene's promoter is provided in Figure 10.

Insulators are genomic regions which block the interactions between an enhancer, or a silencer, and a promoter. Eukaryotic insulators possess the CCCTC sequence, on which binds the CCCTC binding factors (CTCF). It has been shown that CTCF binds unmethylated DNA, suggesting that methylation of insulators could inhibit their activity [START_REF] Bell | Methylation of a CTCF-dependent boundary controls imprinted expression of the Igf2 gene[END_REF][START_REF] Shukla | CTCF-promoted RNA polymerase II pausing links DNA methylation to splicing[END_REF]. For example, methylation of CTCF binding site within the imprinted IGF2-H19 locus, blocks the binding of CTCF [START_REF] Bell | Methylation of a CTCF-dependent boundary controls imprinted expression of the Igf2 gene[END_REF]. However, a more recent study conducted on murine ESCs has shown that binding of CTCF is not necessary influenced by methylation in CpG-poor regions [START_REF] Stadler | DNA-binding factors shape the mouse methylome at distal regulatory regions[END_REF]. Altogether these studies suggest that there is no general rule on the effects of DNA methylation at insulators. Changes in DNA methylation at insulator may not affect the gene transcription.

Figure 10. DNA methylation at promoters regulates transcription binding and subsequent transcription. From [START_REF] Bommarito | The Role of DNA Methylation in Gene Regulation[END_REF].

Role of the methylation within gene body

Gene bodies are genomic regions from promoters to the last exon. They are globally depleted in CpG dinucleotides compared to the whole-genome rate of CpGs and meanwhile highly methylated. Genes can be divided into coding sequences, referred as the exons, and non-coding, called introns. In intronic regions, hypomethylation can trigger the activation of a regulatory element through the unmasking of a binding site, leading to the activation of the target gene [START_REF] Blattler | Global loss of DNA methylation uncovers intronic enhancers in genes showing expression changes[END_REF][START_REF] Cheung | Methylation of an intronic region regulates miR-199a in testicular tumor malignancy[END_REF], or on the contrary inactivation of gene expression. In the exonic regions, methylation of CpG is a major cause of C to T transition, that could be responsible for tumoral transformation [START_REF] Rideout | 5-Methylcytosine as an endogenous mutagen in the human LDL receptor and p53 genes[END_REF]. In general, methylation in gene body is associated with gene expression activation. For example, it has been observed that there is a positive correlation between transcription from the active X chromosome and its gene body methylation [START_REF] Hellman | Gene Body-Specific Methylation on the Active X Chromosome[END_REF]. This first observation was then confirmed at the genome-wide level using an approach combining MethylC-seq and strand-specific RNA-seq analysis [START_REF] Lister | Human DNA methylomes at base resolution show widespread epigenomic differences[END_REF].

When the methylation occurs in the first exon, the expression of the gene is generally repressed [START_REF] Brenet | DNA Methylation of the First Exon Is Tightly Linked to Transcriptional Silencing[END_REF]. However, the methylation at first exon can also trigger other mechanisms such as the expression of an alternative transcript leading to appearance of noncanonical isoform of a protein. This has been shown, for example, with Bax (BCL2-associated X protein) in the context of glioblastoma multiforme [START_REF] Cartron | The expression of a new variant of the pro-apoptotic molecule Bax, Baxψ, is correlated with an increased survival of glioblastoma multiforme patients[END_REF]. This phenomenon 67 finds an explanation in the fact that genes often have several TSS, making it possible to generates different isoforms.

Even if the methylation within gene body does not seem to play important role in the regulation of the expression, its function is still essential. The body of the genes also contains repetitive elements, such as retroviruses, LINEs, SINEs or Alu repeats. Therefore, the maintenance of DNA methylation within gene body is required to silence these elements, while the host gene can still be transcribed. Another hypothesis to explain this global hypermethylation, is the presence of H3K36me3 in gene bodies [START_REF] Baubec | Genomic profiling of DNA methyltransferases reveals a role for DNMT3B in genic methylation[END_REF][START_REF] Morselli | In vivo targeting of de novo DNA methylation by histone modifications in yeast and mouse. ELife 4, e06205[END_REF]. This histone mark is involved in the elongation of the transcript but not in the initiation of the transcription. Deposition of H3K36me3 could then be involved in the recruitment of DNMTs, resulting in DNA methylation. The methylation level is more elevated within exons compared to the introns, and this rupture in methylation levels was observed to occur at the exon/intron junctions. Indeed, there exists a very distinctive pattern of methylation across exon-intron boundaries, displaying a spike of methylation at the 3' extremity of the exon, followed by an immediate decrease at the beginning of the next intron [START_REF] Laurent | Dynamic changes in the human methylome during differentiation[END_REF]. This observation suggests that methylation within gene body could be implicated in splicing process.

B. DNA methylation dynamics during development

DNA methylation pattern is globally affected at two specific stages of the development.

These two waves, called "epigenetic reprogramming" occur in early embryo, just after the fertilization, and during germline development. During both reprogramming, a limited number of loci do not loss methylation mark and at the same time, de novo methylation can occur at certain regions, specific for cell type lineage.

First wave -Post-fertilization

Right after the fertilization, the embryo loses the gamete-specific DNA methylation patterns during the first wave of epigenetic reprogramming. Indeed, the genome has to progress from highly specialized cell identities (oocyte and spermatozoa) toward pluripotent state. In maternal and paternal genomes, this process does not occur the same way. In the most recent accepted model, the paternal genome in the mouse zygote is demethylated in an active way that involved the Tet Methylcytosine Dioxygenase 3 (TET3) which converts 5mC to 5hmC, and other downstream derivatives [START_REF] Gu | The role of Tet3 DNA dioxygenase in epigenetic reprogramming by oocytes[END_REF], which can then be replaced by unmethylated cytosines or diluted passively during cell replication. A similar process was also observed in humans, while it presents certain difference compared to the murine process. An initial fast demethylation occurs in human in a longer time (up to the two-cell stage), then a gradual demethylation occurs through the genome until the blastocyst stage [START_REF] Zhu | Single-cell DNA methylome sequencing of human preimplantation embryos[END_REF]. Following this, TET3-mediated active demethylation of the paternal genome takes place where the two parental genomes undergo a passive demethylation. DNMT1, which is in charge of methylation maintenance through cell division, is restricted to the cytoplasm [START_REF] Howell | Genomic Imprinting Disrupted by a Maternal Effect Mutation in the Dnmt1 Gene[END_REF]. DNA methylation is therefore diluted at each cycle in the absence of DNMT1.

A recent single-cell whole-genome bisulfite sequencing analysis revealed that de novo methylation also occurs in the human embryonic genome. Indeed, an increase of DNA methylation was observed at the one-and eight-cell stages (from the early to mid-pronuclear stage and from the four-cell to eight-cell stage). Genomic regions that presente de novo methylation were enriched in Alu repeats [START_REF] Zhu | Single-cell DNA methylome sequencing of human preimplantation embryos[END_REF]. Following implantation, the genome of the embryo is remethylated. This gain of methylation mark corresponds to the loss of cellular pluripotency.

After fertilization, transcripts with maternal origin are progressively degraded and zygote genome starts to be transcribed. This phenomenon called zygote genome activation (ZGA) is subdivided into two phases, minor and major ZGA (Figure 11). Minor ZGA occurs during the 1-cell stage (zygote) in mouse embryo [START_REF] Latham | Acquisition of a transcriptionally permissive state during the 1cell stage of mouse embryogenesis[END_REF] and is characterized by a very low level of transcription. It is thought that the minor ZGA is triggered by paternal H3K4me3 and H4ac, which make the paternal pronucleus permissive for active transcription [START_REF] Adenot | Differential H4 acetylation of paternal and maternal chromatin precedes DNA replication and differential transcriptional activity in pronuclei of 1-cell mouse embryos[END_REF][START_REF] Zhang | Allelic reprogramming of the histone modification H3K4me3 in early mammalian development[END_REF]. At the 2-cell stage, occurs the major ZGA which marks the switch from maternal genome control to zygote genome control. The later starts to be highly expressed to reach a stable transcriptional level. ZGA is fundamental for proper embryo development and failure of this process avoid further development. ERV-derived sequences create alternative promoters during ZGA. LTR elements provide the promoter at the 5' end of ERVs and transcriptional termination and polyadenylation signals at their 3' end [START_REF] Fu | Endogenous Retroviruses Function as Gene Expression Regulatory Elements During Mammalian Pre-implantation Embryo Development[END_REF]. It has been reported that ZGA-associated genes (Gata4, Tead4, Zscan4) are located in the vicinity of LTR elements [START_REF] Macfarlan | Embryonic stem cell potency fluctuates with endogenous retrovirus activity[END_REF]. Retrotransposons also contribute to set up the chromatin structure of higher-order, by providing chromatin organizer binding sites. It has been reported that ERVs are enriched for CTCF [START_REF] Ito | Systematic identification and characterization of regulatory elements derived from human endogenous retroviruses[END_REF], which participates in the three-dimensional structuration of the chromatin via chromatin loop formation and long-range connection between enhancers and promoters [START_REF] Satou | The retrovirus HTLV-1 inserts an ectopic CTCF-binding site into the human genome[END_REF].

The precise mechanisms by which these sequences are activated to function as transcriptional regulators and how they are controlled to avoid anarchical expression during the epigenetic reprogramming window are still not clearly understood. However, it is thought that their transcription is finely tuned by multilayer systems to ensure an accurate control of their expression [START_REF] Fu | Endogenous Retroviruses Function as Gene Expression Regulatory Elements During Mammalian Pre-implantation Embryo Development[END_REF]. For example, while genome is globally demethylated, H3K9me3

repressive mark is introduced to avoid retrotransposons to escape from transcriptional repression [START_REF] Wang | Reprogramming of H3K9me3-dependent heterochromatin during mammalian embryo development[END_REF]. Other mechanisms including transcriptional factor inactivation or other histone modifications have been reported. For example, lysine demethylase-mediated mechanism has been described (e.g., KDM1A), suggesting that the cross-talk between several histone marks (H3K4 and H3K9 methylation and H3K27ac) is involved in the control of certain retrotransposons [START_REF] Macfarlan | Endogenous retroviruses and neighboring genes are coordinately repressed by LSD1/KDM1A[END_REF].

2. Function of PIWI-interacting RNAs in silencing of transposable elements.

piRNAs are small single-stranded RNAs of 21-30 nucleotides, that associate with PIWI (P-element induced Wimpy testis) proteins, to identify RNA targets through base-pairing interactions. Key factors involved in this function are PIWI proteins, such as Aub (Aubergine) and Ago3 (Argonaute 3). They act as silencers via RNA degradation, inhibition of translation or recruitment of chromatin modifiers [START_REF] Czech | piRNA-Guided Genome Defense: From Biogenesis to Silencing[END_REF]. PIWI proteins and piRNAs play an important role in the silencing of transposable elements, even if they are also implicated in the regulation of gene expression during the development [START_REF] Rouget | Maternal mRNA deadenylation and decay by the piRNA pathway in the early Drosophila embryo[END_REF]. Loading piRNAs into Piwi proteins requires Hsp90 (Heat shock protein 90), and the loss of Hsp90 deregulates transposon silencing [START_REF] Ichiyanagi | HSP90α plays an important role in piRNA biogenesis and retrotransposon repression in mouse[END_REF][START_REF] Kajiwara | Spermatogenesis arrest caused by conditional deletion of Hsp90α in adult mice[END_REF].

piRNAs are derived from piRNA clusters/loci sequences in the pericentric or subtelomeric regions of the genome that are rich in transposable elements [START_REF] Klattenhoff | The Drosophila HP1 Homolog Rhino Is Required for Transposon Silencing and piRNA Production by Dual-Strand Clusters[END_REF].

Reduction of piRNA pathway leads to sterility in Drosophila melanogaster due to the activation of retroelements in the germline [START_REF] Shpiz | Mechanism of the piRNA-mediated silencing of Drosophila telomeric retrotransposons[END_REF]. Silencing of transposable elements by piRNAs relies on a "ping-pong" signature. Each anti-sense piRNA has a complementary sense partner that overlaps its sequence on 10 nucleotides. These sequences are generated by the cleavage of both sense and anti-sense piRNA precursors by PIWI proteins.

Precursors of piRNAs are exported from the nucleus and are cleaved by Ago3, close to their 5' extremity. Short fragment of precursor transcript is loaded onto Aub, while remaining

Second wave -Germline development

In mammals, the second wave of reprogramming initiates in primordial germ cells (PGCs). In mouse, around 40 PGCs appear as a cluster at E7.25 at the base of the incipient allantois [START_REF] Chiquoine | The identification, origin, and migration of the primordial germ cells in the mouse embryo[END_REF][START_REF] Lawson | Clonal analysis of the origin of primordial germ cells in the mouse[END_REF]. Then, PGCs migrate through hindgut to the genital ridge. During migration, and at the genital ridge, PGCs undergo a series of coordinated epigenetic reprogramming, including a genome-wide loss of 5mC, in order to become gonocytes or oocytes (Figure 12). Indeed, since PGCs are specified from cells intended to be somatic, nascent PGCs must both repress the ongoing somatic program and activate the germ cell transcription network. Thus, just as the post-fertilization wave, this process involves both active and passive mechanisms of demethylation (as well as X-chromosome reactivation and chromatin reorganization). Shortly after PGCs specification, PR/SET Domain 1 (PRDM1) and PR/SET Domain 14 (PRDM14) repress the expression of DNMT3A (DNA (cytosine-5-)-methyltransferase 3 Alpha), DNMT3B (DNA (cytosine-5-)-methyltransferase 3 Beta) and UHRF1 [START_REF] Magnúsdóttir | A tripartite transcription factor network regulates primordial germ cell specification in mice[END_REF], that binds to hemi-methylated DNA and allows the recruitment of DNMT1 during cell division via its ubiquitin ligase activity. Maintenance and de novo methylation are therefore repressed, leading to a passive demethylation when PGCs proliferate [START_REF] Kagiwada | Replication-coupled passive DNA demethylation for the erasure of genome imprints in mice[END_REF]. This first phase is followed by a TET1-and TET2-dependent demethylation, mostly affecting imprinting loci [START_REF] Hackett | Germline DNA demethylation dynamics and imprint erasure through 5-hydroxymethylcytosine[END_REF][START_REF] Yamaguchi | Role of Tet1 in genomic imprinting erasure[END_REF]) and germline specific genes [START_REF] Yamaguchi | Tet1 controls meiosis by regulating meiotic gene expression[END_REF].

Long-term silencing: Genomic imprinting and XCI

It is in 1961 that Mary Lyon discovers the X-chromosome inactivation (XCI), while observing the different coat color of mice, displaying Mottled and Tabby phenotypes [START_REF] Lyon | Gene Action in the X -chromosome of the Mouse ( Mus musculus L.)[END_REF].

From the observations of Susumu Ohno and Murray Barr, Mary Lyon proposed that one of the X chromosome of mammal females is transcriptionally inactive.

Why this phenomenon occurs? Males and females display a major difference at sex chromosomes. Females have two copies of X chromosome while males have one copy of both X and Y chromosomes. Y chromosome is much shorter and poorer in gene content compared to the X chromosome (~70 vs ~840 genes). Moreover, both chromosomes do not share much genes together.

XCI is an essential phenomenon, if it does not occur during early development, the embryo dies rapidly. This can explain why really few mutants survive until late stage, making it difficult to study this process. It is now thought that the phenomenon is probably not essential for all the X chromosome genes, and it does not necessary occur in all tissues during the whole life of an organism. However, this remains an open question.

In numerous cases, XCI is a non-random process, explaining why females display less severe phenotypes than males in the X chromosome-related diseases. In some cases, the paternal X will always be inactivated, while in others it is the maternal one. For example, it is manifested as mosaicism in skin color, as it is the case with typical Agouti phenotype example.

Some genes are not subjected to XCI, leading to their expression from the inactivated X [START_REF] Shapiro | Non-inactivation of an x-chromosome locus in man[END_REF]. It involves, for example, the pseudo-autosomal regions (PARs), i.e., homologous sequences on X and Y chromosomes. These regions being present in two copies in both males and females, does not need dose compensation. It has been suggested that about 25% of the genes carried by the X chromosome could escape inactivation [START_REF] Carrel | X-inactivation profile reveals extensive variability in X-linked gene expression in females[END_REF].

The XCI is a perfect example of an epigenetic phenomenon, mono-allelic expression and heterochromatin establishment. How two identical chromosomes, in the same nucleus, in the same nucleoplasm, confronted to the same transcription factors and regulators, could be treated in different ways?

In the 1980's, Gartler and Riggs described a two phase process: an initiation during which the process is established, and a maintenance or propagation phase, to maintain this inactivated state [START_REF] Gartler | Mammalian X-Chromosome Inactivation[END_REF]. Several hypotheses were then proposed. For example, it was hypothesized that the gain or the loss of genetic regions, could be involved.

Nowadays, with cloning and induced reprogramming experiment, we know that this hypothesis is not confirmed. Another hypothesis suggested that one of X chromosome was attached to the nuclear membrane triggering a different processing, or that a non-histone protein could allow to differentiate the two chromosomes. At this time, it was thought that histones occupy the full length of the chromosomes, and therefore could not be a way to distinguish the two X chromosomes. Today we know that histone variants and histone modifications, allow to distinguish between the two alleles. Besides that, the in-situ hybridization using probe for X chromosome showed that inactivated chromosome appears as Barr body. The formation of the Barr body within the nucleus was the first description of facultative heterochromatin representing a transcriptionally repressive environment.

Relatively early, it was observed that CGIs located in the gene's 5' region of inactive X chromosome were often methylated [START_REF] Riggs | X inactivation, differentiation, and DNA methylation[END_REF], whereas other cytosines (on active X chromosome or any other chromosomes) are globally hypomethylated, leading to the hypothesis that DNA methylation could be involved in XCI. Shortly after, several studies showed that DNA methylation is implicated in XCI. In particular, several studies performed on methylation of Hprt (hypoxanthine guanine phosphoribosyl transferase) involving methylation-sensitive restriction enzymes, showed that Hprt locus was methylated on the inactive X chromosome [START_REF] Wolf | Methylation of the hypoxanthine phosphoribosyltransferase locus on the human X chromosome: implications for X-chromosome inactivation[END_REF][START_REF] Yen | Differential methylation of hypoxanthine phosphoribosyltransferase genes on active and inactive human X chromosomes[END_REF]. These observations were confirmed more recently using high-throughput methods: CGIs located on the inactive X chromosome are methylated, with the exception of those located in the vicinity of genes escaping from XCI [START_REF] Cotton | Chromosome-wide DNA methylation analysis predicts human tissue-specific X inactivation[END_REF].

From this relatively long period, focused on the study of the methylation of the inactive X chromosome, it was clear that DNA methylation was involved in the maintenance of this inactivation (through treatment with 5-azacytidine, or more recently deletion of DNMT1 experiments). However, the exact mechanism was not understood. The starting point for this was a study led in marsupials. As mammals, they are also subjected to XCI. However, they do not possess methylation at CGIs on the inactive X, at least not in the same extent as rodents or humans [START_REF] Kaslow | DNA methylation stabilizes X chromosome inactivation in eutherians but not in marsupials: evidence for multistep maintenance of mammalian X dosage compensation[END_REF], even if a slightly higher reactivation of their gene expression was observed. At this time, it became clear that DNA methylation alone could not accomplish XCI. A study that tracked the methylation during mouse development showed that methylation, at least at the Hprt locus (~E9.5), happens later than XCI (E6.5) [START_REF] Lock | Methylation of the Hprt gene on the inactive X occurs after chromosome inactivation[END_REF].

Advances in molecular biology, and in particular the development of antibodies able to detect post-translational modifications of the histones, have been used for the study of XCI.

As early as 1993, Bryan Turner et al. studied the acetylation of histone H4 (H4ac) on mitotic chromosomes by Hoescht / anti-H4ac co-staining [START_REF] Jeppesen | The inactive X chromosome in female mammals is distinguished by a lack of histone H4 acetylation, a cytogenetic marker for gene expression[END_REF]. In this study, they observed that all the chromosomes are well visualized by immunostaining against H4Ac,

C. DNA methylation in cancers

Change of methylation status, either hypo-or hypermethylation, is the most common epigenetic alteration in cancers. These changes affect mainly enhancers, Polycomb-repressed regions and heterochromatin [START_REF] Berman | Regions of focal DNA hypermethylation and long-range hypomethylation in colorectal cancer coincide with nuclear lamina-associated domains[END_REF][START_REF] Hansen | Increased methylation variation in epigenetic domains across cancer types[END_REF][START_REF] Lister | Human DNA methylomes at base resolution show widespread epigenomic differences[END_REF].

Major variations are hypermethylation of CGIs and global hypomethylation.

It is thought that the hypermethylation of some key genes happens in early carcinogenesis, leading to the inactivation of the transcription. These key genes are involved in several cellular functions, such as DNA repair (GSTP1), hormonal pathways (RARβ2) or proliferation (RASSD1A). In the absence of DNA repair activity, DNA damage can accumulate and be improperly repaired triggering mutation appearance and genomic instability. It has been shown

that the modification of DNMT expression (overexpression or down-regulation) modulates the appearance of tumors in vivo in mice [START_REF] Linhart | Dnmt3b promotes tumorigenesis in vivo by gene-specific de novo methylation and transcriptional silencing[END_REF].

Localized hypermethylation

The hypermethylation of tumor suppressor genes is a driving phenomenon in tumorigenesis [START_REF] Jin | DNA Methyltransferases (DNMTs), DNA Damage Repair, and Cancer[END_REF]. These anomalies are detected in tumors as well as in precancerous lesions, suggesting that this is an early event within the cascade leading to tumoral transformation [START_REF] Belinsky | Gene-promoter hypermethylation as a biomarker in lung cancer[END_REF]. This hypermethylation is tumor-specific as it was not detected in normal cells surrounding the tumor.

Several studies have shown that methylation frequency and targeted genes are dependent on the cancer type. Nonetheless, epigenetic status of some DNA repair genes has been found to be altered in different types of cancer; reviewed in [START_REF] Jin | DNA Methyltransferases (DNMTs), DNA Damage Repair, and Cancer[END_REF].

For example, the promoter of MLH1 has been found to be hypermethylated in HNPCC, AML, oral squamous cell carcinoma (OSCC), ovarian and gastric cancers, among others (Table 3).

Polycomb-repressed regions are highly likely to become hypermethylated in cancer, possibly through the recruitment of DNMTs to these regions by enhancer of zeste homolog 2 (EZH2) [START_REF] Viré | The Polycomb group protein EZH2 directly controls DNA methylation[END_REF], a member of the polycomb repressor complex 2 (PRC2). DNA methylation at these regions seems not to affect gene expression, but affects already silenced genes. However, it may block the capability of a cell to reactivate genes, which may be essential for malignant transformation.

Table 3. Genes in DNA damage repair pathways that are hypermethylated in cancers. From [START_REF] Jin | DNA Methyltransferases (DNMTs), DNA Damage Repair, and Cancer[END_REF].

Global hypomethylation

In contrast to promoter of DNA repair genes and polycomb-repressed regions, heterochromatin, which shows a strong overlap with late-replicating regions and association with nuclear lamina, is particularly prone to losing DNA methylation during malignant transformation [START_REF] Hon | Global DNA hypomethylation coupled to repressive chromatin domain formation and gene silencing in breast cancer[END_REF][START_REF] Lister | Human DNA methylomes at base resolution show widespread epigenomic differences[END_REF].

In mice, it was shown that induction of hypomethylation leads to aggressive T cell lymphomas [START_REF] Gaudet | Induction of tumors in mice by genomic hypomethylation[END_REF]. More generally, it is a well-accepted fact that global hypomethylation of the genome is a hallmark of the cancer [START_REF] Feinberg | Hypomethylation distinguishes genes of some human cancers from their normal counterparts[END_REF][START_REF] Narayan | Hypomethylation of pericentromeric DNA in breast adenocarcinomas[END_REF]. This global hypomethylation of the genome in cancer could affect the genome stability and could trigger recombination events, potentially via the activation of dangerous repetitive elements [START_REF] Rauch | Highresolution mapping of DNA hypermethylation and hypomethylation in lung cancer[END_REF]. For example, hypomethylation of LINEs L1

was reported in several types of cancer, such as lymphocytic leukemia [START_REF] Dante | Methylation patterns of long interspersed repeated DNA and alphoid repetitive DNA from human cell lines and tumors[END_REF], urinary bladder [START_REF] Jürgens | Hypomethylation of L1 LINE sequences prevailing in human urothelial carcinoma[END_REF], hepatocellular [START_REF] Takai | Hypomethylation of LINE1 retrotransposon in human hepatocellular carcinomas, but not in surrounding liver cirrhosis[END_REF] or prostate [START_REF] Santourlidis | High frequency of alterations in DNA methylation in adenocarcinoma of the prostate[END_REF] carcinomas. Loss of genomic imprinting can also lead to the overexpression of oncogenes and participate in oncogenesis [START_REF] Rainier | Relaxation of imprinted genes in human cancer[END_REF].

Alteration of DNA methylation effectors

Alterations in DNA methylation can result from several mutations affecting epigenetic effectors. It has been shown that mutations within DNMT3A, mostly in the C-terminal catalytic domain (e.g., R882C, R882S, R882H) could lead to a loss-of-function in AML. It has been reported that mutations in DNMT3A led to hypomethylation of the HOXB cluster genes [START_REF] Yan | Exome sequencing identifies somatic mutations of DNA methyltransferase gene DNMT3A in acute monocytic leukemia[END_REF]. Certain mutations of DNMT3A also lead to gain-of-function. For example, it has been shown that R882S DNMT3A mutant interacts with Polycomb repressive complex 1 (PRC1), while the wild-type DNTM3A does not [START_REF] Koya | DNMT3A R882 mutants interact with polycomb proteins to block haematopoietic stem and leukaemic cell differentiation[END_REF]. Other effectors, such as enzymes involved in demethylation, can also be mutated. For example, genes encoding for isocitrate dehydrogenases (IDH1/2) were found to be mutated in glioblastoma and AML. Mutations that affect the arginine residue (R132/R172) lead to a gain-of-function, allowing the conversion of α-ketoglutarate to (D)-2-hydroxyglutarate, which inhibits α-ketoglutarate-dependent enzymes, such as TET proteins [START_REF] Ward | The common feature of leukemia-associated IDH1 and IDH2 mutations is a neomorphic enzymatic activity that converts α-ketoglutarate to 2-hydroxyglutarate[END_REF]. The reduced activity of TET enzymes leads, therefore, to an accumulation of 5mC. TET enzymes have also been reported to be mutated in blood cancers [START_REF] Abdel-Wahab | Genetic characterization of TET1, TET2, and TET3 alterations in myeloid malignancies[END_REF][START_REF] Jankowska | Loss of heterozygosity 4q24 and TET2 mutations associated with myelodysplastic/myeloproliferative neoplasms[END_REF], as well as certain solid tumors such as liver or lung cancers.

Ultimately, the cross-talk between histone mark effectors and DNA methylation enzymes can lead to alteration of DNA methylation in certain cases. For example, it is known that H3K27me3 is a pre-mark for methylation-susceptible genes in normal cells [START_REF] Mccabe | A multifactorial signature of DNA sequence and polycomb binding predicts aberrant CpG island methylation[END_REF][START_REF] Schlesinger | Polycomb-mediated methylation on Lys27 of histone H3 pre-marks genes for de novo methylation in cancer[END_REF]. Therefore, alteration of H3K27me3 can trigger modification of subsequent DNA methylation status. A mutation that induces EZH2 histone methyltransferase activity was identified in lymphoma at a tyrosine residue (Y641H, Y641N, Y641S), resulting in cellular alteration of H3K27me3 [START_REF] Morin | Somatic mutations altering EZH2 (Tyr641) in follicular and diffuse large B-cell lymphomas of germinal-center origin[END_REF]. Moreover, inactivating mutations were identified in KDM6A in AML, colorectal cancers and esophageal squamous cell carcinomas (ESCCs) [START_REF] Van Haaften | Somatic mutations of the histone H3K27 demethylase, UTX, in human cancer[END_REF]. Other mutations within chromatin remodeling factors, such as SWI/SNF, can also be involved in DNA methylation modification. Consequently, genomic

78

DNA is not protected from DNMTs de novo methylation as these mutations lead to alteration of nucleosome occupancy.

There are several hypotheses that were formulated to understand from where, and from which mechanisms, these changes in DNA methylation are originated. Do they result from random events or are rather directed by oncogenes? One study suggests that the oncogene Ras could induce the methylation of its target genes via the recruitment of several epigenetic silencing effectors, including DNMT1 [START_REF] Gazin | An elaborate pathway required for Ras-mediated epigenetic silencing[END_REF].

Another very promising line of research is possible influence of the environment on methylation profiles. For example, a recent study shows that exposure to low doses of pollutants (BPA) during development can induce epigenetic abnormalities linked to an increase in the frequency of certain cancers, such as prostate cancer, in mice [START_REF] Ho | Developmental exposure to estradiol and bisphenol A increases susceptibility to prostate carcinogenesis and epigenetically regulates phosphodiesterase type 4 variant 4[END_REF]. The influence of the environment on the epigenetic landscape is the subject of one of the following sections and therefore will be discussed in details hereafter.

D. International epigenome studies

Several scientific consortia characterized the epigenome of normal and pathological cells. The two most important are the ENCODE (Encyclopedia of DNA Elements) and IHEC (International Human Epigenome Consortium) projects.

The ENCODE project, which started in 2004, aimed to identify all the functional elements of the human genome. This includes the elements acting at the protein and RNA levels as well as the regulatory elements that control cells and the circumstances in which a gene is active. In order to achieve this objective, the investigators involved in the ENCODE project have resorted to various methods. These studies are mainly based on high-throughput sequencing methods coupled with many molecular biology techniques. Regulatory elements are generally studied by DNA hypersensitivity assays, methylation assays and immunoprecipitation assays of proteins interacting with DNA or RNA, such as modified histones, transcription factors, chromatin regulators or RNA binding proteins.

An overview of the main results from this international cooperation was provided in 2012 in Nature (The ENCODE Project Consortium, 2012). The conclusions of this work suggest that 80% of the genome participates in at least one function associated with the biochemistry of RNAs or with a chromatid event in at least one cell type among the 147 studied. It has also been reported that 95% of the genome is within 8kb in the vicinity of essential DNA-protein interactions (data from ChIP-seq or DNase-seq). Analysis of the datasets established the existence of seven major chromatin states (which can then be further subdivided into thousands of narrow states with distinct functional properties). These states are shown in the table on the next page (Table 4).

Following their publication, these results were strongly criticized [START_REF] Doolittle | Is junk DNA bunk? A critique of ENCODE[END_REF][START_REF] Graur | On the immortality of television sets: "function" in the human genome according to the evolution-free gospel of ENCODE[END_REF], by questioning the definition of a regulatory element, in particular through the distinction between the "selected effects" and the "causal role" of an entity or a process. However, whatever be the meaning behind the term "regulatory element", the ENCODE project has made it possible to annotate a large part of the genome, for example by identifying around 400,000 regions with enhancers-like features and just over 70,000 regions with promoter-like features (The ENCODE Project Consortium, 2012). The data of the ENCODE project are listed in a database freely accessible online at https://www.genome.ucsc.edu/ENCODE/.

The international IHEC consortium, launched in 2010, aimed to map 1,000 epigenomes of references, like the 1,000 Genomes project. The first phase of the project involved the production of at least 1,000 epigenomes from healthy and diseased human cells, as well as some from model organisms, such as the mouse, relevant to specific human diseases. Emphasis is

III. Description of analyzed tissues

The testis and the ovary have similar functions: they produce the cells of the germ line, the gametes, as well as in these organs the synthesis of sexual hormones takes place. The cell populations found in the testis and the ovary are quite distinct. However, there are functional analogies between cell populations of male and female gonads. The work done during my PhD focused on the effects of in utero exposure to CD on the reproductive organs of mice of both sexes. The aim of this chapter is therefore to present the mechanisms of differentiation in reproductive organs during development as well as the functions of these organs in adults.

The acquisition of human tissue through biopsy is an invasive act. Therefore, it is not easy to obtain human biological material, and even less for large quantities of materials. This is why the use of blood may be a good alternative for studying the effects of certain environmental compounds on humans. Indeed, acquisition of blood is relatively noninvasive compared to sample from other tissues. However, blood has limitations for use as a biological model, e.g. low expression of RNA, less complexity in cell types, blood does not replace as model of complex organs such a liver, testis or brain. Thus, using the model organisms such mouse is essential to discover the effects of toxicants in vivo in the context of an entire complex organism. That's why during my PhD I used largely mouse as a model organism. Thus, I will present the gametogenesis mainly in mouse, as most of knowledge of developmental biology of reproductive organs was done in mouse. Moreover, during my PhD, a large number of experiments were performed using this model. At the same time, in the second part of my thesis, we worked on samples of umbilical cord blood from a mother-child cohort (TIMOUN). This cohort was created in Guadeloupe in order to understand the effects of prenatal exposure to CD on pregnancy on child development. The last subsection of the current chapter will therefore be dedicated to the presentation of the circulatory system.

In animals that use sexual mechanisms for their reproduction, germ cells are the only cells that have the ability to be transmitted to the next generation to give rise to a new organism.

Therefore, understanding how they establish themselves and evolve is crucial for studying the mechanisms of transgenerational effects. In animals, the germ cells originate and specify during early embryonic development. The first part of this chapter will be dedicated to the description of specification and development of the PGCs in the embryo and then, I will describe the process of the differentiation into male or female gonads. In the second part, the physiological functions of the reproductive system in adult life will be described. Finally, the common and distinct features of gametogenesis will be described in both females and males.

A. Embryonic development of the gonads

Bipotential gonad development and germ cell specification

The fetal gonads develop from the coelomic epithelium (mesothelium) that lines the posterior abdominal wall, the underlying mesenchyme (intermediate mesoderm), and the PGCs. The genital ridge, the precursor of the gonads, is composed of somatic cell lineages and germ cells. However, these two lineages are formed at different developmental stages and positions in the embryo.

a. Development of embryonic gonad

Embryonic gonads have a unique capacity to become two morphologically distinct organs, testes or ovaries. Therefore, they are called bipotential. The fate of embryonic gonad relies on the sex chromosomes and particularly on the presence or absence of the sex-determining gene of the Y chromosome (SRY).

The coelomic epithelial cells that are destined to form the gonad become positive for the transcription factor WT1 (Wilm's tumor 1). It has been shown that in absence of WT1, the thickening of the coelomic epithelium is reduced dramatically [START_REF] Kreidberg | WT-1 is required for early kidney development[END_REF]. In the absence of another transcription factor, GATA4 (GATA binding protein 4), the anterior to posterior enlargement of the coelomic epithelium cannot occur, leading to failure of subsequent gonad development [START_REF] Hu | Gata4 is required for formation of the genital ridge in mice[END_REF]. A third actor plays an indispensable role in the development of the gonad is SF1 (steroidogenic factor 1, also known as Nr5a1). The expression of this orphan nuclear receptor is promoted by GATA4 and two homeodomain proteins, SIX1 and SIX4 (sine oculis homeobox homologs 1 and 4) [START_REF] Fujimoto | Homeoproteins Six1 and Six4 Regulate Male Sex Determination and Mouse Gonadal Development[END_REF], and occurs in the precursor of gonadal somatic cells. This process of coelomic epithelium thickening takes places between E9.5 and E10.5 in mice and during the fourth week of the development in humans (Figure 13).

Following its expansion, the underlying basement membrane starts to disrupt, allowing the coelomic epithelium cells to internalize into the dorsal inner mesenchyme region to form the nascent gonad. This process involves multiple factors and pathways, such as the homeodomain transcription factor EMX2 (empty spiracles homeobox 2), whose absence leads to the accumulation of the coelomic epithelial cells on surface of the future gonad [START_REF] Kusaka | Abnormal epithelial cell polarity and ectopic epidermal growth factor receptor (EGFR) expression induced in Emx2 KO embryonic gonads[END_REF].

Figure 13. Development of the genital ridge from the coelomic epithelium. From [START_REF] Rotgers | Formation of the Testis Primordium[END_REF].

Then, LHX9 (Lim homeobox 9) and insulin signaling IGF1R (insulin receptor and IGF type I receptor) promotes the cellular proliferation in order to give rise to the progenitors in the developing gonad, which occurs at E10.5 to E11.5 in mice (during the fifth week of development in humans). Following the ingression, certain cells keep proliferating as progenitor cells, while some others acquire mesenchymal characteristics by losing their polarity and cell-cell connections. The latter group of cells form a cluster which are destined to become the future somatic cells within the gonad. This asymmetric division is strongly regulated via the Notch signaling pathway.

Among the somatic cells, the supporting cells play the most critical role in sex determination in the undifferentiated gonad. Indeed, this is the first population to differentiate into cell types that are specific to the sex of the embryo. In males, supporting cells differentiate into Sertoli cells, through the action of SRY gene, while in females they differentiate into granulosa cells. A second kind of somatic precursors is also found in the fetal gonad: steroidogenic progenitors that produce Leydig cells in the testis or theca cells in the ovary. For a comprehensive review on the genital ridge formation, see [START_REF] Tanaka | Regulation of male sex determination: genital ridge formation and Sry activation in mice[END_REF] b. Specification of the PGCs

In the pre-gastrulation mouse, at E6.25, a subset of six to eight epiblast cells start to express a transcriptional activator, Prdm1 (PR domain zinc finger protein 1), also known as Blimp1 [START_REF] Ohinata | Blimp1 is a critical determinant of the germ cell lineage in mice[END_REF]. Blimp1, together with Prdm14 and Ap2 (encoded by Tfap2c gene), are part of a tripartite transcription factor network that induce the PGC program [START_REF] Nakaki | Induction of mouse germ-cell fate by transcription factors in vitro[END_REF]. It has been shown that Prdm14 enhances the reprogramming of epiblast stem cells to naive pluripotent state, suggesting that it could contribute to epigenetic reprogramming in PGCs [START_REF] Gillich | Epiblast stem cell-based system reveals reprogramming synergy of germline factors[END_REF].

PGCs can be detected in the proximal epiblast, just before the beginning of gastrulation. PGCs are also specified by BMP (Bone morphogenic proteins), they include the family of proteins, BMP2, BMP4 and BMP8B, which are expressed in the surrounding extra-embryonic tissues [START_REF] Lawson | Bmp4 is required for the generation of primordial germ cells in the mouse embryo[END_REF][START_REF] Ying | Cooperation of endoderm-derived BMP2 and extraembryonic ectoderm-derived BMP4 in primordial germ cell generation in the mouse[END_REF][START_REF] Ying | Requirement of Bmp8b for the generation of primordial germ cells in the mouse[END_REF]. Indeed, it has been shown that mice lacking BMP4 do not produce PGCs [START_REF] Lawson | Bmp4 is required for the generation of primordial germ cells in the mouse embryo[END_REF]. Besides that, WNT signaling is essential for PGC specification [START_REF] Kobayashi | Principles of early human development and germ cell program from conserved model systems[END_REF].

The appearance of a cluster of six to eight PGC cells occurs at E6.25 in the region of the future extra-embryonic mesoderm which, after cellular movements, is contiguous to the primitive streak. Prdm1-expressing cells proliferate, and at 7.5, the number of PGCs located in the primitive streak become 40 [START_REF] Chiquoine | The identification, origin, and migration of the primordial germ cells in the mouse embryo[END_REF][START_REF] Ginsburg | Primordial germ cells in the mouse embryo during gastrulation[END_REF][START_REF] Lawson | Clonal analysis of the origin of primordial germ cells in the mouse[END_REF], which corresponds to the final number of cells that will migrate to the genital ridge.

Prdm1, as well as Prdm14 and Ap2 act together to suppress the somatic gene expression and activate germ-cell specific genes [START_REF] Magnúsdóttir | A tripartite transcription factor network regulates primordial germ cell specification in mice[END_REF]. Induction of AP2 by BLIMP1 is crucial for the induction of PGC-specific genes such as Kit, Dnd1 or Nanos3 [START_REF] Magnúsdóttir | How to make a primordial germ cell[END_REF]. PRDM14 and AP2 both bind to a distally located enhancer of Pou5f1

(previously known as Oct4), a pluripotent factor, to maintain its expression in PGCs. At this point, the expression of Hox genes and other genes involved in somatic development, is repressed in PGCs.

From the other hand, PGCs express genes such as Nanog, a transcription factor associated with pluripotency maintenance in stem cells. Besides, a large number of genes involved in adhesion and migration are also expressed in PGCs [START_REF] Richardson | Mechanisms guiding primordial germ cell migration: strategies from different organisms[END_REF].

Although the exact time of the appearance of germ cells in humans is not known, migration has been observed during the 4 th week of development [START_REF] Witschi | Migration of the germ cells of human embryos from the yolk sac to the primitive gonadal folds[END_REF]. In humans, many factors are known to play a role in PGC specification.

In mouse, PGCs at the primitive streak migrate anteriorly and become incorporated into the endoderm of the hindgut, from where they migrate to the genital ridges. Mouse chemokine protein SDF-1 (Stromal-cell Derivated Factor 1) appears to act as a guiding signal at least during the terminal part of the migration. Indeed, it has been shown that in animals which do not produce SDF-1 or its receptor, CXCR4 (C-X-C chemokine receptor type 4), most of germ cells remain in the hindgut [START_REF] Molyneaux | The chemokine SDF1/CXCL12 and its receptor CXCR4 regulate mouse germ cell migration and survival[END_REF]. These two proteins are also produced in certain human cancers where they contribute to the capacity to spread to various regions of the body [START_REF] Dillenburg-Pilla | SDF-1/CXCL12 induces directional cell migration and spontaneous metastasis via a CXCR4/Gαi/mTORC1 axis[END_REF]. The migration involves other cellular chemotaxis mechanisms where the KITLG (KIT-ligand) factor and its membrane receptor KIT (expressed in PGCs) play a predominant role.

The PGCs proliferate by mitosis during their migration to approximately 30,000 PGCs by the time they reach the genital ridge. After PGC colonization, the fate of the bipotential gonad to become either a testis or an ovary is triggered by the differentiation of somatic cells into Sertoli or granulosa cells. Male and female sex differentiation will be described independently in the following sections.

Female sex-determination pathway

Although female fate was initially thought to be the default differentiation pathway, several studies involving the KO of key genes (e.g. Wnt4) have shown that differentiation of the bipotential gonad into ovaries is not just a passive process resulting from the lack of Sry.

Ovary formation occurs through the expression of female differentiation factors (Rspo1, Wnt4, -catenin, Dax1) and the repression of Cyp11a1 expression. The differentiation is initiated by the expression of RSPO1 and WNT4 in support cells. Wnt4 acts as an antagonist of the male pathway.

Rspo1 acts as a crucial regulator of canonical β-catenin signaling required for female development [START_REF] Chassot | Activation of beta-catenin signaling by Rspo1 controls differentiation of the mammalian ovary[END_REF]. The activation of WNT4/β-catenin pathway result in the inhibition of CYP11A1 delaying, therefore, the steroidogenesis and inducing the expression of FST (follistatin) and DAX1 [START_REF] Mizusaki | Dax-1 (dosage-sensitive sex reversal-adrenal hypoplasia congenita critical region on the X chromosome, gene 1) gene transcription is regulated by wnt4 in the female developing gonad[END_REF].

DAX1 plays a role in steroidogenesis inhibition and activation of STRA8 which, in turn, activates proteins from the synaptonemal complex (SYCP1-3) and trigger meiosis initiation.

Stra8 also activates Spo11, involved in the initiation of homologous recombination via introduction of DNA double-strand breaks (DSBs) and activation of recombinase protein Dmc1, which is responsible of DSBs repair. Thus, the initiation of the meiosis is the triggering event of the female sex determination pathway.

Meiosis allows the generation of haploid cells from a diploid cell following two successive divisions without any DNA replication event between these two divisions (Figure 14). The In female mice, germ cells enter meiosis at E13.5. This entry into meiosis is preceded by the transient expression of Stra8 (stimulated by retinoid acid 8) [START_REF] Menke | Sexual differentiation of germ cells in XX mouse gonads occurs in an anterior-to-posterior wave[END_REF] and is highly synchronized. Almost all the oogonia initiate the first division of meiosis between E13.5 and E15.5 [START_REF] Sarraj | Mammalian foetal ovarian development: consequences for health and disease[END_REF]. In humans, the majority of the gonocytes continue to proliferate between 6 and 14 weeks of gestation, and the germ cells enter meiosis asynchronously from the 10 th week of gestation.

Retinoic acid and Stra8 are critical for meiotic initiation. Stra8 expression increases in the fetal ovary from E12.5 to E14.5 before it decreases. This window corresponds to the period of initiation of meiosis in the ovary. Fetal testes produce CYP26B1, an enzyme capable of breaking down retinoic acid. This enzyme is not expressed in the ovary [START_REF] Bowles | Retinoid signaling determines germ cell fate in mice[END_REF][START_REF] Koubova | Retinoic acid regulates sexspecific timing of meiotic initiation in mice[END_REF]. In females, germ cells enter meiosis during fetal life, and all oocytes interrupt this process at the diplotene stage of meiosis I. This quiescent state continues until puberty. In females, meiosis is therefore asymmetric and discontinuous. From the puberty, at each cycle several ovarian follicles start to grow, but only one reach the pre-ovulatory stage. The oocyte of this follicle then resumes its meiotic division. Meiosis I ends with the expulsion of the first polar body, a leftover cell containing half of the chromosomes. The second division is then initiated and is stopped in metaphase II. Meiosis II is not resumed until after fertilization and ends with the expulsion of the second polar body. In the absence of fertilization, the quiescent oocyte degenerates.

Compared to mitotic prophase, meiosis prophase I requires more time to complete.

This step also has other specificities, notably the pairing of homologous chromosomes, involving double strand breaks in DNA. Prophase I is commonly subdivided into different stages characterized by the state of the synaptonemal complex and chromatin condensation. These are the leptotene, zygotene, pachytene, diplotene and diakinesis stages.

Following the S phase which takes place before the onset of meiosis, the cell expresses cohesins which make it possible to maintain the newly formed chromatid with its sister chromatid and thus ensure their proper alignment. Then, during leptotene, the lateral elements of the synaptonemal complex, SYCP2 and SYCP3, anchor themselves along homologous chromatids causing chromosome compaction (Figure 15). At this point, homologous recombination is initiated under the action of SPO11, which introduces DNA DSBs throughout the genome at certain loci called recombination hotspots. In females, around 500 recombination hotspots are generated [START_REF] Smagulova | Suppression of genetic recombination in the pseudoautosomal region and at subtelomeres in mice with a hypomorphic Spo11 allele[END_REF]. Following the formation of the double-stranded breaks, resection is performed on both sides of the break to produce a single-stranded DNA overhang end. This single-stranded DNA is immediately linked by RPA (replication protein A). Under the action of BRCA2, RPA is quickly replaced by the RAD51 recombinase which assembles into a filament on the single stranded DNA. Among other proteins, DMC1 provides stabilization of this nucleoprotein complex. The two recombinases, RAD51 and DMC1, then begin the search by homology that takes place during the zygotene stage. Pairing of homologous chromosomes follows through the formation of the central element of the synaptonemal complex (SYCP, SYCE-1, SYCE-2 and TEX12). The placement of the central elements between the lateral elements propagates towards the ends of the chromosomes, like a zipper. At this stage, the chromatin is very condensed. During pachytene stage, DSBs are repaired and the homologous chromosomes complete their pairing, and crossovers are formed. The synapsis is then complete and the homologous chromosomes have exchanged their genetic material with each other. During diplotene stage, the synaptonemal complex dissociates. However, some regions retain this structure, especially the centromeres and the chiasmas, thus ensuring that homologous chromosome pairing is maintained. Degradation of the synaptonemal complex leads therefore to chromatin refinement. During the last stage of prophase I, diakinesis, the chiasma terminates. This process involves the sliding of the chiasmas towards the telomeres, located at the end of the chromosomes. Thus, the non-sister chromatids are linked only by their end, until their future separation during Anaphase I. At the end of diakinesis, the nuclear envelope and the nucleoli disappear, and a division spindle is formed. This is followed the metaphase, anaphase and telophase to complete meiosis I. Meiosis then continues with the second division, in a manner similar to mitosis, without prior DNA replication. There is a phase of massive apoptosis, which is thought to be necessary for the elimination of abnormal cells with asynapsed chromosomes that could lead to the production of non-viable eggs. This phase starts around E14.5 and continues until after birth (PND2). This wave of apoptosis results from the activation of CASP9 (caspase-9) via apoptosome formation within oocytes, whose formation is triggered by a cascade of activation involving AHR (aryl hydrocarbon receptor), BAX and BCL2 (BCL2 apoptosis regulator).

At the same time (E16-E18), viable oocytes gather in clusters designated as germ cell nests. Germ cell nests are interconnected oogonia formed by incomplete cytokinesis and surrounded by somatic cells (Figure 16). PCGs differentiate into oogonia recognizable by their large size and large round nucleus. PCGs proliferate rapidly by successive mitoses and form clusters. Oogonia are linked together by cytoplasmic bridges following incomplete cytodieresis [START_REF] Ruby | Intercellular bridges between germ cells in the developing ovary of the tadpole, Rana pipiens[END_REF]. The expression of several genes is essential for female sex-determination pathway.

For example, the loss of several ovary genes, such as Rspo [START_REF] Tomizuka | R-spondin1 plays an essential role in ovarian development through positively regulating Wnt-4 signaling[END_REF], Foxl2

(Garcia- [START_REF] Garcia-Ortiz | Foxl2 functions in sex determination and histogenesis throughout mouse ovary development[END_REF] and Esr1 [START_REF] Couse | Postnatal sex reversal of the ovaries in mice lacking estrogen receptors alpha and beta[END_REF] leads to activation of the male pathway. Notably, FOXL2 and ER-α bind to a testis-specific enhancer of Sox9 (synergistically repressing its activity) during development. Wnt pathway and β-catenin is essential for Sox9 silencing and deregulation of Wnt pathway led to XY sex reversal [START_REF] Maatouk | Stabilization of β-catenin in XY gonads causes male-to-female sex-reversal[END_REF]. Foxl2 also plays a role in postnatal development; their experimental postnatal inactivation causes gonadal sex reversal [START_REF] Uhlenhaut | Somatic Sex Reprogramming of Adult Ovaries to Testes by FOXL2 Ablation[END_REF]. FOXL2 is responsible for arresting or blocking the proliferation of support cells and their differentiation into pre-granulosa cells [START_REF] Maatouk | Stabilization of β-catenin in XY gonads causes male-to-female sex-reversal[END_REF]). Yet another factor important for female sex determination is Dmrt1. Experimental inactivation of Dmrt1 [START_REF] Minkina | DMRT1 Protects Male Gonadal Cells from Retinoid-Dependent Sexual Transdifferentiation[END_REF]) also leads to the blocking of supporting cell proliferation. Thus, granulosa cells are somatic cells required for nourishing and supporting oocytes, and they produce hormones as well, and their development is strictly regulated by transcription factors. Among transcriptional factors genes RSPO1/WNT4 and FOXL2 are the major players in the regulation of pre-granulosa cell proliferation and differentiation:

Another regulator of female pathway is Wnt4 which, in turn, is regulated by growth factors Fgf9 and Fgfr2. In Fgf9 or Fgfr2 null testes, Wnt4 expression increases [START_REF] Kim | Fgf9 and Wnt4 act as antagonistic signals to regulate mammalian sex determination[END_REF].

This suggest that FGF9 pathway participate actively in the suppression of female pathway.

Then, in XX gonad, Wnt4 increases the expression of follistatin (Fst) at E11.5, which prevents the vascularization of the gonad in a male fashion. Subsequently, around E13.5 (12 th weeks in humans), the differentiated ovary is observable in ovigerous cords, that consist of PGCs surrounded by somatic cells. At this stage, PGCs are physically interconnected by cytoplasmic bridges, and develop synchronously as germ cell cysts.

In the developing ovary, individual oocytes are surrounded by pre-granulosa cells (formation of primary follicles). Majority of the early oocytes that do not assemble into primordial follicles are lost through apoptosis. Formation of primordial follicle occurs in mice after birth.

Thus, transcription factors Rspo, Wnt4, Foxl2, Dmrt1 and their partners are essential for the female pathway and among their female sex determination function is the inactivation of expression of the genes essential for the male pathway.

Ovary function in adulthood

During adulthood, reproductive organs produce functional gametes, the unique cells that are transmitted to the next generation. The gametes therefore carry all the information necessary for the development of the new organism and their production is therefore strictly controlled. This section is dedicated to a brief presentation of the structure of the ovary.

a. Structure of the ovary

The ovarian cortex is made up of many follicles integrated into the stroma, which contains fibroblasts forming the connective tissue, smooth muscle cells and interstitial cells (Figure 17). The latter include the undifferentiated cells of the theca, the degenerated cells of the atretic follicles as well as the corpus lutei. The follicles located within this stroma vary in size and are found at different developmental stages. The follicle wall contains an inner layer of granulosa cells as well as an outer layer of theca cells, separated by the basement membrane. The oocyte is located within the follicle, surrounded by granulosa cells, the number and function of which change during follicular growth. In mature follicles, theca interstitial cells express LH (luteinizing hormone) receptors and are responsible for the synthesis of androgens, including androstenedione. After ovulation of the Graafian follicle (mature follicle), the theca cells as well as the luteinizing granulosa cells divide and invade the antral cavity of the follicle to form a corpus luteum. Following this ovulation, if pregnancy does not occur, the corpus luteum degenerates and the luteinizing cells are replaced by connective tissue to form corpus albicans. In the ovary, estrogen is synthetized by theca and granulosa cells. Granulosa cells metabolize androgens produced by theca cells via Cyp19a1, also known as the aromatase.

Under the influence of LH, theca cells convert cholestenone into 17-hydroxy-pregnenolone, which is then further processed by 17-hydrolase to synthetize the androgen, androstenedione.

Under the influence of FSH, most of androstenedione is then aromatized into the major estrogen, estradiol, by the aromatase in the granulosa cells. Estradiol produced by this reaction of aromatization has an important role in oogenesis. Indeed, it is involved in follicle maturation, as well as epithelial cell proliferation during menstrual cycle. Besides it allows progesterone receptor expression which is required for egg implantation [START_REF] Drummond | The role of estrogen in folliculogenesis[END_REF].

Estrogen secretion is regulated by a negative feedback of the hypothalamus-hypophysis axis:

secretion of GnRH within hypothalamus stimulates the release of LH and FSH by the hypophysis, which are mandatory for estradiol synthesis in the ovary. In turn, estradiol acts on the GnRH release via a negative feedback, ensuring maintenance of the hormonal homeostasis [START_REF] Radovick | Estrogenic regulation of the GnRH neuron[END_REF].

Estradiol acts as a growth hormone of the female reproductive system, supporting the lining of the vagina, cervical glands, the endometrium and the lining of the Fallopian tubes. A positive feedback of the estradiol occurs during menstrual cycle and is responsible for surge of LH that triggers the ovulation. This event is characterized by the release of the egg from the follicle and the conversion of the residual follicle into a corpus luteum, which will then produce progesterone. Estrogens are ligand of ESR1 which are expressed not only in reproductive tissue, but in many other organs including liver, brain and fat tissues.

Male sex determination pathway

The genetic sex of mammals is established at the time of the conception, when the spermatozoid introduces either an X or a Y chromosome into the egg. The presence of the Y chromosome is responsible for the development of testes, and the hormones they produce trigger the formation of all the somatic tissues towards a male phenotype, and suppress the female development. The specification of the gonads into testes is controlled by a single gene, SRY. In mouse, sex determination occurs at E11.5, when Sry expression increase dramatically in Sertoli cells, through its induction by WT1 and SF1. The molecular mechanisms responsible for this differentiation, involving the expression of different factors such as SRY and SOX9 will be detailed in the next section.

b. Sex-determining Region of the Y chromosome

As often in biology, the discovery of the region triggering the differentiation into the male pathway resulted from the observation of two rare diseases; The Klinefelter's syndrome, characterized by the presence of an additional X chromosome in males (XXY), and the Turner's syndrome which corresponds to the lack of one X chromosome in females (XO). It has been observed that differentiation of the gonad into testis was dependent on the presence of the Y chromosome, regardless of the number of X chromosomes [START_REF] Jacobs | A case of human intersexuality having a possible XXY sex-determining mechanism[END_REF]. The gene responsible for the differentiation into male pathway, SRY, has been identified more than 30 years later [START_REF] Sinclair | A gene from the human sex-determining region encodes a protein with homology to a conserved DNA-binding motif[END_REF], after the discovery of a 35kb translocated region in XX females displaying male features [START_REF] Palmer | Genetic evidence that ZFY is not the testis-determining factor[END_REF].

This observation was then confirmed by transgenic experiments. It has been shown

that introduction of Sry gene into XX eggs triggers male pathway, characterized by the development of testes [START_REF] Koopman | Male development of chromosomally female mice transgenic for Sry[END_REF]. This study revealed that Sry is necessary and sufficient to determine the male pathway. However, XX + Sry males are sterile, suggesting that other genes located on the chromosome Y are mandatory for the proper development of spermatozoa.

SRY is relatively poorly conserved in mammals with the exception of the DNA binding region (HMG box). It has been shown that mutation within the HMG box could lead to sex inversion, where gonadal sex is different from genetic sex [START_REF] Ely | Review of the Y chromosome, Sry and hypertension[END_REF]. Sry is expressed in the supporting cell precursors and triggers a cascade of activation leading to their differentiation into Sertoli cells [START_REF] Larney | Switching on sex: transcriptional regulation of the testis-determining gene Sry[END_REF]. All the further morphogenetic processes needed for testis development are dependent on them.

Males have all the genes required for making ovaries, while females have all the genes required for making testes, with the exception of Sry that activates them, suggesting that activation of testis-determining pathway should actively suppress the ovarian-determining pathway.

Majority of the functional information regarding Sry regulation have been obtained using transgenic mice. With experiments involving transgenic mice, it has been shown that GATA4, its co-factor FOG2, and their physical interaction, are required to induce Sry expression [START_REF] Tevosian | Gonadal differentiation, sex determination and normal Sry expression in mice require direct interaction between transcription partners GATA4 and FOG2[END_REF]. More recently, a study using the chromatin immunoprecipitation (ChIP)

technique revealed that GATA4 binds to two regions of the promoter of Sry in mouse [START_REF] Gierl | GADD45G functions in male sex determination by promoting p38 signaling and Sry expression[END_REF]. This binding is dependent on the phosphorylated status of GATA4. Expression of Gata4 in itself is regulated by CBX2 (chromobox homolog 2), while SIX1 and SIX4 homeobox proteins are responsible for the activation of Fog2, as identified by a study involving double-KO (Six1/Six4) mice [START_REF] Fujimoto | Homeoproteins Six1 and Six4 Regulate Male Sex Determination and Mouse Gonadal Development[END_REF].

Phosphorylation of GATA4 is performed by p38 MAP kinases, Mapk11 (p38) and Mapk14 (p38) [START_REF] Warr | Gadd45γ and Map3k4 interactions regulate mouse testis determination via p38 MAPK-mediated control of Sry expression[END_REF], that are upstream regulated via MAP3K4 (mitogen-activated protein kinase kinase kinase 4) in mouse [START_REF] Bogani | Loss of Mitogen-Activated Protein Kinase Kinase Kinase 4 (MAP3K4) Reveals a Requirement for MAPK Signalling in Mouse Sex Determination[END_REF]. Nevertheless, it is envisaged that different members of the MAP3K family are responsible for the regulation of Sry in different species. At a higher level of regulation, MAPK cascade is triggered by the stressresponse protein, GADD45G. Indeed, it has been reported that GADD45G binds to MAP3K4

and activates its enzymatic activity [START_REF] Miyake | Activation of MTK1/MEKK4 by GADD45 through Induced N-C Dissociation and Dimerization-Mediated trans Autophosphorylation of the MTK1 Kinase Domain[END_REF][START_REF] Takekawa | A Family of Stress-Inducible GADD45-like Proteins Mediate Activation of the Stress-Responsive MTK1/MEKK4 MAPKKK[END_REF]. This complex activates p38-MAPK, which phosphorylates GATA4, leading to elevated expression of Sry [START_REF] Gierl | GADD45G functions in male sex determination by promoting p38 signaling and Sry expression[END_REF][START_REF] Warr | Gadd45γ and Map3k4 interactions regulate mouse testis determination via p38 MAPK-mediated control of Sry expression[END_REF]. Besides MAP3K family, insulin tyrosine kinase family is also required for the formation of male gonads. In triple mutants (Ir, Igfr1, Irr), expression of Sry is reduced [START_REF] Nef | Testis determination requires insulin receptor family function in mice[END_REF].

Another important gene for male pathway induction in humans is NR5A1. Mutations in NR5A1 (aka SF-1) leads to sex reversal in humans [START_REF] Achermann | A mutation in the gene encoding steroidogenic factor-1 causes XY sex reversal and adrenal failure in humans[END_REF]. Therefore, more studies were performed to understand its function in human gonadal development. It has been observed that NR5A1 binds to SRY promoter in humans, and alteration of this site by directed mutagenesis leads to a decreased expression of Sry in human cell lines (de Santa [START_REF] De Santa Barbara | Steroidogenic factor-1 contributes to the cyclic-adenosine monophosphate down-regulation of human SRY gene expression[END_REF]. The expression of Nr5a1 is regulated by a Polycomb group protein, CBX2 which is part of the PRC1 in mice. It has been shown that induced expression of Sry or Sox9 in M33

(mouse homolog of CBX2) KO mice is able to rescue the sex-reversal that was observed in XY mutants, suggesting that M33 potentially regulates testis determination via tuning expression of Sry [START_REF] Katoh-Fukui | Cbx2, a Polycomb Group Gene, Is Required for Sry Gene Expression in Mice[END_REF]. Similarly, XY sex-reversal has also been reported in humans carrying mutations on CBX2 [START_REF] Biason-Lauber | Ovaries and female phenotype in a girl with 46,XY karyotype and mutations in the CBX2 gene[END_REF]. Other genes involved in gonadal development and sex differentiation were found to be decreased in M33 KO mice, such as Dmrt1, Gata4 or Lhx9, suggesting that CBX2 could be implicated in further processes of the male pathway [START_REF] Katoh-Fukui | Cbx2, a Polycomb Group Gene, Is Required for Sry Gene Expression in Mice[END_REF]. The regulation of Nr5a1 by CBX2 also requires a co-factor named CITED2 (Cbp/p300 interacting transactivator with Glu/Asp-rich carboxy-terminal domain 2), which involves WT1. A schematic representation of the proposed model of the regulation of Sry is provided in Figure 19.

d. SRY-dependent induction of SOX9

The expression of SRY, stimulated by WT1 and GATA4, leads to the differentiation of supporting cells into Sertoli cells, via the induction of AMH. The expression of Sry in the XY gonad triggers dramatic changes in gonadal gene expression. The first downstream target of Sry that is subjected to upregulation is Sox9. (Figure 20). Inactivation of SOX9 in humans and mice leads to male-to-female sex-reversal [START_REF] Foster | Campomelic dysplasia and autosomal sex reversal caused by mutations in an SRY -related gene[END_REF][START_REF] Wagner | Autosomal sex reversal and campomelic dysplasia are caused by mutations in and around the SRYrelated gene SOX9[END_REF]. Conversely, duplication of SOX9 in humans or over-expression of Sox9 in mice lead to female-tomale sex-reversal [START_REF] Huang | Autosomal XX sex reversal caused by duplication of SOX9[END_REF][START_REF] Sekido | SOX9 is up-regulated by the transient expression of SRY specifically in Sertoli cell precursors[END_REF]. These studies revealed the central role of Sox9 in sex determination.

ChIP-seq experiment targeting SOX9 in mouse and bovine revealed that SOX9 binds more than 4000 target genes, including most of those already implicated in testis determination [START_REF] Rahmoun | In mammalian foetal testes, SOX9 regulates expression of its target genes by binding to genomic regions with conserved signatures[END_REF].

In mice, expression of Sox9 start to be detectable at E10.5. SOX9 is present at low levels in the cytoplasm of cells of both male and female genital ridges before SRY expression.

SRY and SF1/NR5A1 bind to TESCO, a testis-specific enhancer of Sox9, directly and activate it synergistically [START_REF] Sekido | Sex determination involves synergistic action of SRY and SF1 on a specific Sox9 enhancer[END_REF]). An autoregulatory loop has been described for this. SF1 and SOX9 complex can bind to TESCO and thereby stimulate expression of Sox9 via this positive feedback loop [START_REF] Sekido | Sex determination involves synergistic action of SRY and SF1 on a specific Sox9 enhancer[END_REF]. However, genetic edition of TESCO does not lead to loss of Sox9 expression, suggesting the existence of one or several other enhancers [START_REF] Gonen | Normal Levels of Sox9 Expression in the Developing Mouse Testis Depend on the TES/TESCO Enhancer, but This Does Not Act Alone[END_REF].

Figure 20. Sox9 is the central element triggering the differentiation of male gonad. From [START_REF] Ono | Disorders of sex development: new genes, new concepts[END_REF].

It has been reported that high levels of Sox9 lead to repression of Sry expression around E12.0, suggesting the existence of a Sox9-dependent negative feedback loop [START_REF] Chaboissier | Functional analysis of Sox8 and Sox9 during sex determination in the mouse[END_REF][START_REF] Sekido | SOX9 is up-regulated by the transient expression of SRY specifically in Sertoli cell precursors[END_REF].

Overexpression of Sox9 in the genital ridges induces testis development in XX transgenic mice [START_REF] Vidal | Sox9 induces testis development in XX transgenic mice[END_REF]. Sox9 is the main responsible for sex determination, through the activation of numerous targets necessary for the induction of Sertoli cell phenotype [START_REF] Li | The Sex-Determining Factors SRY and SOX9 Regulate Similar Target Genes and Promote Testis Cord Formation during Testicular Differentiation[END_REF]. It is thought that Sox9 maintains its own expression to lock the Sertoli cell identity throughout the life of an individual.

To ensure and accelerate the commitment of the male pathway, FGF9 promotes the maintenance of Sox9 expression at a high level in the supporting cell lineage via a positivefeedback loop [START_REF] Colvin | Male-to-female sex reversal in mice lacking fibroblast growth factor 9[END_REF]. Deletion of Fgf9 or its receptor Fgfr2 results in male-tofemale sex-reversal [START_REF] Kim | Fibroblast growth factor receptor 2 regulates proliferation and Sertoli differentiation during male sex determination[END_REF], indicating that FGF9 represses Wnt4 expression in the testis. Another factor important for male pathway is prostaglandin D2 (PGD2). In mouse, L-PGDS (lipocaline prostaglandin D synthase), responsible for the synthesis of prostaglandin D2, is specifically expressed in male gonads [START_REF] Wilhelm | Sertoli cell differentiation is induced both cell-autonomously and through prostaglandin signaling during mammalian sex determination[END_REF][START_REF] Wilhelm | SOX9 regulates prostaglandin D synthase gene transcription in vivo to ensure testis development[END_REF]. As previously mentioned, before the peak expression of Sry at E11.5, Sox9 is expressed at a very low level. It has been identified that PGD2 and its DP1 receptor are autocrine factors implicated in the activation of Sox9, and therefore, in the differentiation of Sertoli cells.

Other genes have been reported to be involved in the differentiation of the fetal gonad.

One of most important factors responsible for germ cell development is Nr5a1. Besides activation of Sry, Nr5a1 play a role in activation of many genes essential for male pathway functioning. Mice lacking Nr5a1 do not develop testis [START_REF] Ikeda | The nuclear receptor steroidogenic factor 1 is essential for the formation of the ventromedial hypothalamic nucleus[END_REF][START_REF] Luo | A cell-specific nuclear receptor is essential for adrenal and gonadal development and sexual differentiation[END_REF]Shen et al., 1994). Nr5a1 is expressed in both Sertoli and Leydig cells [START_REF] Ikeda | Developmental expression of mouse steroidogenic factor-1, an essential regulator of the steroid hydroxylases[END_REF]. Nr5a1 plays a regulatory role in the transcription factor network that include WT1, SOX9 and GATA4. This complex, for example, is required to trigger the expression of hormone AMH [START_REF] Arango | Targeted Mutagenesis of the Endogenous Mouse Mis Gene Promoter: In Vivo Definition of Genetic Pathways of Vertebrate Sexual Development[END_REF][START_REF] Barbara | Direct Interaction of SRY-Related Protein SOX9 and Steroidogenic Factor 1 Regulates Transcription of the Human Anti-Müllerian Hormone Gene[END_REF][START_REF] Nachtigal | Wilms' Tumor 1 and Dax-1 Modulate the Orphan Nuclear Receptor SF-1 in Sex-Specific Gene Expression[END_REF][START_REF] Shen | Nuclear receptor steroidogenic factor 1 regulates the müllerian inhibiting substance gene: A link to the sex determination cascade[END_REF][START_REF] Watanabe | Endogenous expression of Müllerian inhibiting substance in early postnatal rat Sertoli cells requires multiple steroidogenic factor-1 and GATA-4-binding sites[END_REF].

Thus, Nr5a1 is a critical factor for regulation of hormone synthesis.

Yet another factor, FGF9 is also required for the differentiation of Sertoli cells. It has been shown that mice lacking the Fgf9 gene develop into females [START_REF] Colvin | Male-to-female sex reversal in mice lacking fibroblast growth factor 9[END_REF]. FGF9

suppresses the expression of Wnt4, which otherwise promotes the development of ovaries by suppressing the expression of Sox9 [START_REF] Jameson | Testis development requires the repression of Wnt4 by Fgf signaling[END_REF]. Thus, the development of testes requires active suppression of the female pathway.

Sertoli cells orchestrate the cellular differentiation of other cell types: Leydig cells, peritubular myoid cells, germ cells and endothelial cells, which rely on paracrine factors produced by the Sertoli cells. When PGCs are surrounded by Sertoli cells, they are defined as "gonocytes".

Testis functions in the adulthood

Mammalian spermatogenesis takes place in the seminiferous tubules of the testis. The seminiferous tubules include the germ cells at all stages of maturation with the most mature cells located closest to the central lumen.

The testes perform two important functions, the production of gamete or spermatogenesis, and the steroidogenesis. These two functions are regulated by the gonadotropins, LH and FSH, produced by the pituitary gland under the control of the hypothalamus.

Spermatozoa begin to form within the testis from the germinal stem cells, i.e. the spermatogonia. They then complete their maturation in the epididymis, where they notably acquire their ability to move.

a. Structure of the testis

The testis is enclosed in a fibrous capsule through which nerves and blood vessels pass. This capsule is made up of three layers of tissue, the tunica serosa, the tunica albuginea In the second phase, i.e., the meiotic phase, the spermatocytes experience two meiotic divisions to generate the haploid cells. In males, germ cells initiate meiosis just before puberty.

The two divisions of meiosis are successive and result in four haploid cells, the round spermatids. Unlike females, meiosis in males is asymmetric and continuous. From one spermatogonia, four spermatozoids are produced. In females, from one germ-cell only one oocyte is produced.

In the third phase, the spermatids undergo the final transformation to form mature sperm. This transition requires major physical and structural reorganizations in the cells, and this process is known as spermiogenesis.

b. Spermiogenesis

Once meiosis is completed, the spermatids that are produced will undergo profound morphological changes to become spermatozoa with fully compacted chromatin. This process of spermiogenesis is subdivided into six stages namely Sa, Sb1, Sb2, Sc, Sd1 and Sd2. (Figure 22). It takes 23 days to undergo full maturation of the round spermatid within the adluminal compartment of seminiferous tubule.

The Sa1 phase is characterized by a well-developed and differentiated Golgi complex and mitochondria. At this stage, the cell still presents a more or less circular shape. Then, the acrosomal vesicle appears, derived from Golgi apparatus, and the chromatoid body, a dense structure composed of RNAs and RNA-binding proteins, develops in the opposite pole of the cell. Acrosome formation is then completed within the phases Sb1 and Sb2. During these steps, the middle piece is formed and the tail develops, until the Sc phase where this process is completed.

The nucleus of the spermatozoa elongates and flattens throughout the spermiogenesis.

The morphological changes that take place in the nucleus results from the re-organization of the chromatin into a highly organized, condensed and compact structure. This process is characterized by a nuclear shape transformation, conversion of supercoiled nucleosomal DNA into a non-supercoiled state, induction of DNA breaks, and chromatin condensation [START_REF] Desai | Female and Male Gametogenesis[END_REF].

During the chromatin re-organization, histones are replaced by testis specific histone variants, such as H1T2, Th2B or H3.3. These replacements constitute the first of a cascade of substitutions. Indeed, between histone eviction and protamine incorporation, transition proteins that are arginine-and lysine-rich, encoded by Tnp1 and Tnp2 genes, are incorporated into the nucleus of the spermatids. From [START_REF] Desai | Female and Male Gametogenesis[END_REF].

H4ac is indispensable for histone-to-protamine transition. (Figure 23). The increase of this histone mark, specially at lysines K5, K8, K12 and K16, is the earliest event to precede the histone-to-protamine transition, and is conserved during evolution [START_REF] Bao | Epigenetic regulation of the histone-to-protamine transition during spermiogenesis[END_REF]. It is suggested that H4 hyper-acetylation could be responsible for unpacking of the chromatin, and therefore could help in the eviction of histones.

The bromodomain testis associated (BRDT) protein binds to hyperacetylated H4 and triggers a reorganization of the chromatin [START_REF] Pivot-Pajot | Acetylation-Dependent Chromatin Reorganization by BRDT, a Testis-Specific Bromodomain-Containing Protein[END_REF]. BRDT specifically recognizes acetylated lysine residues and is able to interact with the SWI/SNF family proteins [START_REF] Dhar | Insights into role of bromodomain, testis-specific (Brdt) in acetylated histone H4-dependent chromatin remodeling in mammalian spermiogenesis[END_REF]. This complex is in charge of the removal of histones and their replacement by transition proteins, TP1 and TP2, in condensing spermatids. The biological functions of the transition proteins remain largely unknown; however, it is suggested that they are involved in facilitating the eviction of remaining histones, as well as in condensation of the DNA. In elongated spermatids, the transition proteins are replaced by protamines in late spermatids.

133

Protamination occurs late in spermiogenesis, when the transcription has already stopped.

Transcripts are synthetized earlier, in primary spermatocytes, and are translationally repressed until elongated spermatid stage [START_REF] Raja | Replacement by Drosophila melanogaster Protamines and Mst77F of Histones during Chromatin Condensation in Late Spermatids and Role of Sesame in the Removal of These Proteins from the Male Pronucleus[END_REF]. Protamines tightly interact

with DNA via a central DNA binding domain which is rich in arginine [START_REF] Balhorn | The protamine family of sperm nuclear proteins[END_REF]. The binding of highly-basic protamines neutralizes the negative charge on the DNA which enables adjacent DNA molecules to pack close together. Finally, the DNA-bound protamines are locked into their place during epididymal transit by the formation of a network of disulfide bonds [START_REF] Balhorn | The protamine family of sperm nuclear proteins[END_REF].

The precise molecular mechanisms underlying the chromatin re-organization that occur during spermiogenesis are still not understood perfectly. However, it is known that the re-organization of the chromatin is critical for correct morphological transitions from round spermatid to mature spermatozoid, and any alterations in this process could lead to male infertility or reduced fertility [START_REF] Wang | Essential Role of Histone Replacement and Modifications in Male Fertility[END_REF]. Table 5. The main histone variants and the modifications during histone-to-protamine transition. From [START_REF] Wang | Essential Role of Histone Replacement and Modifications in Male Fertility[END_REF].

The epididymis plays an essential role in storage, maturation and transport of sperm between the testis and the deferens duct. The epididymis is a coiled segment of the spermatid ducts and consists of caput (head), corpus (body) and cauda (tail) sub-compartments. The epididymal duct consists of a number of joint efferent tubules, which elongate from the testis till the head of the epididymis. The epididymal duct is a very thin and largely convoluted tubule lined by a columnar epithelium containing cilia and microvilli. The epididymal duct also contributes to absorption of testicular fluid and storage of sperm.

During their transport through the epididymis, spermatozoa undergo crucial morphological and functional changes. In addition to attaining motility, the midpiece and acrosome of spermatozoa get organized in a compact manner. During sperm transition through the epididymis, there are several major changes that occur in the cells including modification of the sperm chromatin, the migration of the cytoplasmatic droplet from the neck to the region near the annulus, and the alternation of the acrosome size. Without these transformations, the spermatozoa are immotile and immature even if they are fully formed when they leave the testes.

The proportions of a variety of proteins in the epididymal fluid changes during the sperm of AR-expressing cells in the mesenchyme to form prostatic buds. Although prostatic bud formation cannot occur in the absence testosterone, several other factors including SHH, SOX9, HOXB13, and WNT5A are also required for prostatic bud formation and subsequent prostate ductal development. Prostate buds initiate as small epithelial projections that elongate into the surrounding stroma. This growth starts around E17 in mice (10 to 24 weeks in humans). Meanwhile, AR-expressing epithelial cells undergo differentiation to form the epithelium of the prostate. E-cadherin is also involved in prostate bud elongation. The buds then branch, under the influence of BMP2, to develop into a tree-like structure to form a network of ducts. AR is also necessary for the timing of prostate bud formation.

The Hox genes are homeobox genes that encode transcription factors that play an essential role in determining cell identity during development, especially along the antero-posterior axis. These genes are also involved in the proliferation and differentiation of embryonic and adult stem cells.

Mammals have 39 Hox genes separated into four paralogous clusters, called A, B, C and D. In humans, they are located on chromosomes 7, 17, 12 and 2, respectively. Within each cluster, gene expression is activated from the 3′ end of the cluster (anterior region), towards the 5' end (posterior region). The expression of these genes is spatiotemporally regulated and is involved in the development of genitourinary structures.

As previously explained, male sex organs have a mesodermal origin and develop from Wolffian duct. On the contrary, the prostate gland originates from the endoderm as it is derived from the urogenital sinus [START_REF] Prins | Molecular signaling pathways that regulate prostate gland development[END_REF]. In rodents, the Hoxc11 gene is involved in the development of the urogenital sinus. Other Hox genes play an important role in normal prostate development, including the posterior Hox genes, such as Hoxa9-11, Hoxa13, Hoxd13 and Hoxb13. Indeed, they are responsible for the development of different lobes of the prostate, seminal vesicles and epididymis [START_REF] Huang | Posterior Hox gene expression and differential androgen regulation in the developing and adult rat prostate lobes[END_REF]. The Hox code participates in the determination of the prostate-specific identity of the lobe and cell differentiation [START_REF] Huang | Posterior Hox gene expression and differential androgen regulation in the developing and adult rat prostate lobes[END_REF].

Another homeobox gene, Nkx3-1, plays an important role in the normal differentiation of the prostate epithelium. Induced expression of Nkx3-1 in fully differentiated murine seminal vesicle epithelium is sufficient to reprogram the cells to prostatic epithelium [START_REF] Dutta | Identification of an NKX3.1-G9a-UTY transcriptional regulatory network that controls prostate differentiation[END_REF].

Loss of Nkx3.1 is a tumor-initiating event that disrupts normal prostate epithelial differentiation.

Moreover, it has been reported that reduced expression of NXK3.1, triggered by a functional variant (rs1512268), is associated with sporadic prostate cancer [START_REF] Akamatsu | A functional variant in NKX3.1 associated with prostate cancer susceptibility downregulates NKX3.1 expression[END_REF]. Deletion of Nkx3.1 in mice leads to the appearance of prostatic epithelial hyperplasia (PIN) and dysplasia, which becomes increasingly more apparent with advancing age (Abdulkadir et al., 139 2002;[START_REF] Park | Deletion of NKX3.1 via CRISPR/Cas9 Induces Prostatic Intraepithelial Neoplasia in C57BL/6 Mice[END_REF]. The majority of the homozygous mutant mice develop, with time, histological features that resemble human PIN, which is thought to be the primary precursor of prostate cancer. (Figure 24). Histologic findings in these mice include perturbation of the basal cell layer, attenuation of the stroma, and heterogeneous expression of markers of epithelial differentiation (Abate- [START_REF] Abate-Shen | Integrating differentiation and cancer: The Nkx3.1 homeobox gene in prostate organogenesis and carcinogenesis[END_REF]. For a review on the role of Nkx3.1 in normal prostate development and its involvement in prostate cancer, see (Abate- [START_REF] Abate-Shen | Integrating differentiation and cancer: The Nkx3.1 homeobox gene in prostate organogenesis and carcinogenesis[END_REF].

Figure 24. Schematic representation of evolution from normal prostate to pre-malignant and cancerous states. From [START_REF] Packer | The molecular and cellular origin of human prostate cancer[END_REF].

The prostatic ducts differentiate from the urethra to the ductal tip, in the growing prostate. This cord initially composed of epithelial cells proliferate, and the growth of the duct trigger differentiation into epithelial and basal cells.

In rodents, prostate differentiation initiation takes place shortly before birth (approximately 2 days before for mice). The development of the prostate, therefore, continues during childhood and adolescence, and becomes functional around week 8 of rodent life, and at the time of puberty in humans.

Structure and function of the prostate

About 40-50% of the prostate is made up of stroma, the supporting tissue, that includes blood vessels, nerves, smooth muscles and fibrous tissue. Stromal cells play an important role in both the differentiation and development of the prostate, and in maintaining its architecture.

The stroma/epithelium ratio is less in prostate of the rodents compared to humans.

The basal epithelial cells of the prostate are flattened and lie along the epithelial basement membrane. (Figure 25). They express a range of characteristic markers, including p63 and cytokeratins 5 and 14. These cells lack contractile power, unlike epithelial cells from other organs. Prostate secretions are therefore excreted by the contraction of the smooth muscles of the prostate, during ejaculation. Unlike humans, in mice, the basal cells do not form a continuous layer but are rather interspersed. Luminal epithelial cells line the prostate ducts, and are characterized by the expression of cytokeratins 8 and 18, as well as AR expression. Depending on the region of the prostate, the luminal cells are cuboidal or columnar in shape.

Epithelial cells are those responsible for the production and secretion of components of the prostatic fluid. Another cell type found in the prostate is the neuroendocrine cells. They are nevertheless much rarer and scattered. Their precise function is not known, but it is suggested that they play a role in cellular communication with non-endocrine cells of the prostatic epithelium, and thus regulate cell differentiation and secretions from the epithelium.

In rodents, the prostate is composed of four lobes designated as anterior, dorsal, lateral and ventral prostate, based on their relative position around the urethra. In contrast, in humans, the prostate is a single-lobed organ, nevertheless subdivided into distinct areas based on different histological and anatomical criteria: central, transitional and peripheral prostate. The dorso-lateral lobe in mice is considered to be similar to the human peripheral zone. However, it is mostly accepted that no direct relationship exists between different prostate areas of humans with the lobes in rodents.

Figure 25. Major cell types found in the prostate. From [START_REF] Sasaki | Prostate-Overview[END_REF].

In men, the transition zone, which surrounds the urethra and represents about 5% of the prostate volume, is the innermost part of the prostate gland. The latter is surrounded by the central zone, within which the ejaculatory ducts connect to the urethra. It represents about a quarter of the total volume of the prostate. Finally, the peripheral zone represents the majority of the glandular prostate volume (~70%) and is located in the back of the prostate gland. It is within this zone that majority of prostate cancer occurs.

Secretions of the prostate are mainly produced by the luminal cells. These secretions are carried to the urethra via multiple prostatic ducts upon ejaculation. These prostatic secretions contribute to the ejaculate and also promote sperm health (Table 6). The production of the prostatic component of the seminal plasma is controlled by circulating androgens. The circulating androgens are converted by prostate cells into DHT, which binds to AR within luminal cells. Activated AR binds to its response elements on the genome and initiates transcription of secretory proteins or enzymes whose products are secreted into seminal fluid [START_REF] Gauntner | Prostate-Cell Biology and Secretion[END_REF].

Table 6. Prostate-secreted components of the human seminal plasma. From [START_REF] Gauntner | Prostate-Cell Biology and Secretion[END_REF].

C. The circulatory system

In the context of certain pathologies, the main treatment is based on a surgical operation aimed at partially or totally removing the affected organ. This is the case, for example, with nephrectomies in kidney cancer. Performing such surgical procedures, in addition to treating the disease, allow recovery and also study human samples to understand the mechanisms related to the disease. When a research project is based on exposures and in the absence of any pathology, it is unthinkable to obtain tissue biopsies for obvious ethical reasons. To carry out these projects of interest, it is therefore necessary to resort to non-invasive or minimally invasive sampling. These samples may consist of urine, hair, oral epithelial cells, or peripheral blood.

In addition to the studies carried out in mice, our work focused on the consequences of exposure of CD to humans in utero. The biological material available consisted of blood from the umbilical cord of newborns, collected at the time of delivery, as well as peripherical blood from mothers. This final section will therefore be devoted to the description of the circulatory system with an emphasis on nucleated cells of the blood, which constitutes the cellular compartment within which the epigenetic mechanisms can be studied.

The circulatory system is made up of the heart, blood vessels and blood. The latter is continuously distributed throughout the body via the blood vessels and the heartbeat. The blood delivers vital elements (nutrients, oxygen) to all the body's organs. It is also responsible for ensuring long-distance interactions within the body through the transport of hormones from the endocrine glands to the target organs. Finally, the white blood cells are involved in the body's immunity. In the early stages of the embryonic development, oxygen and the necessary metabolites can be supplied by diffusion. However, this diffusion is quickly gets limited by the growing size of the embryo, making it essential to set up the circulatory system at the start of development.

Development of the circulatory system

The heart develops from the mesoderm, just below the anterior part of the gut. It is initially formed as a tube-like structure that joins with the blood vessels, which also forms from the mesoderm. Other mesodermal cells form a coat around the heart tube and become the myocardium. At this point, the heart is within a structure called the pericardial coelom. The heart then folds on itself, expanding into the pericardial cavity. The sinus venosus sinus and the atrium lie above the ventricle and the bulbus cordis, the embryonic equivalent of the arterial cone. The septa gradually divide the heart into chambers.

Development of the hematopoietic system

The hematopoietic system is responsible for the development of blood cells from hematopoietic stem cells (HSC). HSCs are characterized by their dual ability to self-renew and differentiate in all lineages of the blood and immune system, i.e., its multipotency. During adult life, HSCs are localized in the bone marrow where they differentiate into immature progenitors, which in turn undergo progressive proliferation and differentiation events, until they form blood cells, such as erythroids, myeloid cells or lymphocytes.

During development, the establishment of the hematopoietic system is divided into two waves. Primary hematopoiesis, which generates a transient hematopoietic cell population, and a definitive or permanent hematopoiesis, which occurs later, where hematopoietic cell populations are produced from definitive multipotent HSCs. Blood cell production in the embryo is first performed by the yolk sac. Then, from mid-gestation, the production is shifted to the fetal liver and thymus (for T-cell), before it is transiently moved to the spleen and finally to the bone marrow by the end of the gestation [START_REF] Godin | Kaufman's Atlas of Mouse Development Supplement[END_REF] In mice, primitive hematopoiesis takes place in the extra-embryonic mesoderm layer of the yolk sac from E7.25 (3 rd week of development in humans). Mesodermal cells of the yolk sac form an aggregate of cells, which are at the origin of both vascular system and extraembryonic hematopoiesis. The peripheral cells start to express endothelial markers while the central cells are eliminated to create the lumen of the first blood vessels. Certain mesodermal cells remain attached to the newly formed vascular epithelium. These cells are termed blood islands, and give rise mainly to primitive erythroid cells, as well as megakaryocyte and macrophage lineage cells.

Later, during the development (E9-E11.5), occurs the definitive hematopoiesis which takes place inside the embryo, within the para-aortic splanchnopleura (P-Sp) and the aortagonad-mesonephros (AGM) region [START_REF] Godin | Kaufman's Atlas of Mouse Development Supplement[END_REF]. (Figure 26). Blood cell progenitors produced during the second wave are multi-lineage whereas those from the yolk sac only generate progenitor cells with limited erythro-myeloid potential [START_REF] Tavian | The human embryo, but not its yolk sac, generates lympho-myeloid stem cells: mapping multipotent hematopoietic cell fate in intraembryonic mesoderm[END_REF]. In human embryos, during the 5 th week of gestation, small groups of 2-3 cells expressing CD34 glycoprotein at their surface are detected [START_REF] Tavian | Aorta-associated CD34+ hematopoietic cells in the early human embryo[END_REF]. They are the hematopoietic cell progenitors, which then proliferate rapidly to form clusters of several thousands of cells.

Fetal liver and thymus are the major lymphohematopoietic organs during the mid-gestation period.

Cell composition of blood in adulthood

HSCs are able to differentiate into cells of two primary lineages, lymphoid and myeloid.

Cells of the myeloid lineage develop during the process of myelopoiesis and include granulocytes, monocytes, megakaryocytes, and dendritic cells. Circulating erythrocytes and platelets also develop from myeloid progenitor cells. Erythrocytes make up 99% of the circulating cells in the blood, while white cells make up the remaining 1%. The latter are characterized by the surface marker, CD45.

Among the white blood cells, the majority of the cells are polynuclear cells, in particular neutrophils. Normal proportions are in the order of: 62% of neutrophils, 2.3% of eosinophils, 0.4% of basophils. Monocytes account for about 5.3% of the white blood cells and finally lymphocytes represent the last 30%.

Granulocytes express the CD15 surface marker and participate in the innate immune response, although different granulocytes have different functions. Indeed, neutrophils have a phagocytosis function. They can also release soluble antimicrobial compounds or generate neutrophil extracellular traps, which are networks of extracellular fibers composed of neutrophil DNA that binds to pathogens and traps them [START_REF] Brinkmann | Neutrophil extracellular traps kill bacteria[END_REF]. Basophilic granulocytes are involved in inflammation. They release from their granules, among other things, histamines, responsible for the recruitment of other immune cells. They are also involved in allergic reactions. Finally, the role of eosinophils is to kill the parasites, via the release of certain proteins such as cathepsin. In addition, they are also antigen presenting cells.

145

Monocytes (CD14 +) are also nucleated blood cells that differentiate when passing through biological tissues. They differentiate either into macrophages or dendritic cells. Like granulocytes, monocytes are part of the innate immune system. Monocytes, along with the resulting macrophages and dendritic cells, perform three functions: phagocytosis, antigen presentation and cytokine production.

Natural killers (CD3-/ CD16 + 56 +) are important in fighting against tumors and virusinfected cells, through the identification of changes in the major histocompatibility complex I (MHC I). They are activated by interferons and modulate the function of other immune cells such as macrophages or T lymphocytes.

T lymphocytes (CD3+) are involved in cellular immunity, i.e., against pathogenic organisms present inside cells. T lymphocytes are further subdivided into cytotoxic T lymphocytes (CD8+), whose role is to kill infected cells, regulatory T lymphocytes, which help to prevent activation of autoimmune lymphocytes, and finally the T helper lymphocytes (CD4+). T helpers proliferate after being presented with the antigen to activate other cell types, through the secretion of interleukin 2 (IL2).

B lymphocytes (CD19+), on the other hand, play an important role in humoral immunity, i.e., adaptive immunity by production of antibodies. Again, B cells can be subdivided into four groups. Naive B cells, which have never yet encountered the antigen against which they are intended, plasma cells which secrete antibodies to facilitate phagocytosis by specialized cells, memory B cells which are formed specifically against the antigens encountered during the primary immune response, and finally the regulatory B cells, involved in the control of autoimmune inflammation.

Umbilical cord blood

Umbilical cord is an anatomical structure that connects the mother to the fetus during pregnancy. It provides oxygen and nutrients to the fetus, and excretes waste products from the fetus. Umbilical cord contains two arteries and one vein, covered by a mucous connective tissue called Wharton's jelly. The latter is then covered by the amniotic epithelium [START_REF] Nasadyuk | Umbilical cord stem cells: biological characteristics, approaches to banking and clinical application[END_REF].

Nucleated red blood cells are absent or rare in adulthood. However, they are commonly present in low proportion in the umbilical cord blood, with a higher number being associated with a variety of maternal and fetal health factors [START_REF] De Goede | Nucleated red blood cells impact DNA methylation and expression analyses of cord blood hematopoietic cells[END_REF].

Cord blood contains fewer hematopoietic progenitors than bone marrow. Indeed, 100mL of placental blood contains only one tenth of nucleated and progenitor cells than the same amount of blood from the bone marrow. However, cord blood contains a higher proportion of immature progenitors, capable of restoring long-term hematopoiesis after an event of transplantation.

Umbilical cord blood is also a source of stem cells that are genetically unique to a newborn donor. It has been reported that stem cells from umbilical cord express surface markers CD29, CD44, CD73, CD90, CD105. On the contrary, they no do express CD14, CD34, CD45 [START_REF] Dominici | Minimal criteria for defining multipotent mesenchymal stromal cells. The International Society for Cellular Therapy position statement[END_REF][START_REF] Ullah | Human mesenchymal stem cells -current trends and future prospective[END_REF] Umbilical cord blood is source of neonatal material which is very commonly used in epidemiological studies. Together with placenta they could be used, after birth, for the analysis of exposure to toxicants and also to evaluate human health effects. This is not an invasive way of getting human mother and child material. Based on the material available, several studies were accomplished in humans including studies on the effects of smoking, bisphenol exposures and other toxicants.

Table 7. Physical and chemical properties of chlordecone. Adapted from (Agency for Toxic Substances and Disease Registry (ATSDR), 2019).

Endocrine disrupting properties

CD has the ability to bind to both subtypes of estrogen receptors (alpha and beta), with approximately the same affinity. This property has been shown in in vitro studies, as well as in an in vivo study using rats [START_REF] Bulger | Studies on the estrogenic activity of chlordecone (Kepone) in the rat: effects on uterine estrogen receptor[END_REF][START_REF] Hammond | Estrogenic activity of the insecticide chlordecone (Kepone) and interaction with uterine estrogen receptors[END_REF][START_REF] Williams | Estradiol and chlordecone interactions with the estradiol receptor[END_REF].

This property was found to be highly surprising because of the cage-like structure of the CD (which is unlikely to form phenolic metabolites, on the contrary to DDT analogues, which are also estrogenic compounds). It has also been shown that CD is able to bind to recombinant human estrogen receptors [START_REF] Bolger | Rapid screening of environmental chemicals for estrogen receptor binding capacity[END_REF][START_REF] Scippo | Recombinant human estrogen, androgen and progesterone receptors for detection of potential endocrine disruptors[END_REF]. The binding of CD to estrogen receptors is around 1,000 times less than estradiol, with a very slight increased affinity for ERβ [START_REF] Kuiper | Interaction of estrogenic chemicals and phytoestrogens with estrogen receptor beta[END_REF]. However, this binding causes the translocation of the receptor from the cytoplasm to the nucleus. It is suggested that CD could have a tissue-specific affinity for estrogen receptors, as variable binding affinity was observed in brain and in uterus [START_REF] Williams | Estradiol and chlordecone interactions with the estradiol receptor[END_REF]. Moreover, in complement to differential affinity, it has been reported that CD could have different effects depending on the tissue. CD is considered to be an agonist of estrogen receptors in the uterus while it has been observed to act as an antagonist in the central nervous system [START_REF] Huang | Anti-estrogenic action of chlordecone in rat pituitary gonadotrophs in vitro[END_REF][START_REF] Uphouse | Failure of chlordecone (Kepone) to induce behavioral estrus in adult ovariectomized rats[END_REF]. It has been found

that CD also display the ability to bind to human recombinant progesterone receptors with a relatively high affinity (200-fold less compare to progesterone) [START_REF] Scippo | Recombinant human estrogen, androgen and progesterone receptors for detection of potential endocrine disruptors[END_REF]).

An epidemiological study performed in Guadeloupe, revealed that the level of CD in cord blood at the time of delivery was positively associated with an increased level of the thyroid-stimulation hormone (TSH) in males, three months after birth [START_REF] Cordier | Perinatal exposure to chlordecone, thyroid hormone status and neurodevelopment in infants: the Timoun cohort study in Guadeloupe (French West Indies)[END_REF]. Other studies performed in animal models revealed that exposure to CD led to effects on adrenal gland. Specifically, it has been reported that rats exposed to CD presented an increase in size and weight of the adrenal gland, which can be associated with hyperplasia and hypertrophy of cortical cells [START_REF] Cannon | Short-term chlordecone toxicity in rats including effects on reproduction, pathological organ changes, and their reversibility[END_REF][START_REF] Swanson | Comparison of the neurotoxic effects of chlordecone and dieldrin in the rat[END_REF]. Considering these observations, CD is classified as an endocrine-disrupting compound. These features of CD could, in part, explain its reprotoxicity, which will be discussed in more detail in the dedicated sections. [START_REF] Epstein | Kepone--hazard evaluation[END_REF]. For pesticide use, CD mixture was mostly found as a wettable powder containing around less than 50% of the CD. However, formulations containing up to 90% of CD were exported to Europe. The production from the main factory located in Hopewell, Virginia was ceased on 24 th July 1975, following hospitalization of several workers presenting neurological disorders (DHHS, 2011). Following this incident, the Environmental Protection Agency (EPA) banned the production, the selling and the use of CD in the US in April 1977 [START_REF] Epstein | Kepone--hazard evaluation[END_REF][START_REF] Joly | La saga du chlordécone aux Antilles françaises Reconstruction chronologique[END_REF]. A second wave of CD production took place in France under the commercial name of Curlone® between 1981 and 1990, following the cease of production in the US. The restart of this production of CD was linked to banana lobbies who were facing a serious invasion by banana root borer pest in the French West Indies. It is only in July 1990 that French government banned the production and use of CD [START_REF] Le Déaut | Les impacts de l'utilisation de la chlordécone et des pesticides aux Antilles : bilan et perspectives d'évolution[END_REF]. This interdiction was effective in the French mainland, however, two consecutive derogations were given to banana producers in the French islands, where the product was officially in use until 1993 [START_REF] Le Déaut | Les impacts de l'utilisation de la chlordécone et des pesticides aux Antilles : bilan et perspectives d'évolution[END_REF].

Production and usage of chlordecone

Until its interdiction in 1975, Kepone® was exported and used in the French West Indies, and was then replaced by the Curlone®. The Curlone® was mostly used in the French West Indies, in banana crops. From 1973 to 1993, CD has been used to control banana root borer (Cosmopolites sordidus). The formulation used contained 5% of CD. The recommendation was to use 30g of powder per tree (i.e., around 1.5g of active CD) representing a quantity of active CD of around 3kg per hectare per year (counting 800 banana trees per hectare). The product had to be placed all around the trunk of the banana tree and was applied every 6 to 18 months depending on the level of infestation of the field [START_REF] Vilardebo | Chlordecone et autres insecticides dans la lutte contre le charançon du bananier Cosmopolites sordidus Germ[END_REF].

Other formulations were used in different regions of the world, ranging from 0.125% to 50%, depending on the applications (ant and roach traps, to control Colorado potato beetles or mole crickets). Although CD was mainly used as an insecticide, other uses were also reported such as use as a fungicide [START_REF] Cabidoche | Conclusions du groupe d'étude et de prospective : Pollution par les organochlorés aux Antilles[END_REF].

Environmental pollution by chlordecone

Most of the pesticides that pollute the environment get progressively eliminated. However, as it was previously written, in the case of the CD that is classified as a POP, no significant degradation was observed. Its half-life is expected to be 10 years and it was estimated that more than 6 centuries will be necessary to degrade the totality of CD from Guadeloupe soils [START_REF] Cabidoche | Stockage dans les sols à charges variables et dissipation dans les eaux de zoocides organochlorés autrefois appliqués en bananeraies aux Antilles : relation avec les systèmes de culture[END_REF]. However, these estimations should be temperate, as advances in scientific research in the upcoming years could decrease the required time, via bioremediation for example. This conservation of CD in the environment is explained by its physical and chemical properties. Nonetheless, the mechanisms of transfer of CD in all the parts of the environment is highly dependent on the nature of the soil.

CD is poorly soluble in water, it exhibits a very low volatility and is stable up to its sublimation point (350°C), making it difficult to eliminate via incineration (>1,000°C are required).

Moreover, CD has a high affinity for organic matter, explaining that sediments serve as vectors of contamination of river and marine environments (EPA, 1978;[START_REF] Lunsford | Uptake of Kepone® by the estuarine bivalve Rangia cuneata, during the dredging of contaminated sediments in the James river, Virginia[END_REF]. This characteristic of CD is particularly deleterious in the French West Indies, as concentration of organic carbon in soil is one of the highest in the world. Besides, the tropical climate of the French West Indies characterized by the occurrence of cyclones which causes a regular mixing of aquatic environments results in the re-suspension of CD in water.

Plant uptake of CD from the soil via the roots and volatilization from the leaves is negligible [START_REF] Topp | Factors affecting the uptake of 14C-labeled organic chemicals by plants from soil[END_REF]. Even if this does not constitute an efficient route of depollution, it suggests that it is unlikely that plants can bioaccumulate really high levels of CD. Moreover, CD does not appear to be subjected to photolysis or hydrolysis [START_REF] Ineris | INERIS : Valeur guide environnementale; Chlordecone -n°CAS : 143-50-0 (Institut national de l'environnement industriel et des risques). International Human Genome Sequencing Consortium[END_REF].

Some biotechnology techniques were envisaged to enhance the elimination of CD from the environment and therefore decrease human exposure. However, even if some techniques developed in laboratories are promising, none of them seems to be directly applicable on polluted territories. For example, waste water from production plant can be treated with UV light, hydrogen and sodium hydroxide to dehalogenate CD [START_REF] Reimers | Use of applied fields in biological treatment of toxic substances, wastewater, and sludges[END_REF]. Bioremediation was also envisaged. In 1981, it was reported that a fungi of genus Aspergillus was able to degrade CD into three metabolites (chlordecone-alcohol, a dechlorinated form and two other unidentified compounds) [START_REF] Wagner | Isolation of fungi from organochlorine pesticide waste[END_REF]. More recently, several bacteria strains from Citrobacter and Desulfobrio genus, were reported to be able to metabolize CD [START_REF] Chaussonnerie | Microbial Degradation of a Recalcitrant Pesticide: Chlordecone[END_REF][START_REF] Chevallier | Natural Chlordecone Degradation Revealed by Numerous Transformation Products Characterized in Key French West Indies Environmental Compartments[END_REF][START_REF] Della-Negra | Transformation of the recalcitrant pesticide chlordecone by Desulfovibrio sp.86 with a switch from ring-opening dechlorination to reductive sulfidation activity[END_REF]. These results are promising for the use of bacterial bioremediation in the upcoming years in the fight against CD contamination.

Human exposure to chlordecone

Taking into account that CD use has been ceased in 1993, the main source of exposure of human populations are through the consumption of contaminated water or food.

CD has been banned worldwide for several years, therefore the potential exposure of the general population is relatively small and should continue to diminish over time. Nonetheless, in the French West Indies, CD was massively used during two decades leading to an important accumulation in the environment, enhanced by the organic-rich nature of the soils.

As discussed previously, CD is not well degraded.

The contamination level of plants, including vegetables that form human diet, is directly dependent on the contamination of the soil [START_REF] Achard | Contamination des racines et tubercules cultivés sur sol pollué par la chlordécone aux Antilles[END_REF][START_REF] Cabidoche | Pollution durable des sols par la chlordécone aux Antilles : comment la gérer ?[END_REF][START_REF] Woignier | Chlordecone retention in the fractal structure of volcanic clay[END_REF]. It has been reported that contamination of plants by CD affects mostly underground storage organs, such as roots or tubers. Therefore, it is conceivable that different crops are contaminated unequally. Root-vegetables, such as carrots, sweet potato or yam are much more contaminated by CD compared to vegetables growing on the ground (e.g., zucchini, melon) or as trees (e.g., pineapple, banana) [START_REF] Clostre | Transfert de la chlordécone du sol vers les produits cultivés[END_REF].

In addition, it has been reported that CD can bioaccumulate in aquatic and terrestrial organisms, both through their alimentation and their living environment. Bioaccumulation is defined as the process of absorption and accumulation of a chemical compound within the tissues. For example, both fishes and crustaceans living in freshwater were reported to be contaminated by CD, with the latest displaying higher levels of CD [START_REF] Coat | Contamination of some aquatic species with the organochlorine pesticide chlordecone in Martinique[END_REF]Rocle et 152 al., 2009). These levels are regularly above the maximum residue limit (MRL), fixed at 0.020mg/kg for any animal foodstuff since 2019.

The levels of CD measured in the blood of people living in Guadeloupe or Martinique were considerably lower (100 to 1,000 times) than those observed in Hopewell's workers [START_REF] Kadhel | Chlordecone exposure, length of gestation, and risk of preterm birth[END_REF]. As a consequence, the health issues, mostly neurological troubles, identified in the Hopewell's workers are unlikely to occur in the population of the French West Indies.

However, the chronic nature of their exposure to CD could lead to different but serious health problems.

Under physiological conditions, hormones are known to function at concentrations that are extremely low (as low as picomolar). The capacity of CD to interfere with the estrogenic signaling suggest that chronic exposure could lead to deleterious effects, specifically in fragile subpopulations, such as pregnant women, young children or teenagers. As a consequence, CD appears to be a high priority public health issue, especially when it has been evaluated that more than 90% of the population living in Martinique and Guadeloupe has detectable levels of CD (above 0.02 µg/L) in their body [START_REF] Dereumeaux | Imprégnation de la population antillaise par la chlordécone et certains composés organochlorés en 2013-2014 : Étude Kannari[END_REF].

Moreover, it was not observed any troubles in the reproduction for the exposed workers. For a few workers, testicular biopsies were performed. This analysis confirmed that several cell types were reduced in the testis of the exposed workers (spermatids, spermatocytes and spermatozoa). However, stem cells, spermatogonia, were not affected, suggesting that the effects could be reversed.

Mammalian studies indicate that testicular atrophy can occur at low doses of CD in the diet for 3 months [START_REF] Larson | Acute, subchronic, and chronic toxicity of chlordecone[END_REF].

Toxic effects on reproduction were reported in both males and females in animal studies. It was shown that exposure to low doses (0.625 and 1.25 mg/kg/day) of CD induced a decrease in spermatozoa numbers in rats. On the contrary, exposure to a higher dose (10mg/kg/day) led to both increased sperm count and relative testes weight (EPA, 1978). Intermediate-duration exposures of mice to CD (130 days and 6 months) resulted in a decrease in litter number, as well as litter size [START_REF] Good | Effects of insecticides on reproduction in the laboratory mouse. I. Kepone[END_REF][START_REF] Huber | Some physiological effects of the insecticide Kepone in the laboratory mouse[END_REF]. However, no similar effect was reported in the litters of CD-exposed rats [START_REF] Linder | Spermotoxicity and tissue accumulation of chlordecone (Kepone) in male rats[END_REF]. Nonetheless, a diminution of sperm motility and viability was still observed, as well as a decrease in seminal vesicle and prostate relative weights. Moreover, testicular atrophy was observed in adolescent rats exposed to higher dose of CD (2.3mg/kg/day for 90 days) [START_REF] Larson | Acute, subchronic, and chronic toxicity of chlordecone[END_REF].

Toxicity to other tissues

No effect on the skin was observed in animal studies including rabbits, rats or dogs, neither by oral consumption through food nor following dermal application [START_REF] Larson | Acute, subchronic, and chronic toxicity of chlordecone[END_REF].

Similarly, concerning ocular effects, no effects were reported on the offspring of mice and rats which were exposed orally to CD [START_REF] Chernoff | Fetotoxicity and cataractogenicity of mirex in rats and mice with notes on kepone[END_REF].

Development effects of chlordecone

Limited data from human studies provide evidence that blood levels of CD could be associated with developmental effects. For example, it has been shown that prenatal exposure to CD was associated with reduced visual recognition memory and an increased risk of nonoptimal fine motor development, at the age of 7-month-old [START_REF] Dallaire | Cognitive, visual, and motor development of 7-month-old Guadeloupean infants exposed to chlordecone[END_REF]. This study was performed in the TIMOUN mother-child cohort, which is part of a longitudinal study implemented in Guadeloupe in order to study the impact of prenatal CD exposure on pregnancy outcome and infant development. In another study, which is a continuation of the work by Dallaire and colleagues, the researchers examined the relation of perinatal CD exposure to early child development, in 18-month-old children. They reported that prenatal exposure to CD, with umbilical cord blood CD concentration above 0.24ng/µL, was associated with poorer fine 155 motor function [START_REF] Boucher | Exposure to an organochlorine pesticide (chlordecone) and development of 18-monthold infants[END_REF]. This association was sex-specific, as the association was only observed in boys.

Other studies performed on the same cohort revealed that perinatal exposure to CD was associated with increased TSH, free tri-iodothyronine (FT3) and free thyroxine (FT4) levels in 3-month-old children in a sex-specific manner [START_REF] Cordier | Perinatal exposure to chlordecone, thyroid hormone status and neurodevelopment in infants: the Timoun cohort study in Guadeloupe (French West Indies)[END_REF]. Besides, it has been reported that higher maternal exposure to CD during pregnancy was associated with shorter gestation, and increased risk of pre-term birth [START_REF] Kadhel | Chlordecone exposure, length of gestation, and risk of preterm birth[END_REF].

Taking into consideration that CD levels in this cohort were 1,000 times lower than those measured among the intoxicated workers of Hopewell, it was suggested that there is an increased sensitivity to the neurotoxic effects of CD during the prenatal period. Taken together, the results of these studies suggest that prenatal exposure to environmental levels of CD is associated with persistent impairment of the fine motor functions during infancy. As illustrated in the Introduction, CD is a toxic molecule whose mechanism of actions remain relatively unclear. As this molecule is no longer used because of its prohibition, it is no longer a major priority for the international scientific community. However, 850,000 inhabitants of the French West Indies are continuously exposed to CD, notably through their diet. Among these populations, certain groups are considered to be more vulnerable, particularly pregnant women. Indeed, environmental exposure during early development can be particularly harmful and could have consequences on health later in an individual's life, this is the concept of DO-HaD (Developmental Origins of Health and Disease).

Thus, we have made two main hypotheses, which were the subject of this thesis. The first hypothesis formulated is that exposure to CD during development could alter the cellular epigenetic landscape and result in deregulation of transcriptomic network and therefore affect tissues on a macroscopic scale, altering their physiological functions. We also speculated that these deleterious effects induced by CD are transmissible by epigenetic mechanisms, known as transgenerational inheritance, to subsequent generations in the absence of new exposure.

Our second hypothesis is that CD is a mutagenic molecule, probably via an indirect genotoxic effect.

The objective of the work performed during my Ph.D. is therefore to test these hypotheses, using the murine model, in order to study the effects of CD on the embryonic reproduction system at the time of exposure, as well as in adult animals that are directly exposed during their development (F1 generation) and their grandchildren in adulthood (F3 generation). The second aspect of this work consists of studying the epigenetic and genetic alterations in human umbilical cord blood, for which the CD levels have been determined.

The results section of this manuscript includes four articles, two of which have been published (testicular and ovarian studies) and two are currently under review. The latter are presented in the form of their initial publication (study of epigenetics in humans) or by including the changes applied following the first round of revision (prostate study).

During my Ph.D., I analyzed different kinds of datasets, obtained from high-throughput sequencing. In particular, I performed analysis of transcriptomic (RNA-seq) and epigenomic (ChIP-seq) data. The path from raw data to interpretable results that allows to obtain biological information is based on bioinformatics work that requires the use of tools developed by the scientific community. In this section, the main steps and tools that are necessary to obtain the results presented in the Results section will be presented. Obviously, our work is largely based on wet lab experiments using molecular biology approaches. These methodologies are detailed in the "Materials and Methods" sections of the articles included in this thesis manuscript and will not be discussed further in this section.

I. RNA-seq analysis

Nowadays, transcriptomics analysis generally use RNA-seq techniques using Illumina technology. This method requires the extraction of total RNA from cells or tissues. The biological samples are first lysed and homogenized in the presence of a highly denaturing buffer containing guanidine thiocyanate. This first step aims to inhibit RNases and thus ensure the purification of intact RNA. This step is followed by an elimination of DNA. The resulting solution containing total RNA is then treated with DNase to ensure that there is no remaining trace of DNA.

The majority of eukaryotic mRNAs have a polyadenylated tail at their 3' end. It is this characteristic that is used to purify mRNAs from total RNAs, through the use of oligo dT magnetic beads.

Another method consists of depleting rRNA from the samples, which makes it possible to retain all of the non-polyadenylated RNAs, in particular the small ncRNAs as well as a large proportion (around 60%) of the lncRNAs.

There are several steps in RNA sequencing library construction protocol (Figure 28):

- The cDNA fragments fixed on the flowcell can then be sequenced by their second end, in the case of so-called paired-end sequencing. Thus, two sequencing reads are obtained for each fragment, facilitating downstream bioinformatics analyses, in particular the mapping or assembly steps, and the identification of the different isoforms of a gene.

Strand-specific sequencing allows to determine the direction of mRNA (i.e., whether it is transcribed from sense or anti-sense strand of the genome). Therefore, it increases the efficiency of the analysis. For example, in the case of genomic locus where two genes overlap in opposite directions, strand-specificity will allow to determine the transcript of origin of the read that is mapped to this locus. Current sequencing technologies produce reads that decrease in quality near its 3' end.

The quality of bases can also be comparatively lower for the first bases of the read (5' end) compared to the average quality of the bases of a read. When these cases are observed, it may be necessary to proceed to the trimming of the reads using a tool such as Sickle. For each read, this tool automatically determines when the quality of the bases drops in order to trim the poor-quality bases. If the reads obtained have a length less than a predefined threshold, then those reads are excluded. In our projects performed during my Ph.D., the quality of our sequencing data was good enough to not use this approach.

B. Mapping of reads on the reference genome

For the species commonly studied in biology, a reference genome or transcriptome is usually available. Otherwise, it is necessary to carry out a de novo assembly of the sequencing reads in order to reconstruct the genome / transcriptome of interest. These methods are generally more demanding in terms of computer resources. Our research having been carried out in mice, we were able to easily use the reference genome mm10 (Mus musculus 10). The mapping step therefore consists of determining the locus of origin of a sequencing read from the reference genome used. In the case of RNA-seq, unlike other NGS techniques, the mapping can lead to alignments containing large gaps, corresponding to the splice junctions. Indeed, the reads come from cDNA themselves resulting from the retrotranscription of spliced mRNA whose introns have been discarded, while the reference genome contains the entire genome, the coding as well as the non-coding regions.

This step allows the detection of new splice junctions as well as the identification of potential new genes. Some reads can be mapped to different regions of the genome if they are from regions of low complexity, repeats, or gene families with multiple paralogous genes.

They are designed by the term "multi-mapped" reads.

There are various bioinformatic approaches to perform the mapping. In the following paragraph I will only focus on the "seed-and-extend" approach since it is the one implemented in the tools that we used during our work. The mapper used is Bowtie2, which uses a FMindex, like other mappers, to quickly and efficiently map reads to the reference genome.

Bowtie is an algorithm based on the Burrows-Wheeler transform (BWT) (Figure 32).

This approach makes it possible to align the complete reads with substrings of characters from the reference genome. This is a major difference from hash-based algorithms that divide reads into multiple seeds, like BLAST for example. These algorithms require significant computational resources, especially RAM. The BWT-based algorithms rely on a certain representation of suffix/prefix trie, called FM-index to find exact matches.

Following the mapping of the reads, several parameters can be evaluated to determine the quality of achievement of this step. For example, the rate of aligned reads constitutes an important indicator of the quality of the sequencing and can reflect the potential biological contaminations. In mammals, an alignment rate of less than 70% is considered insufficient and indicates a problem in the data.

165 When several segments originate from the same read map to non-contiguous regions of the reference genome, the tool considers that the read span an intron. Thereby, it is able to estimate the splice junctions. Command line used to perform this step is provided in Figure 33. The number of reads aligned within a transcript, or a gene, is representative of its abundance in the tissue being studied. This information can therefore be used to measure the levels of gene expression under the various conditions considered. Then, after normalization, it is possible to make comparisons to determine the impact of a treatment, in our case with CD, on the transcriptome.

C. Quantification, normalization and comparison of transcript abundance

The objectives of an RNA-seq experiment can be multiple. This may involve identifying new coding genes, identifying new isoforms or comparing abundances/levels of gene expression between different experimental conditions. During our work, it was the latter case that interested us; we wanted to know whether exposure to CD leads to changes in expression when compared to control samples. Many tools have been specifically developed to answer this kind of questions, such as DESeq, DESeq2 or EdgeR. I will further describe little bit more DESeq2 which is the tool that we used in our research. However, whatever tools are used, it is necessary to provide as input a raw read count (by gene, exon, or transcript). In our projects we used HTSeq (v0.6.1) to perform counting [START_REF] Anders | HTSeq -A Python framework to work with high-throughput sequencing data[END_REF] (Figure 34). There are different sizes of transcripts (from 2,099bp for one of the H3-3A isoform to 281,435bp for TITIN longest isoform, GENCODE v35) and the size of the reads are initially fixed before the project starts (here at 100bp). Intuitively, it is easy to understand that the larger a transcript, the more reads it accumulates. Therefore, it is not possible to directly compare the raw read count within a sample. In addition, there may be technical bias that results from the difference in the number of reads between two sequenced samples. It is therefore necessary to carry out normalization steps in order to overcome the intra-and inter-sample bias. It is from this observation that several metrics, regularly used in the study of the transcriptome, were born: RPKM (Reads Per Kilobase Million), FPKM (Fragments Per Kilobase Million) and TPM (Transcript Per Million).

While calculating the RPKM (or FPKM) the first step is to normalize the read depth, i.e., the total number of reads in the sample (Figure 35). The total number of reads is then divided by a 1,000,000 factor for convenience (it generates numbers easier to handle), which corresponds to the "per million" normalization. Then, the second step is the normalization according to the gene length in kilobase (it is the "per kilobase" normalization). RPKM is used in singleend sequencing, when one read comes from one fragment. On the contrary, FPKM is used in paired-end experiments where fragments are sequenced from both ends, resulting in two reads per fragment. However, the calculation is the same. More recently, another metric called TPM which has the same purpose, i.e. to normalize datasets for depth and gene length, is used. On the contrary to RPKM/FPKM, the two calculation steps are inverted when calculating TPM. It starts with the "per kilobase" normalization and then comes the "per million" one. This results in a major difference between the two metrics. The sum of all the TPM values is the same between different samples, while the sum of all the RPKM/FPKM values is different between every samples. As a result, it makes it easier the inter-sample comparisons using TPM. Finally, these values can be used to plot several kinds of graphs, such as heatmaps, scatter-plots or MA-plots.

As previously mentioned, the tools specially developed to deal with differential expression are taking as input raw read count. They then proceed to their own normalization (Figure 36), that has been shown to be more appropriate than working directly with previous metrics that I presented. In our research we used DESeq2, a R package developed by Michael Love [START_REF] Love | Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2[END_REF].

DESeq2 starts by calculating a scaling factor for each sample. To do so, the algorithm takes into account the depth and the library composition, and for each gene, the raw read count is log-transformed (log base e), which reduce the bias coming from outlier values. Then, DESeq2 makes the average of the log-transformed read count for each gene. If in any sample the original read count for a given gene was 0, then the average will be minus infinity (-Inf) and the gene will be excluded from downstream normalization steps. This allows to take into account for normalization only the genes transcribed in all the experimental conditions, such as housekeeping genes (e.g., this excludes organ-specific genes when comparing transcriptomes between several tissues). The next step aims to extract the average log count from each log read count, which is equivalent to having a ratio between the log read count within a gene in each sample and the average across all the samples. In other words, this step allows to identify the genes that deviate from the average, being expressed at low or high level. In the last step of the normalization performed by DESeq2, median for each sample is calculated and then converted to non-log values, through exponential function. These values are the scaling factors for each sample, that are finally used to normalize the initial raw read counts to obtain the final normalized read counts that can be further processed for differential expression analysis. All the steps described previously are wrapped into a single function of the DESeq2 package named DESeq() (Figure 37). For all the mathematical details of this method, the readers are encouraged to go through the comprehensive manual1 of DESeq2 and the original publication [START_REF] Love | Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2[END_REF].

Finally, the results are extracted with the results() function, that provides a table including log2 fold changes, p-values and adjusted p-values. DESeq2 provides several ways to deal with multiple testing adjustment, such as Holm's, Bonferroni's or Benjamini-Hochberg's methods. In our research, we used the Benjami-Hochberg, also known as FDR (False Discovery Rate), which is less stringent than Bonferonni's method and broadly used by the community of the academic research. To prioritize and identify differentially expressed genes (DEGs), genes are sorted by adjusted p-values and fold change using arbitrary defined thresholds, such as adjusted p-values ≤ 0.05 and fold change ≥ 2.

The reproducibility of the results between technical and biological replicates is assessed using a correlation test or a principal component analysis (PCA), that is performed in R. Correlation matrix or PCA can be plotted natively by R, however DESeq2 provides its own functions to perform a visual validation of the analysis. In our work, we used plotPCA() to generate these figures.

Depending on the annotation used to perform raw read counts, results table generated by DESeq2 can lack official gene symbol, and only provide other kinds of identifier, such as an Ensembl ID. To overcome this situation, it is possible to retrieve the official gene symbol using BioMart database, which is able to map a huge variety of identifiers from different sources.

This tool can be used either online on the Ensembl website 1 or locally via the R package (bi-omaRt 2 ).

After the identification of the DEGs, it is generally interesting to determine what are the main pathways altered between the experimental condition. The functional analysis of groups of co-expressed genes makes it possible to associate transcriptional dynamics with a biological process. Each known gene is annotated with some biological processes, molecular functions or molecular pathways in which its products are involved. This information is available in databases such as Gene Ontology (GO). Another frequently asked question is whether some biological functions are more or less altered compared to what is expected if all the changes were totally random. To answer this question, we performed a GSEA (Gene Set Enrichment Analysis) which is implemented in numerous annotation tools available online, such as Panther, g:profiler, Enrichr, among others.

GSEA relies on an over or under representation tests. This kind of analysis relies on comparison of gene sets. This method is used to identify classes of genes, associated with biological functions that are over-represented in a large set of genes. The method involves three steps: calculation of the enrichment score, estimation of statistical significance of the calculated score and finally the adjustment for multiple tests.

II. ChIP-seq analyses

Chromatin Immunoprecipitation (ChIP) is a powerful method that allows to identify the proteins interacting with the genomic DNA. It is commonly used to identify transcription factors binding or histones modifications via the use of specific antibodies. Followed by high-throughput sequencing (ChIP-seq), the method is used to determine the precise binding sites of the transcription factors, or the loci "covered" by the histone mark of interest. In our research, we focused on H3K4me3.

Typically, we use minimum 2 biological replicates per group as recommended by EN-CODE and minimum 5 ng of material. As for RNA-seq, library was performed in several steps: end repair, addition of adapters, PCR amplification with index primers and finally sequencing.

We used single end mode and multiplexed 6 samples in one lane. Typically, we have around 300 million read per lane on HiSeq4000 machine, conferring around 50 million reads per samples.

The two initial steps of the analysis are the same as those described for RNA-seq analysis: quality control of the sequencing reads and their mapping to the reference genome. Then, specific steps for this method should be performed: peak calling, peak strength quantification and comparison between experimental conditions. Once mapped to the reference genome (Figure 38), reads accumulate to discrete regions to form a characteristic signal that has a shape of the peak. These regions that accumulate reads are therefore called "peaks" and correspond, in our research, to regions covered by H3K4me3. The purpose of the peak calling step is to identify these peaks. To do so, one of the bioinformatic strategy is to parse the genome to look for regions enriched in sequencing reads compared to an input sample that reflect the background noise. This sample is prepared during ChIP, with no antibody added, resulting in non-specific precipitation of the chromatin. In our work, peak calling was performed using MACS2 (v2.1.2), whose principle is summarized in Figure 39. A. Peak calling MACS uses both position and orientation information to fine-tune peak detection. As previously written, the tool can also use an input sample to increase the specificity of the detected signal, and thus discard some regions with artificially high signals.

Figure 40. Process performed by MACS2 to adjust reads location and assess original fragment position. Adapted from [START_REF] Wilbanks | Evaluation of algorithm performance in ChIP-seq peak detection[END_REF].

In order to estimate the size of the region covered by the histone mark of interest, MACS2 first detects the enriched regions via the use of a sliding window with a width of approximately twice the size of chromatin fragments (bandwidth parameter). From the detected regions showing 10 to 30-fold enrichment (adjustable via the mfold parameter) from the randomly distributed reads, MACS2 chooses randomly 1000 of them. For each region, the spanning reads are separated according to their orientation relative to the reference genome (sense or antisense), leading to the identification of two peaks. Then, the algorithm calculates the distance between the summit of the two peaks, in order to estimate the real size of the region, noted d. Finally, MACS2 shifts all reads from d/2 to their 3' end so that the reads are "correctly replaced" under the region of interest (Figure 40). For histone marks, such as H3K4me3, that span broader regions than transcription binding sites, sequencing reads produce less defined bimodal pattern, as the two peaks can overlap.

Following these pre-processing steps, the algorithm slides a 2d window through the genome to detect the regions enriched compared to the background noise, in order to determine candidate peaks. The distribution of reads along the genome can be modeled by a

Poisson distribution, dependent on the λBG parameter, which defines the expected number of reads in the given window. This parameter has the advantage of capturing both the mean and the variance of the distribution.

Many factors can influence the reads distribution within these regions (local chromatin structure, DNA amplification and sequencing bias, genome copy number variation). Therefore, MACS2 does not use a λ for the whole genome, but instead calculates a λlocal for each candidate peak from the input, i.e., the non-specific background signal. More precisely, the value of λlocal is defined as the maximum value among λBG, λ1k, λ5k, λ10k, where λ1k, λ5k and λ10k are the estimated λ for windows of 1, 5 and 10kb, centered on the position of the peak in the input.

This λlocal parameter captures the influence of local biases and thus eliminates potential false positives. In order to avoid introducing bias related to the sequencing depth, MACS2 linearly normalizes the number of reads so that the number of reads in the input and in the ChIP are comparable. This step is performed after eliminating redundant reads, i.e. those having the same orientation and exactly the same coordinates.

The algorithm finally calculates a p-value for each candidate peak. Candidate peaks with a p-value less than 1.10 -5 (or defined by the pvalue parameter) are kept and the ratio between the number of reads in the ChIP sample and the λlocal is reported as the "fold enrichment". For each peak identified, a statistical test is run. Considering that several tens of thousands of peaks can be identified, depending on the tissue, correction for multiple tests should be applied. To overcome this situation, MACS2 calculates a q-value, which is a corrected pvalue after correction with the Benjamini-Hochberg method.

B. Peak strength quantification and normalization

Once the peaks are identified, it is necessary to define their strength, based on their breadth and height. Determining the strength of a peak therefore consist of calculating its integral, i.e., to quantify the area under the curve defined by the peak. To carry out this step we first converted the .bam files containing the mapping data, into .bedgraph files. These are used to represent continuous-valued data in track format. In these files, each genomic position is associated with its sequencing depth. In order to reduce the storage space for these large files, uncovered regions with a depth of 0 are excluded. In addition, adjacent regions with equal depth are grouped into larger regions. This conversion is done using the bedtools suite (v.2.25.0) (Figure 41). As these files are used to perform peak strength comparison, the signal should be comparable between replicates. To avoid bias related to sequencing depth, we normalized the signal by a scale factor that scale down each sample to the level of the one having the lowest depth (Figure 42). These normalized files are finally used to quantify peak strength for each sample using the script presented in Figure 43.

C. Differential peak identification

Following quantification of the peaks, we wanted to identify those peaks that show a difference in intensity between the experimental conditions. To do this, we performed several filtration steps before testing the statistical significance of the observed differences. First, we discarded all the peaks with relatively low intensity. For each peak, the minimum intensities for each experimental condition were compared. Among the two values (exposure or not to CD), if the maximum value is less than the defined threshold (median intensity of all the peaks), then the peak is considered too low and therefore excluded.

Then, we calculated the average intensities for each condition and determined the foldchange between our experimental conditions. The threshold value used for filtration was not set for all our projects. However, the commonly used thresholds were a fold-change greater than or equal to 1.5 or 2 times. All the peaks retained following these first two filtration steps are then tested using a moderate t-test implemented in the R Limma package (v3.38.3). This R package, based on an Empirical Bayes method, was specifically designed to work with a limited number of replicates [START_REF] Phipson | ROBUST HYPERPARAMETER ESTIMA-TION PROTECTS AGAINST HYPERVARIABLE GENES AND IMPROVES POWER TO DETECT DIFFERENTIAL EXPRES-SION[END_REF]. P-values were corrected for multiple testing by the Benjamini-Hochberg method, which is directly implemented in the package. The R function used to perform this analysis is provided in Figure 44. Table 8. Online tools to characterize the genomic regions or list of genes.

III. Exome analysis

Exome sequencing was performed on the blood of 24 boys who lived in Guadeloupe.

Exome sequencing was also performed on the chromosome X of 15 mothers. Comparison of X chromosome sequences from boys and their mothers allows to identify which variant can be de novo in the children. Since the children are only boys, their X chromosome is maternally inherited, while chromosome Y is transmitted by their father.

Exome sequencing results were in fastq files, just as data from other sequencing methods. The reads are paired-end with a length of 100bp. Initial steps of quality check and mapping are similar to those performed for RNA-seq and ChIP-seq analysis. Analysis are performed according to the GATK (Genome Analysis ToolKit) best practices.

A. Mapping and preprocessing of bam files

The mapping of the reads to the reference genome (Homo sapiens GRCh38) was performed using BWA (v0.7.5a) [START_REF] Li | Fast and accurate long-read alignment with Burrows-Wheeler transform[END_REF], which is based on the same algorithm as Bowtie, the BWT. Results of the alignment are stored within human readable SAM files. The command line used is provided in Figure 47. In order to reduce the memory prints on the storage location, these files are converted into binary BAM files using samtools [START_REF] Li | The Sequence Alignment/Map format and SAMtools[END_REF]. In order to detect the differences between the genome of the individuals from TIMOUN cohort and the reference genome, a variant calling step was performed. Variant calling allows to detect the genetic variations such as the SNPs and the short indels. Before variant calling, bam files resulting from the mapping step are further preprocessed using Picard (Figure 48).

This step aims to add unique identifiers to each sample before to call the variants from the set of all samples. Moreover, this step allows to identify duplicate reads without excluding them, before sorting the alignment results by genomic coordinates. The algorithms used for variant calling rely heavily on the quality score of each base within the reads. Indeed, the higher a base has a quality score, the more likely that the variation detected is really of biological origin rather than a technical artefact. However, the scores produced by the sequencers are subject to various systematic errors (e.g., functioning of the chemical reaction or calibration of the sequencer) which lead to underestimated, or more frequently overestimated, quality scores.

In order to take this bias into account, we used one of GATK's tools called Base Quality Score Recalibrator (BQSR) (Figure 49). The algorithm uses machine learning to empirically model the errors and adjust the quality scores accordingly. The algorithm uses different covariables in order to build the model, in particular the context of the sequence (bases upstream For each individual in the cohort, a gVCF file is generated. They can be combined into a multi-sample VCF using the CombineGVCFs tool. It is then necessary to convert the obtained gVCF file into a VCF file. The gVCF contains a record for all sites, whether there is a variant call or not, unlike the VCF which only contains the sites for which there was a variant call. As a result, VCF files take much less disk space, and are the ones used in down-stream analysis.

The conversion is done by GenotypeGVCFs (Figure 50).

D. Variant filtrations

The variant calling step detected a very large set of variants (around 4 million). It is then necessary to carry out various filtration steps in order to keep only the variants of interest.

These filtration steps are carried out on the quality of the data on one hand and on the annotation of the variants on the other hand.

Variant quality score recalibration

Filtration of variants on data quality has traditionally relied on examining various metrics such as total number of reads covering the variant (depth), number of reads covering each allele, proportion of reads oriented to the sense strand compared to those coming from the antisense strand, and other parameters. For each of these parameters it is necessary to set a defined threshold, and if one of the fields does not pass the threshold then the variant is discarded from the analysis. This approach has the drawback of looking at each of these variables individually. This results in the elimination of true positives if at least one of the parameters tested has a value that does not exceed the defined threshold. On the contrary, this method results in the conservation of false positives if the user adjusts the thresholds in order to maintain the true positives mentioned above.

In order to overcome this limitation, it is possible to use another tool from GATK, the Variant Quality Score Recalibrator (VQSR) (Figure 51). This method uses machine learning algorithms to determine the annotation profile of good variants versus bad variants, taking into account several parameters simultaneously. In order to build the model, a dataset of variants for which the confidence level is very high should be used. In our work, we used as a training set the variants contained in the OMNI, 1,000 Genomes and HapMap projects, as suggested by the developers of the GATK. The program looks at the profile of these trusted variants in our dataset, and determines the rules that allow us to characterize the good variants. These rules are then applied to all the variants called, and assigns each of them a score, the VQSLOD (variant quality score log-odds) describing its probability according to all the parameters taken into account initially.

Finally, a threshold value is defined to filter the variants on the VQSLOD. The variants of the training set are classified according to their VQSLOD. To define the threshold value, it is necessary to specify a tranche sensitivity threshold in percentage, for example 99.9%. The program then looks at the VQSLOD value above which 99.9% of the trusted dataset variants are included. This value is then used as a threshold to filter out the variants. The VQSLOD therefore makes it possible to adjust as precisely as possible, the sensitivity, by trying to keep all the real variants, and the specificity, by limiting the number of false positives remaining after filtration.

This step of VQSR has to be performed twice in total, as SNPs and indels cannot be recalibrated the same way in a one-step process.

Variant annotation using VEP

The next step in the analysis is to annotate the high-quality variants that we detected during the variant calling step. This annotation consists of adding a lot of information relating to the variants, such as the gene affected by the variant, its effect (synonymous, nonsense, missense, frameshift, etc.) or even its frequency in the general population or in some superpopulations. By using various databases, such as ClinVar or COSMIC (Catalog of Somatic Mutations in Cancer), it is possible to add information related to the impact of these variants and its potential implication in pathologies.

In order to carry out this annotation step, we used the VEP (Variant Effect Predictor) v99 tool developed as a part of the EMBL-EBI Ensembl project [START_REF] Mclaren | The Ensembl Variant Effect Predictor[END_REF], which uses the dbSNP and COSMIC databases to determine if the variants have previously been identified (Figure 52).

Following annotation by VEP we performed some filtrations in order to prioritize the variants detected and thus restrict our investigations to a smaller list of variants. From the complete exome of boys in the TIMOUN cohort, we wanted to identify potentially uninherited variants (i.e., de novo variants) that could have resulted from exposure to CD. To do so, we therefore filtered the variants commonly found in the general population, i.e., the variants whose alternative allele is found in more than 0.1% of the population. The frequencies used for this filtration come from the 1000 Genomes and gnomAD projects.

Then, we filtered the variants based on the prediction of their effects. To perform this step, VEP uses other tools, including SIFT and PolyPhen-2. SIFT predicts whether an amino acid substitution is likely to affect protein function based on sequence homology and the physico-chemical similarity between the alternate amino acids. The data provided for each amino acid is a score and a qualitative prediction, of whether a change is tolerated or deleterious.

PolyPhen-2 predicts the effect of an amino acid substitution on the structure and function of a protein using sequence homology, tridimensional structure, and other information from several tools and databases. As SIFT, for each amino acid substitution, PolyPhen-2 provides both a qualitative prediction such as "probably damaging", "possibly damaging", "benign" or "unknown" and a score. The score represents the probability that a substitution is damaging. For our filtration, we only kept the variants predicted to be damaging as well as the variants leading to the appearance of a stop codon, the loss of a start codon or a shift in the reading frame.

For each type of effect (start loss, stop gain, frameshift), we identified all of the affected genes and looked whether certain pathways or biological functions were over-represented. For this we used the enrichR tool and the various databases that it implements.

This approach that aimed at determining the variants which appeared de novo by filtrations proves to be limited. Indeed, nothing prevents a variant that is rare in the population, or even still unknown, from appearing in one of the child's ancestors, and then being transmitted via the germ line. The children studied are all boys, who theoretically have a single copy of the X chromosome, the second sex chromosome being the Y inherited from father. Therefore, the single X chromosome is necessarily inherited from the mother. Thus, the comparison of the X chromosome variants of the mother and her son allows more precise detection of the de novo variants that could potentially be attributed to CD exposure. The variants considered de novo by this approach are then annotated with VEP. The second chapter is dedicated to our work on the transgenerational effects induced in the prostate of mice exposed during development. This study is a continuation of the previous work described above. The work was carried out in somatic prostate tissue. The results will be presented in the form of an article that is submitted to the journal Environment International, and they include the changes made according to reviewers' comments and suggestions.

At the time of writing this thesis manuscript, we are carrying out the second round of revision.

The third chapter will show the effects of exposure to CD during development in the female lineage, investigating epigenetic changes in the ovary. Unlike the work in males, our investigations focus only on mice directly exposed to CD (i.e., F1 generation), and we did not continue our research on subsequent generations. The results of this chapter will be presented in the form of the article published in the journal Epigenetics and Chromatin in May 2019.

In the fourth chapter, the results concerning the Guadeloupean TIMOUN cohort will be presented. The work focuses mainly on epigenetic alterations in the umbilical cord blood of boys exposed to CD during pregnancy. This work is a continuation of the studies carried out in murine model. For this chapter, the results will be presented in the form of an article submitted to the Life Science Alliance journal in October 2020. The article is currently under review.

Finally, in the fifth and last chapter, we present the results concerning the mutational properties of CD, based on the umbilical cord blood samples from the TIMOUN cohort, as well as the results of the analysis of peripheral blood from their mothers. The study is still not accomplished and some more analysis and experiments will be necessary in order to provide a comprehensive overview of the mutational properties of CD in humans. Results are provided as an outline of the manuscript, and eventually they will be expanded before its submission to a peer-reviewed journal.

B. The low frequency mutations detected in exposed individuals

To determine the possible somatic mutations, we assumed that the mutations which have very low frequency in the general population could arise due to somatic mutagenesis.

From all the detected variants, we kept for analysis the ones which have a frequency below 0.01% in human population (Figure 53). As a reference database of the populations, we used GnomAD, NHLBI Exome Sequencing Project (ESP) and 1,000 Genomes population database.

To get insight into the potential impact of CD on protein functions, we predicted the potential damage of the variants by using Polyphen2 or SIFT tools. SIFT predicts the function of the alternative protein variants based on sequence homology and functional properties of amino acids. We performed functional annotation of the detected damaging alleles; the results are listed in Table 9. We found that the mutated genes code for proteins that are implicated in important liver functions, transport and metabolism functions. Some mutations were detected within the genes that were found to be aberrantly expressed in adenocarcinoma, including FXR1, CREB1, CEACAM7, PTGES3 and CAMP.

Table 9. Main functions of genes affected by potentially deleterious rare variants in children exposed to high level of CD.

Table 10. Recurrent genes affected by de novo variants located on X chromosome.

C. X chromosome variants

In the TIMOUN cohort, the blood samples of mothers were available. To better understand the impact of CD on human mutagenesis, we sequenced the coding regions of the X chromosomes of mothers using custom capture kit from Agilent. The captured DNA was sequenced and analyzed similar to whole-exome sequencing data. The X chromosome is unique in males, so all mutations which were not detected in mothers are likely generated de novo during gestational exposure to CD. After filtration of neutral mutations, we performed the functional annotation of the variants with potential damaging effects on protein functions. In total,

we detected 15,306 potential damaging mutations in X chromosome (Figure 54). To better understand the mechanism of action of CD on the genome, we searched for genes that accumulated variants in several children. Our analyses revealed that several genes were affected by de novo mutations in more than 10 individuals. Further investigation showed that the genes related to signaling, organogenesis, transport molecules and metabolic processes were frequently mutated following CD exposure (Table 10).

E. Large structural variants

To reveal whether exposure to CD could induce large structural variants, we performed analysis based on coverage using cn.MOPS (Copy Number estimation by a Mixture Of Pois-sonS) [START_REF] Klambauer | MOPS: mixture of Poissons for discovering copy number variations in next-generation sequencing data with a low false discovery rate[END_REF]. This method has limited power due to availability of short reads. However, it can reveal some copy number alteration variants in the coding regions.

Using this approach, we detected ~300 variants compared to the reference genome. For example, we detected a recurrent deletion of GSTM1 (glutathione S-transferase mu 1). This null deletion variant was detected in 11 out of the 24 children. We confirmed the deletion by qPCR experiment. The copy number variation detected in GSTM1 is a germline variant and the null genotype is associated with risk of cancers [START_REF] Liu | GSTM1 null genotype is a risk factor for laryngeal cancer[END_REF][START_REF] Zhang | GSTM1 null genotype and gastric cancer risk in the Chinese population: an updated meta-analysis and review[END_REF]. However, an analysis performed on the Caribbean population of African descent of Guadeloupe revealed that individuals that carry GSTM1 had higher risk to develop prostate cancer than men with the homozygous GSTM1 deletion [START_REF] Emeville | Copy number variation of GSTT1 and GSTM1 and the risk of prostate cancer in a Caribbean population of African descent[END_REF]. We asked whether the absence of GSTM1 increase rate of de novo mutations, and we identified that GSTM1 -/-children have on average 2.4 times more de novo variants on X chromosome compared to GSTM1 +/+ children (Figure 56).

F. Discussion

Mutagenesis promoted by CD

We found that CD exposure affects genes which are associated with metabolism of CD and some of them are targets of CD as reported in other studies [START_REF] Gely-Pernot | Gestational exposure to chlordecone promotes transgenerational changes in the murine reproductive system of males[END_REF][START_REF] Lee | Chlordecone, a mixed pregnane X receptor (PXR) and estrogen receptor alpha (ERα) agonist, alters cholesterol homeostasis and lipoprotein metabolism in C57BL/6 mice[END_REF]. Indeed, out of the 941 genes with altered gene expression following CD exposure (listed in the Comparative Toxicogenomics Database (https://ctdbase.org/), 581 were found to be mutated in CD-exposed TIMOUN cohort. This suggests that exposure to CD promotes not only alteration in gene expression but also to the generation of mutations.

The major mechanism of DNA repair in actively transcribed genes is transcription coupled with NER. Normally this is a high-fidelity mechanism, however under toxic conditions this mechanism could be error-prone. To reveal the potential role of NER on mutagenesis in CDexposed humans, we extracted information about histone H3K4me3 occupancy that was previously performed in our lab for the genes that are known to encode for the NER pathway proteins. The gene ontology AMIGO predicted that 112 genes are involved in NER pathway.

Our analyses showed that genes which are known to be associated with NER have decreased H3K4me3 occupancy in CD-exposed humans including, BRCA2, COMMD1, COPS4, COPS5, CUL4B, ISY1, POLR2K, RFC3, RNF11, RPS27A, and TP53. Among them, POLR2K was the most downregulated gene (FC>2) in the TIMOUN ChIP-seq H3K4me3 data. This gene encodes one subunit of RNA pol II, the enzyme responsible for synthesizing mRNA.

In our ChIP-seq data, we detected that large numbers of genes which encodes the proteins essential for HR had decreased H3K4me3 occupancy. The reduced histone H3K4me3 occupancy was detected at ATM, BRCA1/2, RAD51AP1, RAD51B, SFR1, HELQ, KDM4D, NABP1, UBE2N and ZFYVE26. Our ChIP-seq data suggests that the genes essential for DNA repair processes are altered via HR or NER, as the levels of H3K4me3 and mRNA expression were correlated in CD-exposed Ke-37 cells (Legoff et al., under review).

Thus, we propose that perturbation in gene expression of DNA repair system could play a critical role in the occurrence of mutations in CD exposed humans.

Mutation Signatures promoted by CD

Notably, we detected that CD exposure promotes mutation with the predominant C>T and T>C transitions. These are the dominant changes in signature 1 and 5, respectively. The mutational process underlying signature 1 is likely to be the deamination of 5-methylcytosine at CpG dinucleotides leading to C>T mismatches which are not repaired prior to DNA replication [START_REF] Kelly | Regulation of chromosome replication[END_REF]. Very often, deamination of cytosine leads to formation of uracil.

The enzyme called Uracil DNA glycosylase (UNG) excises Uracil in both ssDNA and dsDNA, resulting in an abasic site. In dsDNA, these sites are replaced with Cytosines as a result of copying of Guanines in the complementary strand during repair by the BER pathway. However, Cytosine deamination in ssDNA is difficult to repair as the complementary strand is absent.

Thus, conversion of Cytosine to Thymine mutations could be due to imperfections in BER repair.

The mutational process underlying signature 5 is not well understood. The T>C mutations exhibit transcriptional strand bias, potentially indicating that some of these mutations arise from adducts that are subjected to transcription coupled repair [START_REF] Fousteri | Transcription-coupled nucleotide excision repair in mammalian cells: molecular mechanisms and biological effects[END_REF].

Further work is required to reveal the role of the DNA repair system in CD-induced mutagenesis. The observation of genes recurrently mutated in individuals exposed to CD could be an interesting starting point for further investigations dedicated to the identification of initial events leading to CD-induced mutagenesis. To conclude, our study shows that in utero exposure to CD promote de novo mutations in genes with important functions.

Overall synthesis of discussion from all studies

Proposed mechanism of transgenerational inheritance

In transgenerational studies, we found that the genes regulating pluripotency preserve the epigenetic information in F3. This suggests that genomic regions in the vicinity of master regulator genes avoid erasure during developmental reprograming. Most of tissue-specific epigenetic marks are not preserved in the next generation as gametes are the only cells which give rise to a new organism. A recent paper suggested that there is a set of genes named germline reprogramming responsive (GRR) genes, that avoid reprograming. Some of them encode proteins implicated in meiosis [START_REF] Hill | Epigenetic reprogramming enables the transition from primordial germ cell to gonocyte[END_REF]. The epigenetic information at GRR is preserved by several mechanisms including DNA methylation, transcription factors binding to the genes' promoter and also, by the addition of histone modification marks. According to the studies performed in mammalian species, sperm contains a limited number of regions which preserve histones, while most of the histones are replaced by protamines involved in the compaction of the genome.

In germ cells derived from the animals exposed to CD, we detected that alterations in H3K4me3 mark were predominantly located in the vicinity of the genes that are targets of ZFP57, a transcription repressor that regulates pluripotency by suppressing the differentiation program. Thus, ZFP57 was directly affected by CD and could be one of the major mediators of transgenerational inheritance. The exact underlying mechanisms are not known, but it is conceivable that, with its major partner TRIM28, they could regulate the establishment of H3K9me3, which has opposite effects compared to H3K4me3 mark. This gives a new opportunity to further study the role of H3K9me3 in transgenerational inheritance.

Notably, in our prostate study, we detected an alteration in the cluster of Hoxa genes, and in the sperm of F1 and F3 mice. This suggests that some other developmental genes could avoid reprograming and could therefore contribute to abnormal phenotypes in somatic tissues. Thus, developmental exposure to CD could have a dramatic consequence during late adulthood life since the epigenetic memory lasts throughout the life and is even transmitted to next generations.

Correlation between gene expression and epigenetic marks

In our studies, by using in vitro models, we showed that a strong correlation between gene expression and epigenetic marks. However, in animal studies, where we assessed the correlation between RNA expression and H3K4me3 distribution alteration at the whole-genome level, we observed a less marked association. It is suggested that the gene expression and epigenetic marks could correlate at certain developmental stages. Then, later in the individual's life, the epigenetic marks could stay as a memory of the ancestral gene activation, even in the absence of gene expression. For example, we detected a decrease in Prdm1

H3K4me3 promoter occupancy in adult testis, but the gene was not expressed at the adult stage. However, we detected a decrease in Prdm1 expression during early development. This observation suggests that some changes occur during the embryonic development and the information is preserved in adult organs even if the gene is not expressed.

Damaging effects of CD on meiosis

Our work revealed that direct developmental exposure to CD leads to impairment of meiosis in both male and female mice, which eventually leads to a reduction in viable reproductive cells, i.e., both spermatogonia and spermatozoids in males, and oocytes in females.

This phenomenon could result from the improper repair of double-strand breaks during meiosis. Formation and repair of DSBs are also regulated via the orchestrated actions of chromatin factors and DNA repair proteins. The epigenetic alterations could lead to impaired segregation during meiosis. Besides that, single-stranded DNA which is formed during meiosis is very vulnerable. Even if the mice are exposed during development, they can still have CD accumulation in their body after cease of the exposure, as CD has a long half-life in the body. Even though the meiotic genes are known to be expressed in males during adulthood, some of them are GRR genes, and their perturbation could be due to embryonic exposure.

To which extent does the transgenerational inheritance last?

Our analysis of the sperm from F3 generation mice showed that epigenetic changes are still detectable for a large number of Hoxa genes as well as other genes, suggesting that the effects could last until the 4 th generation. Further work is required to address whether the effects could still be detected in the 4 th generation. With each passing generation, the induced changes are progressively reverted to the normal state and the effects induced by the ancestral CD exposure are less profound in F3 compared to F1.

Correlations between mouse and human studies

Since large population of humans are still exposed to CD, we asked whether the effects observed in mice could be detected in humans. As being said in the Introduction, the availability of human material restricts our study to blood cells and to human cell lines. We used umbilical cord blood from the TIMOUN mother-child cohort from Guadeloupe for which the CD levels were already available. We developed a ChIP technique that allowed us to work with very small quantities of blood. By using this method combined with ChIP-seq approach, we detected around 1,000 regions that were altered between the individuals exposed to high levels of CD compared to those exposed to a lower level. We asked whether some genes, located in the vicinity of the affected regions, were common in mice and humans exposed to CD. We compared the gene sets extracted from the ChIP-seq data, that we identified in our F1 murine testis and human umbilical cord blood studies. We found that a large number of genes overlaps in these two studies. The summary is presented in Table 11.

The common genes that were identified were involved in important functions, including chromosome organization, transcription factor regulation, signaling and organogenesis. We believe that the process of metabolic transformation of CD and its endocrine-disrupting capacity that take place in the body leads to changes in the occupancy of H3K4me3 at these genes.

Considering that, in our previous work, we observed that CD can induce 8-oxo-G and could induce DNA damage, we concluded that alteration in DNA repair genes could lead to the appearance of DNA mutation. The genomic instability in humans could be also mediated via the alterations in retrotransposon activity in the exposed samples. Our analysis of exome data confirmed that CD has a stronger genotoxic effect than previously thought, and it induces a large number of de novo mutations in the human genome. The detection of recurrent mutations in expressed genes suggest that a dysfunction in the NER mechanism could contribute to the mutagenesis. Besides, the appearance of de novo large structural variants suggests that errors during DNA repair via HR could be also responsible for the generation of the large structural variants.

Thus, exposure to CD leads to epigenetic and genetic alterations in mice and humans and future studies are required to investigate the role of identified genes in phenotypic manifestations.

From the perspective viewpoint, it will be necessary to reveal the possible correlations between mutation position and epigenetics features such as DNA sensitive sites, H3K36me3, H3K4me3 and H3K27ac marks. We would like to understand whether the transcription factors could influence or enhance the occurrence of mutations. We would like to uncover the mechanisms involved in the formation of larger structural variants. Specifically, the HR factors that could be responsible for errors in HR.

Résumé :

Les mécanismes épigénétiques régulent de nombreux processus cellulaires et sont essentiels pour en établir l'identité. Le travail effectué pendant mon doctorat visait à déterminer si l'exposition à un polluant environnemental, le chlordécone (CD), pouvait affecter les principales marques épigénétiques du système reproducteur chez la souris et si ces changements pouvaient être hérités par les générations suivantes par héritage épigénétique transgénérationnel. Les travaux réalisés dans le cadre de cette thèse ont révélé qu'une exposition développementale au CD conduit à une altération de la méiose chez les souris mâles et femelles, entraîne une réduction des cellules reproductrices viables, à la fois la spermatogonie et les spermatozoïdes chez les mâles, et les ovocytes chez les femelles. Les modifications morphologiques sont accompagnées d'une modification de l'occupation de l'histone H3K4me3 dans les gènes liés à la régulation de la pluripotence.

Par ailleurs des études ont été menées sur le sang du cordon ombilical des garçons de la cohorte TIMOUN dont la concentration interne en CD est connue. Ces travaux ont permis de constater que l'exposition au CD provoque des changements de tri-méthylation des principales marques histones impliquées dans le maintien de la stabilité génétique. Le séquençage de l'exome complet a permis la détection des mutations de novo dans des gènes codant pour des protéines ayant des fonctions importantes, telles que la réparation de l'ADN et le métabolisme. L'analyse comparative des données d'exposition des souris et des humains a révélé que certains gènes étaient modifiés dans les deux organismes, notamment les gènes liés à l'organisation des chromosomes, aux facteurs de transcription et aux fonctions métaboliques. En résumé, nos études ont apporté des preuves de la capacité du CD à induire des altérations épigénétiques et génétiques. Il reste nécessaire d'étudier plus en détail les gènes identifiés et les mécanismes moléculaires affectés par le CD à l'aide de modèles in vivo et in vitro.

Title: Study of epigenetic alterations promoted by chlordecone exposure during development in human and mouse. Keywords: epigenetics, transgenerational inheritance, chlordecone, reproductive system

Abstract:

Epigenetic mechanisms regulate many cellular processes and they are critical for establishing cell identity. The work performed during my Ph.D. aimed to determine whether exposure to an environmental pollutant, chlordecone (CD), could affect the major epigenetic marks in the reproductive system in directly-exposed mice and whether these changes could be inherited by subsequent generations through epigenetic transgenerational inheritance. Our work revealed that direct developmental exposure to CD leads to impairment of meiosis in male and female mice, causes a reduction in viable reproductive cells, i.e., both spermatogonia and spermatozoid, and oocytes in females. The altered morphological changes were accompanied by altered histone H3K4me3 occupancy in the genes related to pluripotency regulation.

We also performed studies in the umbilical cord blood of males from the TIMOUN cohort with the known internal concentration of CD. We found that exposure to CD causes epigenetic changes in major histone trimethylation marks important for the maintenance of genetic stability. Using whole exome-sequencing, we detected de novo mutations in genes encoding proteins with important functions, such as DNA repair and metabolic genes. Comparative analysis of mice and human exposures revealed some common genes to be altered in both organisms, notably genes related to chromosome organization, transcription factors, and metabolic functions. In summary, our studies brought some evidence for the ability of CD to induce epigenetic and genetic alterations.

Identified genes and molecular mechanisms affected by CD will be further investigated using in vivo and in vitro model systems.

Figure 1 .

 1 Figure 1. Double helix structure of the DNA and detailed nucleotide structures. ...............................Figure 2. The major structure of DNA ................................................................................................... Figure 3. Chromosomes are composed of DNA tightly-wound around histones .................................Figure 4. Summary of the different partitions of the human genome ................................................. Figure 5. DNA repair pathways ............................................................................................................. Figure 6. Types of point mutations .......................................................................................................Figure 7. Different types of large structural variants.. ..........................................................................Figure 8. A schematic representation of the domain structure of human DNMT isoforms .................Figure 9. Overview of DNA methylation and demethylation ................................................................Figure 10. DNA methylation at promoters regulates transcription binding and subsequent transcription .......................................................................................................................................... Figure 11. Transcriptional dynamics during pre-implantation embryo in mouse ................................ Figure 12. DNA methylation reprogramming in development. ............................................................ Figure 13. Development of the genital ridge from the coelomic epithelium ..................................... Figure 14. Meiosis timeline differs in males and females. .................................................................. Figure 15. Schematic representation of the synaptonemal complex at different stages during Prophase I. ........................................................................................................................................... Figure 16. Sex differentiation of the female germ cells. ..................................................................... Figure 17. Schematic representation of the ovary structure and follicle stages ................................ Figure 18. Schematic representation of male gonad differentiation .................................................. Figure 19. A model showing Sry regulation in mouse ......................................................................... Figure 20. Sox9 is the central element triggering the differentiation of male gonad ........................ Figure 21. Schematic representation of main cell types in testis ....................................................... Figure 22. Differentiation of a diploid human germ cell into a fully functional spermatozoon ......... Figure 23. Summary of critical time points, epigenetics events and the key factors involved during histone-to-protamine transition ......................................................................................................... Figure 24. Schematic representation of evolution from normal prostate to pre-malignant and cancerous states. ................................................................................................................................. Figure 25. Major cell types found in the prostate............................................................................... Figure 26. Hematopoietic stem cell generation in the P-Sp/AGM. ..................................................... Figure 27. Chlordecone three-dimensional structure. ........................................................................ Figure 28. Overview of DNA and RNA library preparation.................................................................. Figure 29. Illumina® cluster generation by bridge amplification ........................................................ Figure 30. Structure of a fastq file ....................................................................................................... Figure 31. FastQC provides several metrics to evaluate quality of the sequencing data. .................. Figure 32. The Burrows-Wheeler transform of a text is a permutation of this text. ..........................Figure 33. Command used to run the mapping step using TopHat. ...................................................Figure 34. Command line to count reads within genes using HTSeq. .................................................Figure 35. Comparison between RPKM/FPKM and TPM metrics. ...................................................... Figure 36. An overview of the DESeq2 read count normalization process. ........................................Figure 37. Example of an R code to perform differential gene analysis using DESeq2. .....................Figure 38. Command line to perform mapping using Bowtie2. .......................................................... Figure 39. Overview of the pre-processing and peak calling steps performed by MACS2. ................Figure 40. Process performed by MACS2 to adjust reads location and assess original fragment position ................................................................................................................................................Figure 41. Command used for bam to bedgraph convertion using bedtools. ....................................Figure 42. Python script to perform the normalization of bedgraph files. .........................................Figure 43. Python script used to quantify peak intensity. ..................................................................

Figure 2 .Figure 3 .

 23 Figure 1. Double helix structure of the DNA and detailed nucleotide structures. ...............................Figure 2. The major structure of DNA ................................................................................................... Figure 3. Chromosomes are composed of DNA tightly-wound around histones .................................Figure 4. Summary of the different partitions of the human genome ................................................. Figure 5. DNA repair pathways ............................................................................................................. Figure 6. Types of point mutations .......................................................................................................Figure 7. Different types of large structural variants.. ..........................................................................Figure 8. A schematic representation of the domain structure of human DNMT isoforms .................Figure 9. Overview of DNA methylation and demethylation ................................................................Figure 10. DNA methylation at promoters regulates transcription binding and subsequent transcription .......................................................................................................................................... Figure 11. Transcriptional dynamics during pre-implantation embryo in mouse ................................ Figure 12. DNA methylation reprogramming in development. ............................................................ Figure 13. Development of the genital ridge from the coelomic epithelium ..................................... Figure 14. Meiosis timeline differs in males and females. .................................................................. Figure 15. Schematic representation of the synaptonemal complex at different stages during Prophase I. ........................................................................................................................................... Figure 16. Sex differentiation of the female germ cells. ..................................................................... Figure 17. Schematic representation of the ovary structure and follicle stages ................................ Figure 18. Schematic representation of male gonad differentiation .................................................. Figure 19. A model showing Sry regulation in mouse ......................................................................... Figure 20. Sox9 is the central element triggering the differentiation of male gonad ........................ Figure 21. Schematic representation of main cell types in testis ....................................................... Figure 22. Differentiation of a diploid human germ cell into a fully functional spermatozoon ......... Figure 23. Summary of critical time points, epigenetics events and the key factors involved during histone-to-protamine transition ......................................................................................................... Figure 24. Schematic representation of evolution from normal prostate to pre-malignant and cancerous states. ................................................................................................................................. Figure 25. Major cell types found in the prostate............................................................................... Figure 26. Hematopoietic stem cell generation in the P-Sp/AGM. ..................................................... Figure 27. Chlordecone three-dimensional structure. ........................................................................ Figure 28. Overview of DNA and RNA library preparation.................................................................. Figure 29. Illumina® cluster generation by bridge amplification ........................................................ Figure 30. Structure of a fastq file ....................................................................................................... Figure 31. FastQC provides several metrics to evaluate quality of the sequencing data. .................. Figure 32. The Burrows-Wheeler transform of a text is a permutation of this text. ..........................Figure 33. Command used to run the mapping step using TopHat. ...................................................Figure 34. Command line to count reads within genes using HTSeq. .................................................Figure 35. Comparison between RPKM/FPKM and TPM metrics. ...................................................... Figure 36. An overview of the DESeq2 read count normalization process. ........................................Figure 37. Example of an R code to perform differential gene analysis using DESeq2. .....................Figure 38. Command line to perform mapping using Bowtie2. .......................................................... Figure 39. Overview of the pre-processing and peak calling steps performed by MACS2. ................Figure 40. Process performed by MACS2 to adjust reads location and assess original fragment position ................................................................................................................................................Figure 41. Command used for bam to bedgraph convertion using bedtools. ....................................Figure 42. Python script to perform the normalization of bedgraph files. .........................................Figure 43. Python script used to quantify peak intensity. ..................................................................

Figure 4 .

 4 Figure 1. Double helix structure of the DNA and detailed nucleotide structures. ...............................Figure 2. The major structure of DNA ................................................................................................... Figure 3. Chromosomes are composed of DNA tightly-wound around histones .................................Figure 4. Summary of the different partitions of the human genome ................................................. Figure 5. DNA repair pathways ............................................................................................................. Figure 6. Types of point mutations .......................................................................................................Figure 7. Different types of large structural variants.. ..........................................................................Figure 8. A schematic representation of the domain structure of human DNMT isoforms .................Figure 9. Overview of DNA methylation and demethylation ................................................................Figure 10. DNA methylation at promoters regulates transcription binding and subsequent transcription .......................................................................................................................................... Figure 11. Transcriptional dynamics during pre-implantation embryo in mouse ................................ Figure 12. DNA methylation reprogramming in development. ............................................................ Figure 13. Development of the genital ridge from the coelomic epithelium ..................................... Figure 14. Meiosis timeline differs in males and females. .................................................................. Figure 15. Schematic representation of the synaptonemal complex at different stages during Prophase I. ........................................................................................................................................... Figure 16. Sex differentiation of the female germ cells. ..................................................................... Figure 17. Schematic representation of the ovary structure and follicle stages ................................ Figure 18. Schematic representation of male gonad differentiation .................................................. Figure 19. A model showing Sry regulation in mouse ......................................................................... Figure 20. Sox9 is the central element triggering the differentiation of male gonad ........................ Figure 21. Schematic representation of main cell types in testis ....................................................... Figure 22. Differentiation of a diploid human germ cell into a fully functional spermatozoon ......... Figure 23. Summary of critical time points, epigenetics events and the key factors involved during histone-to-protamine transition ......................................................................................................... Figure 24. Schematic representation of evolution from normal prostate to pre-malignant and cancerous states. ................................................................................................................................. Figure 25. Major cell types found in the prostate............................................................................... Figure 26. Hematopoietic stem cell generation in the P-Sp/AGM. ..................................................... Figure 27. Chlordecone three-dimensional structure. ........................................................................ Figure 28. Overview of DNA and RNA library preparation.................................................................. Figure 29. Illumina® cluster generation by bridge amplification ........................................................ Figure 30. Structure of a fastq file ....................................................................................................... Figure 31. FastQC provides several metrics to evaluate quality of the sequencing data. .................. Figure 32. The Burrows-Wheeler transform of a text is a permutation of this text. ..........................Figure 33. Command used to run the mapping step using TopHat. ...................................................Figure 34. Command line to count reads within genes using HTSeq. .................................................Figure 35. Comparison between RPKM/FPKM and TPM metrics. ...................................................... Figure 36. An overview of the DESeq2 read count normalization process. ........................................Figure 37. Example of an R code to perform differential gene analysis using DESeq2. .....................Figure 38. Command line to perform mapping using Bowtie2. .......................................................... Figure 39. Overview of the pre-processing and peak calling steps performed by MACS2. ................Figure 40. Process performed by MACS2 to adjust reads location and assess original fragment position ................................................................................................................................................Figure 41. Command used for bam to bedgraph convertion using bedtools. ....................................Figure 42. Python script to perform the normalization of bedgraph files. .........................................Figure 43. Python script used to quantify peak intensity. ..................................................................

Figure 7 .

 7 Figure 1. Double helix structure of the DNA and detailed nucleotide structures. ...............................Figure 2. The major structure of DNA ................................................................................................... Figure 3. Chromosomes are composed of DNA tightly-wound around histones .................................Figure 4. Summary of the different partitions of the human genome ................................................. Figure 5. DNA repair pathways ............................................................................................................. Figure 6. Types of point mutations .......................................................................................................Figure 7. Different types of large structural variants.. ..........................................................................Figure 8. A schematic representation of the domain structure of human DNMT isoforms .................Figure 9. Overview of DNA methylation and demethylation ................................................................Figure 10. DNA methylation at promoters regulates transcription binding and subsequent transcription .......................................................................................................................................... Figure 11. Transcriptional dynamics during pre-implantation embryo in mouse ................................ Figure 12. DNA methylation reprogramming in development. ............................................................ Figure 13. Development of the genital ridge from the coelomic epithelium ..................................... Figure 14. Meiosis timeline differs in males and females. .................................................................. Figure 15. Schematic representation of the synaptonemal complex at different stages during Prophase I. ........................................................................................................................................... Figure 16. Sex differentiation of the female germ cells. ..................................................................... Figure 17. Schematic representation of the ovary structure and follicle stages ................................ Figure 18. Schematic representation of male gonad differentiation .................................................. Figure 19. A model showing Sry regulation in mouse ......................................................................... Figure 20. Sox9 is the central element triggering the differentiation of male gonad ........................ Figure 21. Schematic representation of main cell types in testis ....................................................... Figure 22. Differentiation of a diploid human germ cell into a fully functional spermatozoon ......... Figure 23. Summary of critical time points, epigenetics events and the key factors involved during histone-to-protamine transition ......................................................................................................... Figure 24. Schematic representation of evolution from normal prostate to pre-malignant and cancerous states. ................................................................................................................................. Figure 25. Major cell types found in the prostate............................................................................... Figure 26. Hematopoietic stem cell generation in the P-Sp/AGM. ..................................................... Figure 27. Chlordecone three-dimensional structure. ........................................................................ Figure 28. Overview of DNA and RNA library preparation.................................................................. Figure 29. Illumina® cluster generation by bridge amplification ........................................................ Figure 30. Structure of a fastq file ....................................................................................................... Figure 31. FastQC provides several metrics to evaluate quality of the sequencing data. .................. Figure 32. The Burrows-Wheeler transform of a text is a permutation of this text. ..........................Figure 33. Command used to run the mapping step using TopHat. ...................................................Figure 34. Command line to count reads within genes using HTSeq. .................................................Figure 35. Comparison between RPKM/FPKM and TPM metrics. ...................................................... Figure 36. An overview of the DESeq2 read count normalization process. ........................................Figure 37. Example of an R code to perform differential gene analysis using DESeq2. .....................Figure 38. Command line to perform mapping using Bowtie2. .......................................................... Figure 39. Overview of the pre-processing and peak calling steps performed by MACS2. ................Figure 40. Process performed by MACS2 to adjust reads location and assess original fragment position ................................................................................................................................................Figure 41. Command used for bam to bedgraph convertion using bedtools. ....................................Figure 42. Python script to perform the normalization of bedgraph files. .........................................Figure 43. Python script used to quantify peak intensity. ..................................................................

Figure 8 .

 8 Figure 1. Double helix structure of the DNA and detailed nucleotide structures. ...............................Figure 2. The major structure of DNA ................................................................................................... Figure 3. Chromosomes are composed of DNA tightly-wound around histones .................................Figure 4. Summary of the different partitions of the human genome ................................................. Figure 5. DNA repair pathways ............................................................................................................. Figure 6. Types of point mutations .......................................................................................................Figure 7. Different types of large structural variants.. ..........................................................................Figure 8. A schematic representation of the domain structure of human DNMT isoforms .................Figure 9. Overview of DNA methylation and demethylation ................................................................Figure 10. DNA methylation at promoters regulates transcription binding and subsequent transcription .......................................................................................................................................... Figure 11. Transcriptional dynamics during pre-implantation embryo in mouse ................................ Figure 12. DNA methylation reprogramming in development. ............................................................ Figure 13. Development of the genital ridge from the coelomic epithelium ..................................... Figure 14. Meiosis timeline differs in males and females. .................................................................. Figure 15. Schematic representation of the synaptonemal complex at different stages during Prophase I. ........................................................................................................................................... Figure 16. Sex differentiation of the female germ cells. ..................................................................... Figure 17. Schematic representation of the ovary structure and follicle stages ................................ Figure 18. Schematic representation of male gonad differentiation .................................................. Figure 19. A model showing Sry regulation in mouse ......................................................................... Figure 20. Sox9 is the central element triggering the differentiation of male gonad ........................ Figure 21. Schematic representation of main cell types in testis ....................................................... Figure 22. Differentiation of a diploid human germ cell into a fully functional spermatozoon ......... Figure 23. Summary of critical time points, epigenetics events and the key factors involved during histone-to-protamine transition ......................................................................................................... Figure 24. Schematic representation of evolution from normal prostate to pre-malignant and cancerous states. ................................................................................................................................. Figure 25. Major cell types found in the prostate............................................................................... Figure 26. Hematopoietic stem cell generation in the P-Sp/AGM. ..................................................... Figure 27. Chlordecone three-dimensional structure. ........................................................................ Figure 28. Overview of DNA and RNA library preparation.................................................................. Figure 29. Illumina® cluster generation by bridge amplification ........................................................ Figure 30. Structure of a fastq file ....................................................................................................... Figure 31. FastQC provides several metrics to evaluate quality of the sequencing data. .................. Figure 32. The Burrows-Wheeler transform of a text is a permutation of this text. ..........................Figure 33. Command used to run the mapping step using TopHat. ...................................................Figure 34. Command line to count reads within genes using HTSeq. .................................................Figure 35. Comparison between RPKM/FPKM and TPM metrics. ...................................................... Figure 36. An overview of the DESeq2 read count normalization process. ........................................Figure 37. Example of an R code to perform differential gene analysis using DESeq2. .....................Figure 38. Command line to perform mapping using Bowtie2. .......................................................... Figure 39. Overview of the pre-processing and peak calling steps performed by MACS2. ................Figure 40. Process performed by MACS2 to adjust reads location and assess original fragment position ................................................................................................................................................Figure 41. Command used for bam to bedgraph convertion using bedtools. ....................................Figure 42. Python script to perform the normalization of bedgraph files. .........................................Figure 43. Python script used to quantify peak intensity. ..................................................................

Figure 9 .

 9 Figure 1. Double helix structure of the DNA and detailed nucleotide structures. ...............................Figure 2. The major structure of DNA ................................................................................................... Figure 3. Chromosomes are composed of DNA tightly-wound around histones .................................Figure 4. Summary of the different partitions of the human genome ................................................. Figure 5. DNA repair pathways ............................................................................................................. Figure 6. Types of point mutations .......................................................................................................Figure 7. Different types of large structural variants.. ..........................................................................Figure 8. A schematic representation of the domain structure of human DNMT isoforms .................Figure 9. Overview of DNA methylation and demethylation ................................................................Figure 10. DNA methylation at promoters regulates transcription binding and subsequent transcription .......................................................................................................................................... Figure 11. Transcriptional dynamics during pre-implantation embryo in mouse ................................ Figure 12. DNA methylation reprogramming in development. ............................................................ Figure 13. Development of the genital ridge from the coelomic epithelium ..................................... Figure 14. Meiosis timeline differs in males and females. .................................................................. Figure 15. Schematic representation of the synaptonemal complex at different stages during Prophase I. ........................................................................................................................................... Figure 16. Sex differentiation of the female germ cells. ..................................................................... Figure 17. Schematic representation of the ovary structure and follicle stages ................................ Figure 18. Schematic representation of male gonad differentiation .................................................. Figure 19. A model showing Sry regulation in mouse ......................................................................... Figure 20. Sox9 is the central element triggering the differentiation of male gonad ........................ Figure 21. Schematic representation of main cell types in testis ....................................................... Figure 22. Differentiation of a diploid human germ cell into a fully functional spermatozoon ......... Figure 23. Summary of critical time points, epigenetics events and the key factors involved during histone-to-protamine transition ......................................................................................................... Figure 24. Schematic representation of evolution from normal prostate to pre-malignant and cancerous states. ................................................................................................................................. Figure 25. Major cell types found in the prostate............................................................................... Figure 26. Hematopoietic stem cell generation in the P-Sp/AGM. ..................................................... Figure 27. Chlordecone three-dimensional structure. ........................................................................ Figure 28. Overview of DNA and RNA library preparation.................................................................. Figure 29. Illumina® cluster generation by bridge amplification ........................................................ Figure 30. Structure of a fastq file ....................................................................................................... Figure 31. FastQC provides several metrics to evaluate quality of the sequencing data. .................. Figure 32. The Burrows-Wheeler transform of a text is a permutation of this text. ..........................Figure 33. Command used to run the mapping step using TopHat. ...................................................Figure 34. Command line to count reads within genes using HTSeq. .................................................Figure 35. Comparison between RPKM/FPKM and TPM metrics. ...................................................... Figure 36. An overview of the DESeq2 read count normalization process. ........................................Figure 37. Example of an R code to perform differential gene analysis using DESeq2. .....................Figure 38. Command line to perform mapping using Bowtie2. .......................................................... Figure 39. Overview of the pre-processing and peak calling steps performed by MACS2. ................Figure 40. Process performed by MACS2 to adjust reads location and assess original fragment position ................................................................................................................................................Figure 41. Command used for bam to bedgraph convertion using bedtools. ....................................Figure 42. Python script to perform the normalization of bedgraph files. .........................................Figure 43. Python script used to quantify peak intensity. ..................................................................

Figure 20 .

 20 Figure 1. Double helix structure of the DNA and detailed nucleotide structures. ...............................Figure 2. The major structure of DNA ................................................................................................... Figure 3. Chromosomes are composed of DNA tightly-wound around histones .................................Figure 4. Summary of the different partitions of the human genome ................................................. Figure 5. DNA repair pathways ............................................................................................................. Figure 6. Types of point mutations .......................................................................................................Figure 7. Different types of large structural variants.. ..........................................................................Figure 8. A schematic representation of the domain structure of human DNMT isoforms .................Figure 9. Overview of DNA methylation and demethylation ................................................................Figure 10. DNA methylation at promoters regulates transcription binding and subsequent transcription .......................................................................................................................................... Figure 11. Transcriptional dynamics during pre-implantation embryo in mouse ................................ Figure 12. DNA methylation reprogramming in development. ............................................................ Figure 13. Development of the genital ridge from the coelomic epithelium ..................................... Figure 14. Meiosis timeline differs in males and females. .................................................................. Figure 15. Schematic representation of the synaptonemal complex at different stages during Prophase I. ........................................................................................................................................... Figure 16. Sex differentiation of the female germ cells. ..................................................................... Figure 17. Schematic representation of the ovary structure and follicle stages ................................ Figure 18. Schematic representation of male gonad differentiation .................................................. Figure 19. A model showing Sry regulation in mouse ......................................................................... Figure 20. Sox9 is the central element triggering the differentiation of male gonad ........................ Figure 21. Schematic representation of main cell types in testis ....................................................... Figure 22. Differentiation of a diploid human germ cell into a fully functional spermatozoon ......... Figure 23. Summary of critical time points, epigenetics events and the key factors involved during histone-to-protamine transition ......................................................................................................... Figure 24. Schematic representation of evolution from normal prostate to pre-malignant and cancerous states. ................................................................................................................................. Figure 25. Major cell types found in the prostate............................................................................... Figure 26. Hematopoietic stem cell generation in the P-Sp/AGM. ..................................................... Figure 27. Chlordecone three-dimensional structure. ........................................................................ Figure 28. Overview of DNA and RNA library preparation.................................................................. Figure 29. Illumina® cluster generation by bridge amplification ........................................................ Figure 30. Structure of a fastq file ....................................................................................................... Figure 31. FastQC provides several metrics to evaluate quality of the sequencing data. .................. Figure 32. The Burrows-Wheeler transform of a text is a permutation of this text. ..........................Figure 33. Command used to run the mapping step using TopHat. ...................................................Figure 34. Command line to count reads within genes using HTSeq. .................................................Figure 35. Comparison between RPKM/FPKM and TPM metrics. ...................................................... Figure 36. An overview of the DESeq2 read count normalization process. ........................................Figure 37. Example of an R code to perform differential gene analysis using DESeq2. .....................Figure 38. Command line to perform mapping using Bowtie2. .......................................................... Figure 39. Overview of the pre-processing and peak calling steps performed by MACS2. ................Figure 40. Process performed by MACS2 to adjust reads location and assess original fragment position ................................................................................................................................................Figure 41. Command used for bam to bedgraph convertion using bedtools. ....................................Figure 42. Python script to perform the normalization of bedgraph files. .........................................Figure 43. Python script used to quantify peak intensity. ..................................................................

Figure 22 .

 22 Figure 1. Double helix structure of the DNA and detailed nucleotide structures. ...............................Figure 2. The major structure of DNA ................................................................................................... Figure 3. Chromosomes are composed of DNA tightly-wound around histones .................................Figure 4. Summary of the different partitions of the human genome ................................................. Figure 5. DNA repair pathways ............................................................................................................. Figure 6. Types of point mutations .......................................................................................................Figure 7. Different types of large structural variants.. ..........................................................................Figure 8. A schematic representation of the domain structure of human DNMT isoforms .................Figure 9. Overview of DNA methylation and demethylation ................................................................Figure 10. DNA methylation at promoters regulates transcription binding and subsequent transcription .......................................................................................................................................... Figure 11. Transcriptional dynamics during pre-implantation embryo in mouse ................................ Figure 12. DNA methylation reprogramming in development. ............................................................ Figure 13. Development of the genital ridge from the coelomic epithelium ..................................... Figure 14. Meiosis timeline differs in males and females. .................................................................. Figure 15. Schematic representation of the synaptonemal complex at different stages during Prophase I. ........................................................................................................................................... Figure 16. Sex differentiation of the female germ cells. ..................................................................... Figure 17. Schematic representation of the ovary structure and follicle stages ................................ Figure 18. Schematic representation of male gonad differentiation .................................................. Figure 19. A model showing Sry regulation in mouse ......................................................................... Figure 20. Sox9 is the central element triggering the differentiation of male gonad ........................ Figure 21. Schematic representation of main cell types in testis ....................................................... Figure 22. Differentiation of a diploid human germ cell into a fully functional spermatozoon ......... Figure 23. Summary of critical time points, epigenetics events and the key factors involved during histone-to-protamine transition ......................................................................................................... Figure 24. Schematic representation of evolution from normal prostate to pre-malignant and cancerous states. ................................................................................................................................. Figure 25. Major cell types found in the prostate............................................................................... Figure 26. Hematopoietic stem cell generation in the P-Sp/AGM. ..................................................... Figure 27. Chlordecone three-dimensional structure. ........................................................................ Figure 28. Overview of DNA and RNA library preparation.................................................................. Figure 29. Illumina® cluster generation by bridge amplification ........................................................ Figure 30. Structure of a fastq file ....................................................................................................... Figure 31. FastQC provides several metrics to evaluate quality of the sequencing data. .................. Figure 32. The Burrows-Wheeler transform of a text is a permutation of this text. ..........................Figure 33. Command used to run the mapping step using TopHat. ...................................................Figure 34. Command line to count reads within genes using HTSeq. .................................................Figure 35. Comparison between RPKM/FPKM and TPM metrics. ...................................................... Figure 36. An overview of the DESeq2 read count normalization process. ........................................Figure 37. Example of an R code to perform differential gene analysis using DESeq2. .....................Figure 38. Command line to perform mapping using Bowtie2. .......................................................... Figure 39. Overview of the pre-processing and peak calling steps performed by MACS2. ................Figure 40. Process performed by MACS2 to adjust reads location and assess original fragment position ................................................................................................................................................Figure 41. Command used for bam to bedgraph convertion using bedtools. ....................................Figure 42. Python script to perform the normalization of bedgraph files. .........................................Figure 43. Python script used to quantify peak intensity. ..................................................................

Figure 33 .

 33 Figure 1. Double helix structure of the DNA and detailed nucleotide structures. ...............................Figure 2. The major structure of DNA ................................................................................................... Figure 3. Chromosomes are composed of DNA tightly-wound around histones .................................Figure 4. Summary of the different partitions of the human genome ................................................. Figure 5. DNA repair pathways ............................................................................................................. Figure 6. Types of point mutations .......................................................................................................Figure 7. Different types of large structural variants.. ..........................................................................Figure 8. A schematic representation of the domain structure of human DNMT isoforms .................Figure 9. Overview of DNA methylation and demethylation ................................................................Figure 10. DNA methylation at promoters regulates transcription binding and subsequent transcription .......................................................................................................................................... Figure 11. Transcriptional dynamics during pre-implantation embryo in mouse ................................ Figure 12. DNA methylation reprogramming in development. ............................................................ Figure 13. Development of the genital ridge from the coelomic epithelium ..................................... Figure 14. Meiosis timeline differs in males and females. .................................................................. Figure 15. Schematic representation of the synaptonemal complex at different stages during Prophase I. ........................................................................................................................................... Figure 16. Sex differentiation of the female germ cells. ..................................................................... Figure 17. Schematic representation of the ovary structure and follicle stages ................................ Figure 18. Schematic representation of male gonad differentiation .................................................. Figure 19. A model showing Sry regulation in mouse ......................................................................... Figure 20. Sox9 is the central element triggering the differentiation of male gonad ........................ Figure 21. Schematic representation of main cell types in testis ....................................................... Figure 22. Differentiation of a diploid human germ cell into a fully functional spermatozoon ......... Figure 23. Summary of critical time points, epigenetics events and the key factors involved during histone-to-protamine transition ......................................................................................................... Figure 24. Schematic representation of evolution from normal prostate to pre-malignant and cancerous states. ................................................................................................................................. Figure 25. Major cell types found in the prostate............................................................................... Figure 26. Hematopoietic stem cell generation in the P-Sp/AGM. ..................................................... Figure 27. Chlordecone three-dimensional structure. ........................................................................ Figure 28. Overview of DNA and RNA library preparation.................................................................. Figure 29. Illumina® cluster generation by bridge amplification ........................................................ Figure 30. Structure of a fastq file ....................................................................................................... Figure 31. FastQC provides several metrics to evaluate quality of the sequencing data. .................. Figure 32. The Burrows-Wheeler transform of a text is a permutation of this text. ..........................Figure 33. Command used to run the mapping step using TopHat. ...................................................Figure 34. Command line to count reads within genes using HTSeq. .................................................Figure 35. Comparison between RPKM/FPKM and TPM metrics. ...................................................... Figure 36. An overview of the DESeq2 read count normalization process. ........................................Figure 37. Example of an R code to perform differential gene analysis using DESeq2. .....................Figure 38. Command line to perform mapping using Bowtie2. .......................................................... Figure 39. Overview of the pre-processing and peak calling steps performed by MACS2. ................Figure 40. Process performed by MACS2 to adjust reads location and assess original fragment position ................................................................................................................................................Figure 41. Command used for bam to bedgraph convertion using bedtools. ....................................Figure 42. Python script to perform the normalization of bedgraph files. .........................................Figure 43. Python script used to quantify peak intensity. ..................................................................

Figure 34 .

 34 Figure 1. Double helix structure of the DNA and detailed nucleotide structures. ...............................Figure 2. The major structure of DNA ................................................................................................... Figure 3. Chromosomes are composed of DNA tightly-wound around histones .................................Figure 4. Summary of the different partitions of the human genome ................................................. Figure 5. DNA repair pathways ............................................................................................................. Figure 6. Types of point mutations .......................................................................................................Figure 7. Different types of large structural variants.. ..........................................................................Figure 8. A schematic representation of the domain structure of human DNMT isoforms .................Figure 9. Overview of DNA methylation and demethylation ................................................................Figure 10. DNA methylation at promoters regulates transcription binding and subsequent transcription .......................................................................................................................................... Figure 11. Transcriptional dynamics during pre-implantation embryo in mouse ................................ Figure 12. DNA methylation reprogramming in development. ............................................................ Figure 13. Development of the genital ridge from the coelomic epithelium ..................................... Figure 14. Meiosis timeline differs in males and females. .................................................................. Figure 15. Schematic representation of the synaptonemal complex at different stages during Prophase I. ........................................................................................................................................... Figure 16. Sex differentiation of the female germ cells. ..................................................................... Figure 17. Schematic representation of the ovary structure and follicle stages ................................ Figure 18. Schematic representation of male gonad differentiation .................................................. Figure 19. A model showing Sry regulation in mouse ......................................................................... Figure 20. Sox9 is the central element triggering the differentiation of male gonad ........................ Figure 21. Schematic representation of main cell types in testis ....................................................... Figure 22. Differentiation of a diploid human germ cell into a fully functional spermatozoon ......... Figure 23. Summary of critical time points, epigenetics events and the key factors involved during histone-to-protamine transition ......................................................................................................... Figure 24. Schematic representation of evolution from normal prostate to pre-malignant and cancerous states. ................................................................................................................................. Figure 25. Major cell types found in the prostate............................................................................... Figure 26. Hematopoietic stem cell generation in the P-Sp/AGM. ..................................................... Figure 27. Chlordecone three-dimensional structure. ........................................................................ Figure 28. Overview of DNA and RNA library preparation.................................................................. Figure 29. Illumina® cluster generation by bridge amplification ........................................................ Figure 30. Structure of a fastq file ....................................................................................................... Figure 31. FastQC provides several metrics to evaluate quality of the sequencing data. .................. Figure 32. The Burrows-Wheeler transform of a text is a permutation of this text. ..........................Figure 33. Command used to run the mapping step using TopHat. ...................................................Figure 34. Command line to count reads within genes using HTSeq. .................................................Figure 35. Comparison between RPKM/FPKM and TPM metrics. ...................................................... Figure 36. An overview of the DESeq2 read count normalization process. ........................................Figure 37. Example of an R code to perform differential gene analysis using DESeq2. .....................Figure 38. Command line to perform mapping using Bowtie2. .......................................................... Figure 39. Overview of the pre-processing and peak calling steps performed by MACS2. ................Figure 40. Process performed by MACS2 to adjust reads location and assess original fragment position ................................................................................................................................................Figure 41. Command used for bam to bedgraph convertion using bedtools. ....................................Figure 42. Python script to perform the normalization of bedgraph files. .........................................Figure 43. Python script used to quantify peak intensity. ..................................................................

Figure 35 .

 35 Figure 1. Double helix structure of the DNA and detailed nucleotide structures. ...............................Figure 2. The major structure of DNA ................................................................................................... Figure 3. Chromosomes are composed of DNA tightly-wound around histones .................................Figure 4. Summary of the different partitions of the human genome ................................................. Figure 5. DNA repair pathways ............................................................................................................. Figure 6. Types of point mutations .......................................................................................................Figure 7. Different types of large structural variants.. ..........................................................................Figure 8. A schematic representation of the domain structure of human DNMT isoforms .................Figure 9. Overview of DNA methylation and demethylation ................................................................Figure 10. DNA methylation at promoters regulates transcription binding and subsequent transcription .......................................................................................................................................... Figure 11. Transcriptional dynamics during pre-implantation embryo in mouse ................................ Figure 12. DNA methylation reprogramming in development. ............................................................ Figure 13. Development of the genital ridge from the coelomic epithelium ..................................... Figure 14. Meiosis timeline differs in males and females. .................................................................. Figure 15. Schematic representation of the synaptonemal complex at different stages during Prophase I. ........................................................................................................................................... Figure 16. Sex differentiation of the female germ cells. ..................................................................... Figure 17. Schematic representation of the ovary structure and follicle stages ................................ Figure 18. Schematic representation of male gonad differentiation .................................................. Figure 19. A model showing Sry regulation in mouse ......................................................................... Figure 20. Sox9 is the central element triggering the differentiation of male gonad ........................ Figure 21. Schematic representation of main cell types in testis ....................................................... Figure 22. Differentiation of a diploid human germ cell into a fully functional spermatozoon ......... Figure 23. Summary of critical time points, epigenetics events and the key factors involved during histone-to-protamine transition ......................................................................................................... Figure 24. Schematic representation of evolution from normal prostate to pre-malignant and cancerous states. ................................................................................................................................. Figure 25. Major cell types found in the prostate............................................................................... Figure 26. Hematopoietic stem cell generation in the P-Sp/AGM. ..................................................... Figure 27. Chlordecone three-dimensional structure. ........................................................................ Figure 28. Overview of DNA and RNA library preparation.................................................................. Figure 29. Illumina® cluster generation by bridge amplification ........................................................ Figure 30. Structure of a fastq file ....................................................................................................... Figure 31. FastQC provides several metrics to evaluate quality of the sequencing data. .................. Figure 32. The Burrows-Wheeler transform of a text is a permutation of this text. ..........................Figure 33. Command used to run the mapping step using TopHat. ...................................................Figure 34. Command line to count reads within genes using HTSeq. .................................................Figure 35. Comparison between RPKM/FPKM and TPM metrics. ...................................................... Figure 36. An overview of the DESeq2 read count normalization process. ........................................Figure 37. Example of an R code to perform differential gene analysis using DESeq2. .....................Figure 38. Command line to perform mapping using Bowtie2. .......................................................... Figure 39. Overview of the pre-processing and peak calling steps performed by MACS2. ................Figure 40. Process performed by MACS2 to adjust reads location and assess original fragment position ................................................................................................................................................Figure 41. Command used for bam to bedgraph convertion using bedtools. ....................................Figure 42. Python script to perform the normalization of bedgraph files. .........................................Figure 43. Python script used to quantify peak intensity. ..................................................................

Figure 37 .

 37 Figure 1. Double helix structure of the DNA and detailed nucleotide structures. ...............................Figure 2. The major structure of DNA ................................................................................................... Figure 3. Chromosomes are composed of DNA tightly-wound around histones .................................Figure 4. Summary of the different partitions of the human genome ................................................. Figure 5. DNA repair pathways ............................................................................................................. Figure 6. Types of point mutations .......................................................................................................Figure 7. Different types of large structural variants.. ..........................................................................Figure 8. A schematic representation of the domain structure of human DNMT isoforms .................Figure 9. Overview of DNA methylation and demethylation ................................................................Figure 10. DNA methylation at promoters regulates transcription binding and subsequent transcription .......................................................................................................................................... Figure 11. Transcriptional dynamics during pre-implantation embryo in mouse ................................ Figure 12. DNA methylation reprogramming in development. ............................................................ Figure 13. Development of the genital ridge from the coelomic epithelium ..................................... Figure 14. Meiosis timeline differs in males and females. .................................................................. Figure 15. Schematic representation of the synaptonemal complex at different stages during Prophase I. ........................................................................................................................................... Figure 16. Sex differentiation of the female germ cells. ..................................................................... Figure 17. Schematic representation of the ovary structure and follicle stages ................................ Figure 18. Schematic representation of male gonad differentiation .................................................. Figure 19. A model showing Sry regulation in mouse ......................................................................... Figure 20. Sox9 is the central element triggering the differentiation of male gonad ........................ Figure 21. Schematic representation of main cell types in testis ....................................................... Figure 22. Differentiation of a diploid human germ cell into a fully functional spermatozoon ......... Figure 23. Summary of critical time points, epigenetics events and the key factors involved during histone-to-protamine transition ......................................................................................................... Figure 24. Schematic representation of evolution from normal prostate to pre-malignant and cancerous states. ................................................................................................................................. Figure 25. Major cell types found in the prostate............................................................................... Figure 26. Hematopoietic stem cell generation in the P-Sp/AGM. ..................................................... Figure 27. Chlordecone three-dimensional structure. ........................................................................ Figure 28. Overview of DNA and RNA library preparation.................................................................. Figure 29. Illumina® cluster generation by bridge amplification ........................................................ Figure 30. Structure of a fastq file ....................................................................................................... Figure 31. FastQC provides several metrics to evaluate quality of the sequencing data. .................. Figure 32. The Burrows-Wheeler transform of a text is a permutation of this text. ..........................Figure 33. Command used to run the mapping step using TopHat. ...................................................Figure 34. Command line to count reads within genes using HTSeq. .................................................Figure 35. Comparison between RPKM/FPKM and TPM metrics. ...................................................... Figure 36. An overview of the DESeq2 read count normalization process. ........................................Figure 37. Example of an R code to perform differential gene analysis using DESeq2. .....................Figure 38. Command line to perform mapping using Bowtie2. .......................................................... Figure 39. Overview of the pre-processing and peak calling steps performed by MACS2. ................Figure 40. Process performed by MACS2 to adjust reads location and assess original fragment position ................................................................................................................................................Figure 41. Command used for bam to bedgraph convertion using bedtools. ....................................Figure 42. Python script to perform the normalization of bedgraph files. .........................................Figure 43. Python script used to quantify peak intensity. ..................................................................

Figure 38 .

 38 Figure 1. Double helix structure of the DNA and detailed nucleotide structures. ...............................Figure 2. The major structure of DNA ................................................................................................... Figure 3. Chromosomes are composed of DNA tightly-wound around histones .................................Figure 4. Summary of the different partitions of the human genome ................................................. Figure 5. DNA repair pathways ............................................................................................................. Figure 6. Types of point mutations .......................................................................................................Figure 7. Different types of large structural variants.. ..........................................................................Figure 8. A schematic representation of the domain structure of human DNMT isoforms .................Figure 9. Overview of DNA methylation and demethylation ................................................................Figure 10. DNA methylation at promoters regulates transcription binding and subsequent transcription .......................................................................................................................................... Figure 11. Transcriptional dynamics during pre-implantation embryo in mouse ................................ Figure 12. DNA methylation reprogramming in development. ............................................................ Figure 13. Development of the genital ridge from the coelomic epithelium ..................................... Figure 14. Meiosis timeline differs in males and females. .................................................................. Figure 15. Schematic representation of the synaptonemal complex at different stages during Prophase I. ........................................................................................................................................... Figure 16. Sex differentiation of the female germ cells. ..................................................................... Figure 17. Schematic representation of the ovary structure and follicle stages ................................ Figure 18. Schematic representation of male gonad differentiation .................................................. Figure 19. A model showing Sry regulation in mouse ......................................................................... Figure 20. Sox9 is the central element triggering the differentiation of male gonad ........................ Figure 21. Schematic representation of main cell types in testis ....................................................... Figure 22. Differentiation of a diploid human germ cell into a fully functional spermatozoon ......... Figure 23. Summary of critical time points, epigenetics events and the key factors involved during histone-to-protamine transition ......................................................................................................... Figure 24. Schematic representation of evolution from normal prostate to pre-malignant and cancerous states. ................................................................................................................................. Figure 25. Major cell types found in the prostate............................................................................... Figure 26. Hematopoietic stem cell generation in the P-Sp/AGM. ..................................................... Figure 27. Chlordecone three-dimensional structure. ........................................................................ Figure 28. Overview of DNA and RNA library preparation.................................................................. Figure 29. Illumina® cluster generation by bridge amplification ........................................................ Figure 30. Structure of a fastq file ....................................................................................................... Figure 31. FastQC provides several metrics to evaluate quality of the sequencing data. .................. Figure 32. The Burrows-Wheeler transform of a text is a permutation of this text. ..........................Figure 33. Command used to run the mapping step using TopHat. ...................................................Figure 34. Command line to count reads within genes using HTSeq. .................................................Figure 35. Comparison between RPKM/FPKM and TPM metrics. ...................................................... Figure 36. An overview of the DESeq2 read count normalization process. ........................................Figure 37. Example of an R code to perform differential gene analysis using DESeq2. .....................Figure 38. Command line to perform mapping using Bowtie2. .......................................................... Figure 39. Overview of the pre-processing and peak calling steps performed by MACS2. ................Figure 40. Process performed by MACS2 to adjust reads location and assess original fragment position ................................................................................................................................................Figure 41. Command used for bam to bedgraph convertion using bedtools. ....................................Figure 42. Python script to perform the normalization of bedgraph files. .........................................Figure 43. Python script used to quantify peak intensity. ..................................................................

Figure 40 .

 40 Figure 1. Double helix structure of the DNA and detailed nucleotide structures. ...............................Figure 2. The major structure of DNA ................................................................................................... Figure 3. Chromosomes are composed of DNA tightly-wound around histones .................................Figure 4. Summary of the different partitions of the human genome ................................................. Figure 5. DNA repair pathways ............................................................................................................. Figure 6. Types of point mutations .......................................................................................................Figure 7. Different types of large structural variants.. ..........................................................................Figure 8. A schematic representation of the domain structure of human DNMT isoforms .................Figure 9. Overview of DNA methylation and demethylation ................................................................Figure 10. DNA methylation at promoters regulates transcription binding and subsequent transcription .......................................................................................................................................... Figure 11. Transcriptional dynamics during pre-implantation embryo in mouse ................................ Figure 12. DNA methylation reprogramming in development. ............................................................ Figure 13. Development of the genital ridge from the coelomic epithelium ..................................... Figure 14. Meiosis timeline differs in males and females. .................................................................. Figure 15. Schematic representation of the synaptonemal complex at different stages during Prophase I. ........................................................................................................................................... Figure 16. Sex differentiation of the female germ cells. ..................................................................... Figure 17. Schematic representation of the ovary structure and follicle stages ................................ Figure 18. Schematic representation of male gonad differentiation .................................................. Figure 19. A model showing Sry regulation in mouse ......................................................................... Figure 20. Sox9 is the central element triggering the differentiation of male gonad ........................ Figure 21. Schematic representation of main cell types in testis ....................................................... Figure 22. Differentiation of a diploid human germ cell into a fully functional spermatozoon ......... Figure 23. Summary of critical time points, epigenetics events and the key factors involved during histone-to-protamine transition ......................................................................................................... Figure 24. Schematic representation of evolution from normal prostate to pre-malignant and cancerous states. ................................................................................................................................. Figure 25. Major cell types found in the prostate............................................................................... Figure 26. Hematopoietic stem cell generation in the P-Sp/AGM. ..................................................... Figure 27. Chlordecone three-dimensional structure. ........................................................................ Figure 28. Overview of DNA and RNA library preparation.................................................................. Figure 29. Illumina® cluster generation by bridge amplification ........................................................ Figure 30. Structure of a fastq file ....................................................................................................... Figure 31. FastQC provides several metrics to evaluate quality of the sequencing data. .................. Figure 32. The Burrows-Wheeler transform of a text is a permutation of this text. ..........................Figure 33. Command used to run the mapping step using TopHat. ...................................................Figure 34. Command line to count reads within genes using HTSeq. .................................................Figure 35. Comparison between RPKM/FPKM and TPM metrics. ...................................................... Figure 36. An overview of the DESeq2 read count normalization process. ........................................Figure 37. Example of an R code to perform differential gene analysis using DESeq2. .....................Figure 38. Command line to perform mapping using Bowtie2. .......................................................... Figure 39. Overview of the pre-processing and peak calling steps performed by MACS2. ................Figure 40. Process performed by MACS2 to adjust reads location and assess original fragment position ................................................................................................................................................Figure 41. Command used for bam to bedgraph convertion using bedtools. ....................................Figure 42. Python script to perform the normalization of bedgraph files. .........................................Figure 43. Python script used to quantify peak intensity. ..................................................................

Figure 42 .

 42 Figure 1. Double helix structure of the DNA and detailed nucleotide structures. ...............................Figure 2. The major structure of DNA ................................................................................................... Figure 3. Chromosomes are composed of DNA tightly-wound around histones .................................Figure 4. Summary of the different partitions of the human genome ................................................. Figure 5. DNA repair pathways ............................................................................................................. Figure 6. Types of point mutations .......................................................................................................Figure 7. Different types of large structural variants.. ..........................................................................Figure 8. A schematic representation of the domain structure of human DNMT isoforms .................Figure 9. Overview of DNA methylation and demethylation ................................................................Figure 10. DNA methylation at promoters regulates transcription binding and subsequent transcription .......................................................................................................................................... Figure 11. Transcriptional dynamics during pre-implantation embryo in mouse ................................ Figure 12. DNA methylation reprogramming in development. ............................................................ Figure 13. Development of the genital ridge from the coelomic epithelium ..................................... Figure 14. Meiosis timeline differs in males and females. .................................................................. Figure 15. Schematic representation of the synaptonemal complex at different stages during Prophase I. ........................................................................................................................................... Figure 16. Sex differentiation of the female germ cells. ..................................................................... Figure 17. Schematic representation of the ovary structure and follicle stages ................................ Figure 18. Schematic representation of male gonad differentiation .................................................. Figure 19. A model showing Sry regulation in mouse ......................................................................... Figure 20. Sox9 is the central element triggering the differentiation of male gonad ........................ Figure 21. Schematic representation of main cell types in testis ....................................................... Figure 22. Differentiation of a diploid human germ cell into a fully functional spermatozoon ......... Figure 23. Summary of critical time points, epigenetics events and the key factors involved during histone-to-protamine transition ......................................................................................................... Figure 24. Schematic representation of evolution from normal prostate to pre-malignant and cancerous states. ................................................................................................................................. Figure 25. Major cell types found in the prostate............................................................................... Figure 26. Hematopoietic stem cell generation in the P-Sp/AGM. ..................................................... Figure 27. Chlordecone three-dimensional structure. ........................................................................ Figure 28. Overview of DNA and RNA library preparation.................................................................. Figure 29. Illumina® cluster generation by bridge amplification ........................................................ Figure 30. Structure of a fastq file ....................................................................................................... Figure 31. FastQC provides several metrics to evaluate quality of the sequencing data. .................. Figure 32. The Burrows-Wheeler transform of a text is a permutation of this text. ..........................Figure 33. Command used to run the mapping step using TopHat. ...................................................Figure 34. Command line to count reads within genes using HTSeq. .................................................Figure 35. Comparison between RPKM/FPKM and TPM metrics. ...................................................... Figure 36. An overview of the DESeq2 read count normalization process. ........................................Figure 37. Example of an R code to perform differential gene analysis using DESeq2. .....................Figure 38. Command line to perform mapping using Bowtie2. .......................................................... Figure 39. Overview of the pre-processing and peak calling steps performed by MACS2. ................Figure 40. Process performed by MACS2 to adjust reads location and assess original fragment position ................................................................................................................................................Figure 41. Command used for bam to bedgraph convertion using bedtools. ....................................Figure 42. Python script to perform the normalization of bedgraph files. .........................................Figure 43. Python script used to quantify peak intensity. ..................................................................

Figure 44 .

 44 Figure 44. R function used to filtrer data and identify differential peaks. .......................................... Figure 45. Overview of GREAT method to assign genes and functions to differential peaks. ............ Figure 46. The MEME Suite provided numerous tools to performed motif-based sequence analysis, including de novo motif discovery or motif scanning. ........................................................................Figure 47. Command line to map reads using bwa. ............................................................................Figure 48. Bash script to run the preprocessing of bam files using Picard prior variant calling. ........Figure 49. Bash script to perform BQSR and variant calling. ..............................................................Figure 50. Bash script to combine gVCF into multi-samples VCF and convert it into regular VCF. ....Figure 51. Bash script to perform SNPs and indels VQSR. ..................................................................Figure 52. Bash script to perform the annotation of the variants using VEP. .................................... Figure 53. Bar plot of the total number of variants detected for each child in the cohort ................ Figure 54. Bar plot of the total number of variants detected on the X chromosome ........................ Figure 55. Mutational signature of CD exposure based on de novo variants identified on X chromosome. ...................................................................................................................................... Figure 56. Comparison of the average number of de novo variants in GSTM1+/+ and GSTM1-/children. ...............................................................................................................................................

Figure 47 .

 47 Figure 44. R function used to filtrer data and identify differential peaks. .......................................... Figure 45. Overview of GREAT method to assign genes and functions to differential peaks. ............ Figure 46. The MEME Suite provided numerous tools to performed motif-based sequence analysis, including de novo motif discovery or motif scanning. ........................................................................Figure 47. Command line to map reads using bwa. ............................................................................Figure 48. Bash script to run the preprocessing of bam files using Picard prior variant calling. ........Figure 49. Bash script to perform BQSR and variant calling. ..............................................................Figure 50. Bash script to combine gVCF into multi-samples VCF and convert it into regular VCF. ....Figure 51. Bash script to perform SNPs and indels VQSR. ..................................................................Figure 52. Bash script to perform the annotation of the variants using VEP. .................................... Figure 53. Bar plot of the total number of variants detected for each child in the cohort ................ Figure 54. Bar plot of the total number of variants detected on the X chromosome ........................ Figure 55. Mutational signature of CD exposure based on de novo variants identified on X chromosome. ...................................................................................................................................... Figure 56. Comparison of the average number of de novo variants in GSTM1+/+ and GSTM1-/children. ...............................................................................................................................................

Figure 48 .

 48 Figure 44. R function used to filtrer data and identify differential peaks. .......................................... Figure 45. Overview of GREAT method to assign genes and functions to differential peaks. ............ Figure 46. The MEME Suite provided numerous tools to performed motif-based sequence analysis, including de novo motif discovery or motif scanning. ........................................................................Figure 47. Command line to map reads using bwa. ............................................................................Figure 48. Bash script to run the preprocessing of bam files using Picard prior variant calling. ........Figure 49. Bash script to perform BQSR and variant calling. ..............................................................Figure 50. Bash script to combine gVCF into multi-samples VCF and convert it into regular VCF. ....Figure 51. Bash script to perform SNPs and indels VQSR. ..................................................................Figure 52. Bash script to perform the annotation of the variants using VEP. .................................... Figure 53. Bar plot of the total number of variants detected for each child in the cohort ................ Figure 54. Bar plot of the total number of variants detected on the X chromosome ........................ Figure 55. Mutational signature of CD exposure based on de novo variants identified on X chromosome. ...................................................................................................................................... Figure 56. Comparison of the average number of de novo variants in GSTM1+/+ and GSTM1-/children. ...............................................................................................................................................

Figure 49 .

 49 Figure 44. R function used to filtrer data and identify differential peaks. .......................................... Figure 45. Overview of GREAT method to assign genes and functions to differential peaks. ............ Figure 46. The MEME Suite provided numerous tools to performed motif-based sequence analysis, including de novo motif discovery or motif scanning. ........................................................................Figure 47. Command line to map reads using bwa. ............................................................................Figure 48. Bash script to run the preprocessing of bam files using Picard prior variant calling. ........Figure 49. Bash script to perform BQSR and variant calling. ..............................................................Figure 50. Bash script to combine gVCF into multi-samples VCF and convert it into regular VCF. ....Figure 51. Bash script to perform SNPs and indels VQSR. ..................................................................Figure 52. Bash script to perform the annotation of the variants using VEP. .................................... Figure 53. Bar plot of the total number of variants detected for each child in the cohort ................ Figure 54. Bar plot of the total number of variants detected on the X chromosome ........................ Figure 55. Mutational signature of CD exposure based on de novo variants identified on X chromosome. ...................................................................................................................................... Figure 56. Comparison of the average number of de novo variants in GSTM1+/+ and GSTM1-/children. ...............................................................................................................................................

Figure 50 .

 50 Figure 44. R function used to filtrer data and identify differential peaks. .......................................... Figure 45. Overview of GREAT method to assign genes and functions to differential peaks. ............ Figure 46. The MEME Suite provided numerous tools to performed motif-based sequence analysis, including de novo motif discovery or motif scanning. ........................................................................Figure 47. Command line to map reads using bwa. ............................................................................Figure 48. Bash script to run the preprocessing of bam files using Picard prior variant calling. ........Figure 49. Bash script to perform BQSR and variant calling. ..............................................................Figure 50. Bash script to combine gVCF into multi-samples VCF and convert it into regular VCF. ....Figure 51. Bash script to perform SNPs and indels VQSR. ..................................................................Figure 52. Bash script to perform the annotation of the variants using VEP. .................................... Figure 53. Bar plot of the total number of variants detected for each child in the cohort ................ Figure 54. Bar plot of the total number of variants detected on the X chromosome ........................ Figure 55. Mutational signature of CD exposure based on de novo variants identified on X chromosome. ...................................................................................................................................... Figure 56. Comparison of the average number of de novo variants in GSTM1+/+ and GSTM1-/children. ...............................................................................................................................................

Figure 51 .

 51 Figure 44. R function used to filtrer data and identify differential peaks. .......................................... Figure 45. Overview of GREAT method to assign genes and functions to differential peaks. ............ Figure 46. The MEME Suite provided numerous tools to performed motif-based sequence analysis, including de novo motif discovery or motif scanning. ........................................................................Figure 47. Command line to map reads using bwa. ............................................................................Figure 48. Bash script to run the preprocessing of bam files using Picard prior variant calling. ........Figure 49. Bash script to perform BQSR and variant calling. ..............................................................Figure 50. Bash script to combine gVCF into multi-samples VCF and convert it into regular VCF. ....Figure 51. Bash script to perform SNPs and indels VQSR. ..................................................................Figure 52. Bash script to perform the annotation of the variants using VEP. .................................... Figure 53. Bar plot of the total number of variants detected for each child in the cohort ................ Figure 54. Bar plot of the total number of variants detected on the X chromosome ........................ Figure 55. Mutational signature of CD exposure based on de novo variants identified on X chromosome. ...................................................................................................................................... Figure 56. Comparison of the average number of de novo variants in GSTM1+/+ and GSTM1-/children. ...............................................................................................................................................

Figure 52 .

 52 Figure 44. R function used to filtrer data and identify differential peaks. .......................................... Figure 45. Overview of GREAT method to assign genes and functions to differential peaks. ............ Figure 46. The MEME Suite provided numerous tools to performed motif-based sequence analysis, including de novo motif discovery or motif scanning. ........................................................................Figure 47. Command line to map reads using bwa. ............................................................................Figure 48. Bash script to run the preprocessing of bam files using Picard prior variant calling. ........Figure 49. Bash script to perform BQSR and variant calling. ..............................................................Figure 50. Bash script to combine gVCF into multi-samples VCF and convert it into regular VCF. ....Figure 51. Bash script to perform SNPs and indels VQSR. ..................................................................Figure 52. Bash script to perform the annotation of the variants using VEP. .................................... Figure 53. Bar plot of the total number of variants detected for each child in the cohort ................ Figure 54. Bar plot of the total number of variants detected on the X chromosome ........................ Figure 55. Mutational signature of CD exposure based on de novo variants identified on X chromosome. ...................................................................................................................................... Figure 56. Comparison of the average number of de novo variants in GSTM1+/+ and GSTM1-/children. ...............................................................................................................................................

Table 1 .

 1 Similarity between human and mouse genomes .................................................................... Table 2. Very large conserved genes play an important role in cancer development ......................... Table 3. Genes in DNA damage repair pathways that are hypermethylated in cancers.. .................... Table 4. Summary of the combined chromatin state types .................................................................. Table

  .......................................... Table 7. Physical and chemical properties of chlordecone. ................................................................ Table 8. Online tools to characterize the genomic regions or list of genes. ....................................... Table 9. Main functions of genes affected by potentially deleterious rare variants in children exposed to high level of CD. .............................................................................................................................. Table

1 .

 1 Bipotential gonad development and germ cell specification ......................................................................... 2. Female sex-determination pathway .............................................................................................................. 3. Ovary function in adulthood .......................................................................................................................... 4. Male sex determination pathway .................................................................................................................. 5. Testis functions in the adulthood ................................................................................................................... B. Prostate ............................................................................................................................................. 1. Embryonic development of the prostate ....................................................................................................... 2. Structure and function of the prostate .......................................................................................................... I. SUPPLEMENTARY INFORMATION -ARTICLE 1 ................................................................................................... II. SUPPLEMENTARY INFORMATION -ARTICLE 2 ................................................................................................... III. SUPPLEMENTARY INFORMATION -ARTICLE 3 ................................................................................................... IV. SUPPLEMENTARY INFORMATION -ARTICLE 4 ................................................................................................... V. SCIENTIFIC PRODUCTION ...............................................................................................................................

  premières données toxicologiques du CD ont été rapportées dans le dossier d'enregistrement du CD considéré comme pesticide au début des années 1960. Elles soulignaient que l'administration par voie orale du CD à des rats de laboratoire provoque des troubles neurologiques caractérisés par des tremblements ainsi qu'une atrophie testiculaire. Les observations cliniques réalisées chez les travailleurs de l'usine d'Hopewell ont entrainé la mise en place, à partir de la seconde moitié des années 1970, d'études toxicologiques sur le CD via l'utilisation de modèles animaux ainsi que d'essais in vitro. Ces travaux ont permis de classifier cette molécule comme potentiellement cancérogène pour l'Homme (catégorie 2B), puisque les rongeurs de laboratoires exposés au CD développaient des lésions hépatiques tumorales. La nature reprotoxique du CD a également été confirmée par des procédures expérimentales. Enfin, d'autres travaux ont également permis de révéler ses propriétés oestrogéniques, qui en font un perturbateur endocrinien. En effet, le CD est capable de lier le récepteur aux oestrogènes ERα et ERβ. Malgré l'interdiction sur le territoire américain, la France a poursuivi la production et l'autorisation d'utilisation du CD dans les bananeraies des Antilles françaises jusqu'en 1993.

  phologie d'ovaires, de testicules et de prostates de souris. Pour cela, les organes furent fixés dans une solution de Bouin puis enrobés dans de la paraffine avant d'être préparés en sections de 5µm d'épaisseur. Les sections furent ensuite marquées à l'hématoxyline et à l'éosine, ou immun-marquées, avant d'être observées en microscopie. Ces analyses morphologiques des tissus chez les animaux adules ont été accompagnées d'analyses en immunohistochimie sur des étalements de cellules afin d'évaluer la quantité de diverses marques épigénétiques. Nous avons également réalisé des immunomarquages sur des noyaux de cellules dont la structure tri-dimensionnelle était préservée. Ces marquages furent réalisés à partir de cellules isolées d'animaux adultes ou d'embryons. De même, nous avons réalisé les mêmes marquages sur de cellules nucléées provenant du sang de cordon ombilical des individus de la cohorte TI-MOUN. Afin de déterminer si les altérations observées au niveau protéique et morphologique résultaient d'une dérégulation de la transcription, nous avons étudié les niveaux d'expression d'un certain nombre de gènes, voire de l'ensemble du transcriptome. Pour cela, suite à l'extraction des ARN totaux à partir de l'organe d'intérêt, nous avons, soit préparé les ADNc et quantifié leur niveau par PCR quantitative lorsque nous souhaitions étudier un nombre restreint de gènes, ou bien nous avons préparé des librairies et réalisé un séquençage à hautdébit (RNA-seq) lorsque nous voulions obtenir un aperçu général du transcriptome (dans la prostate et le testicule murin).

A

  . Effets transgénérationnels induits par le chlordécone dans le testicule Au cours de ces travaux, des souris gestantes non consanguines ont été exposées entre E6,5 et E15,5 à une dose de CD de 100 µg/kg pc/jour, une dose inférieure à la LOAEL (lowest-observed-adverse-effect level), la dose la plus faible pour laquelle sont observés des effets indésirables, définie à 250 µg/kg pc/jour. Les descendants mâles de femelles F0 (souris gestantes ayant reçu le CD) ont été définis comme F1 et ont été croisés avec des femelles non traitées pour donner naissance à la génération F2. De même, la progéniture mâle de F2 a été croisée avec des femelles non-traitées pour donner naissance à la génération F3. Nous avons observé une diminution significative du nombre de spermatogonies chez les mâles F3 issus des souris exposées au CD, mais cet effet n'a pas été retrouvé chez les mâles F1 directement exposés au cours de leur développement. Dans le but de déterminer si l'exposition pouvait entrainer un changement du nombre de spermatozoïdes, nous avons compté les spermatozoïdes dans l'épididyme des mâles F1 et F3. Nous avons constaté que le nombre de spermatozoïdes a été réduit de 30% dans les deux générations. Ces résultats confirment les propriétés reprotoxiques du CD, qui semblent néanmoins plus délétères que ceux rapportés chez les travailleurs d'Hopewell exposé au cours de leur vie adulte. Afin de déterminer si le CD est capable d'affecter les processus de différenciation clés au cours de la gamétogénèse et de la méiose, nous avons immuno-marqué des coupes de testicules (F1 et F3) contre les protéines du complexe synaptonémal, et nous avons ainsi analysé l'appariement des chromosomes homologues au cours du stade pachytène de la méiose. L'analyse des spermatocytes dans les générations F1 et F3 a révélé une augmentation du nombre d'appariements incorrects présentant certaines caractéristiques telles que des connexions interchromosomiques via les télomères, des appariements incomplets, ou la circularisation des chromosomes X et Y, chez les animaux descendants des souris exposées. Ces défauts méiotiques étaient accompagnés d'une augmentation de nombre de foyers de DMC1, la recombinase facilitant la recherche d'un chromosome homologue suite à une DSB, suggérant que les mésappariements chromosomiques pourraient résulter d'une réparation inefficace de l'ADN. Pour vérifier si l'exposition au CD peut induire des changements d'expression génique, nous avons ensuite effectué une PCR quantitative à partir d'ARN extraits des testicules foetaux à E15,5. Nous avons notamment constaté une réduction de l'expression de plusieurs gènes impliqués dans la division cellulaire (Zfr, Prim2, Tnks). De plus, nous avons révélé une diminution d'expression de Pou5f1, l'un des facteurs de transcription clé impliqué dans la pluripotence. Dans le but de révéler le mécanisme moléculaire de l'action du CD, nous avons ensuite étudié l'expression des gènes dans les testicules des souris mâles F1 et F3 à l'âge adulte. Nous avons constaté que l'expression de gènes impliqués dans le contrôle de la division cellulaire, y compris Ccne2, Tnks et Prim2, était modifiée dans les deux générations. Nous avons aussi observé chez les mâles F1 une augmentation de l'expression de Pou5f1 ainsi qu'une diminution de Zfp57, un répresseur transcriptionnel clé impliqué le silençage des gènes soumis à l'empreinte parentale. L'analyse transcriptomique chez les mâles F3 n'a, néanmoins, pas révélé de changement d'expression pour ces deux gènes bien que plus de 370 étaient dérégulés, notamment des gènes impliqués dans la division cellulaire, la ségrégation et l'appariement des chromosomes ainsi que la réparation de l'ADN.

Finalement

  , afin de comprendre si les changements épigénétiques observés dans la prostate des souris F1 sont préservés dans le sperme de ces mêmes souris, nous avons analysé les niveaux de H3K4me3 par ChIP-qPCR. Les régions que nous avons ciblées étaient enrichies en H3K4me3, suggérant qu'elles préservaient des histones qui ne sont pas remplacées par des protamines. Ces régions sont par conséquent susceptibles d'être responsable de la transmission d'informations épigénétiques à la génération suivante. De manière surprenante, nous avons observé que les niveaux de H3K4me3 sont globalement diminués au niveau des loci étudiés, contrairement à ceux observés dans la prostate. Pris dans leur ensemble, nos résultats suggèrent que l'exposition au CD au cours du développement est susceptible d'induire des changements épigénétiques dans différents organes, et que ces altérations déclenchent une cascade d'événements pouvant aboutir à l'apparition de phénotypes potentiellement délétères. De plus, nos données suggèrent que ces altérations peuvent être transmises jusqu'à trois générations après l'exposition initiale, la transmission des informations pouvant être médiée d'une génération à la suivante à travers le sperme.

Figure 1 .

 1 Figure 1. Double helix structure of the DNA and detailed nucleotide structures. From Open Oregon website (https://openoregon.pressbooks.pub/).

Figure 2 .

 2 Figure 2. The major structure of DNA. Cytosines are displayed in yellow, Guanine in cyan, Thymine in green and Adenine in red. A-DNA and B-DNA are both right-handed uniform double-helical structures, while Z-DNA is a left-handed double helix with a dinucleotide repeat and the backbone follows a zigzag path. From[START_REF] Ghosh | A glossary of DNA structures from A to Z[END_REF].

Figure 3 .

 3 Figure 3. Chromosomes are composed of DNA tightly-wound around histones. From (Annunziato, 2008).

Figure 4 .

 4 Figure 4. Summary of the different partitions of the human genome. The data are from the International Human Genome Sequencing Consortium. From (Gregory, 2005).

Figure 5 .

 5 Figure 5. DNA repair pathways. From Abcam website (https://www.abcam.com/).

  sion. A transition is the substitution of a purine by another purine (A<->G), or a pyrimidine by the other pyrimidine (T<->C). Transitions are the most common mutations. A transversion exchanges a purine for a pyrimidine, or a pyrimidine for a purine (C/T<->A/G). When a point mutation occurs in the coding sequence of a gene, it can be further classified based on its impact on the protein sequence. As the genetic code is degenerated, several codons encode for the same amino acid. A point mutation which does not alter primary protein sequence is said to be synonymous or silent if there are no observed phenotypic effects. Therefore, a nonsynonymous substitution leads to modification of the encoded amino acid. These substitutions are subsequently split into two groups: missense and nonsense mutations. Nonsense substitutions induce the change from an amino acid-encoding codon to a STOP codon, triggering the truncation of the protein. Depending on the location of this type of substitution, it can lead to a loss-of-function (LOF). Missense mutations result from a substitution changing the encoded amino acid. This change can have a low impact on the protein if the two amino acids are chemically close (e.g., arginine and lysine) and related to the three-dimensional structuration of the protein. In some other cases, missense mutation can have a more profound effect, especially if the amino acid concerned by the substitution is located within the active site of an enzyme.

Figure 6 .

 6 Figure 6. Types of point mutations. From (https://saylordotorg.github.io/).

Figure 8 .

 8 Figure 8. A schematic representation of the domain structure of human DNMT isoforms. Nterm domains: ADD (interaction with histones), NLS (nuclear localization signal), CXXC (link to zinc-finger proteins), BAH (interaction with chromatin remodelers), RFTD (recruitment of DNMT1 to replicative fork), PWWP (recognition of specific amino-acid -chromatin targeting of the enzymes). From[START_REF] Maresca | DNA methyltransferase 1 mutations and mitochondrial pathology: is mtDNA methylated? Front[END_REF].

Figure 11 .

 11 Figure11. Transcriptional dynamics during pre-implantation embryo in mouse. From[START_REF] Fu | Endogenous Retroviruses Function as Gene Expression Regulatory Elements During Mammalian Pre-implantation Embryo Development[END_REF].

3 '

 3 portion of the cleaved transcript serves for production of other piRNAs. An endonuclease, Zuc (Zucchini), cleaves the piRNAs into 25 nucleotide-long consecutive pieces. The loading of piRNAs into PIWI relies on Shu (Shutdown) and Hsp90, and triggers a conformational change of Piwi, that allows its translocation into the nucleus. The binding of Aub with an antisense piRNA allows recognition and cleavage of transposon mRNA. The 3' fragment resulting from the cleavage is then converted into a new sense piRNA, which associates with Ago3. The complex formed by Ago3 and sense piRNA can then recognize and cleave the transcripts resulting from the cluster, and so on with the new fragments resulting from the cleavage.

Figure 12 .

 12 Figure 12. DNA methylation reprogramming in development. From (Greenberg and Bourc'his, 2019).

  first division, called meiosis I, is preceded by a replication phase. This division allows the separation of homologous chromosomes. The second division, meiosis II, allows for the separation of the sister chromatids of each chromosome. Meiosis results in the formation of haploid gametes, the oocyte in the female and the spermatozoid in the male.Meiosis allows an important genetic shuffling of parental genomes and is the main vector of evolution. The first level of this shuffling concerns the random distribution of the parental chromosomes between the daughter cells during meiosis I. This random distribution makes it possible to generate in humans (for 23 chromosomes), 8.3 million combinations of different gametes! In addition, during prophase I, homologous chromosomes must be physically connected in pairs in order to allow their correct distribution in the two daughter cells. This connection is made possible by the introduction of DNA double strand breaks and their repair by the homologous recombination system. The use of this repair system induces reciprocal exchanges between the chromatids of homologous chromosomes of maternal and paternal origin. These exchanges of genetic material are called crossing-over and are a very important source of genetic diversity. Usually, one to three crossovers per chromosomes is generated during HR.

Figure 14 .

 14 Figure 14. Meiosis timeline differs in males and females. From (Bolcun-Filas and Handel, 2018).

Figure 15 .

 15 Figure 15. Schematic representation of the synaptonemal complex at different stages during Prophase I. From (Wells, 2020).

Figure 16 .

 16 Figure 16. Sex differentiation of the female germ cells. From (Nicol and Yao, 2018).

Figure 17 .

 17 Figure 17. Schematic representation of the ovary structure and follicle stages. From[START_REF] Desai | Female and Male Gametogenesis[END_REF]

Figure 18 .

 18 Figure 18. Schematic representation of male gonad differentiation. From (Allais-Bonnet and Pailhoux, 2014).

  and the tunica vasculosa. The tunica albuginea forms most of the testicular capsule and is made up of collagen, elastic fibers and fibroblasts. The parenchyma of the testis is divided into several testicular lobes by the septa, and each lobe includes the seminiferous tubules. The walls of the seminiferous tubules are composed of a basement membrane, containing peritubular myoid cells, which display a contractile function needed for sperm progression in the tubules. The seminiferous tubules interlace compactly and aggregate at the level of the rete testis. A set of numerous tubules forms a structure called testicular lobule.Seminiferous tubules are formed from the testicular cords and are composed of three cell types: germ cells, Sertoli cells and peritubular cells (Figure21). Between the Sertoli cells are located spermatogenic cells which undergo meiosis to differentiate into spermatozoa. Sertoli cells express AR that allows an increase of intra-tubular concentration of testosterone.They also express growth and regulation factors required for the spermatogenesis; they are therefore considered to be the supportive cells of the spermatogenesis. During spermatogenesis, germinal and Sertoli cells undergo profound structural changes.

Figure 21 .

 21 Figure21. Schematic representation of main cell types in testis. From[START_REF] Loveland | Cytokines in Male Fertility and Reproductive Pathologies: Immunoregulation and Beyond[END_REF].

Figure 22 .

 22 Figure 22. Differentiation of a diploid human germ cell into a fully functional spermatozoon.From[START_REF] Desai | Female and Male Gametogenesis[END_REF].

Figure 23 .

 23 Figure 23. Summary of critical time points, epigenetics events and the key factors involved during histone-to-protamine transition. From (Wang et al., 2019).

Figure 26 .

 26 Figure26. Hematopoietic stem cell generation in the P-Sp/AGM. From[START_REF] Godin | Kaufman's Atlas of Mouse Development Supplement[END_REF].

  CD was introduced in the American market in 1958, under the commercial names of Kepone® and GC-1189, by Allied Chemicals. From the first synthesis of CD in 1951, by Gilbert and Giolito, and the end of production in 1975, approximately 1.6 million kg of CD were produced in the United States

  It is therefore necessary to understand the underlying molecular mechanisms contributing to this by carrying out studies in animal models. Context, Hypothesis and Objectives 156 The work presented in this manuscript is the result of three years of work carried out at Irset (Institut de Recherche en Santé, Environnement et Travail) in the Meiosis, Epigenetics and Reproduction (MER) team, under the direction of Dr. Fatima Smagulova.

Figure 28 .

 28 Figure 28. Overview of DNA and RNA library preparation. From New-England Biolabs website (https://international.neb.com/).

Figure 31 .

 31 Figure 31. FastQC provides several metrics to evaluate quality of the sequencing data.

Figure 32 .

 32 Figure 32. The Burrows-Wheeler transform of a text is a permutation of this text.

Figure 33 .

 33 Figure 33. Command used to run the mapping step using TopHat.

Figure 34 .

 34 Figure 34. Command line to count reads within genes using HTSeq.

Figure 35 .

 35 Figure 35. Comparison between RPKM/FPKM and TPM metrics. For readability the "per million" factor is illustrated as "per hundred" in the figure.

Figure 36 .

 36 Figure 36. An overview of the DESeq2 read count normalization process.

Figure 37 .

 37 Figure 37. Example of an R code to perform differential gene analysis using DESeq2.

Figure 38 .

 38 Figure 38. Command line to perform mapping using Bowtie2.

Figure 39 .

 39 Figure 39. Overview of the pre-processing and peak calling steps performed by MACS2. Adapted from teaching material at the Harvard Chan Bioinformatics Core (https://github.com/hbctraining).

Figure 41 .

 41 Figure 41. Command used for bam to bedgraph convertion using bedtools.

Figure 42 .

 42 Figure 42. Python script to perform the normalization of bedgraph files.

Figure 43 .

 43 Figure 43. Python script used to quantify peak intensity.

Figure 43 .

 43 Figure 43. Python script used to quantify peak intensity (continued).

Figure 44 .

 44 Figure 44. R function used to filtrer data and identify differential peaks.

Figure 44 .

 44 Figure 44. R function used to filtrer data and identify differential peaks (continued).

Figure 45 .

 45 Figure45. Overview of GREAT method to assign genes and functions to differential peaks.

Figure 46 .

 46 Figure 46. The MEME Suite provided numerous tools to performed motif-based sequence analysis, including de novo motif discovery or motif scanning.

Figure 47 .

 47 Figure 47. Command line to map reads using bwa.

Figure 48 .

 48 Figure 48. Bash script to run the preprocessing of bam files using Picard prior variant calling.

Figure 49 .

 49 Figure 49. Bash script to perform BQSR and variant calling.

Figure 50 .

 50 Figure 50. Bash script to combine gVCF into multi-samples VCF and convert it into regular VCF.

Figure 51 .

 51 Figure 51. Bash script to perform SNPs and indels VQSR.

Figure 52 .

 52 Figure 52. Bash script to perform the annotation of the variants using VEP.

  -induced transgenerational inheritance in male somatic tissue, example of the prostate 260 III. Chlordecone-induced epigenetic alterations in female reproductive tissue 282 IV. Chlordecone-induced epigenetic alterations in Guadeloupean new-borns, example of the TIMOUN cohort 314 V. Chlordecone induces genetic alterations in TIMOUN newborns.

Figure 53 .

 53 Figure 53. Bar plot of the total number of variants detected for each child in the cohort (shown in flesh color). The proportion of rare variants in the general population with allele frequency below 0.01% is shown in a darker shade below. Blue triangle shows low CD levels, red circle shows high, and orange square shows medium CD levels in children.

Figure 54 .

 54 Figure 54. Bar plot of the total number of variants detected on the X chromosome (shown in flesh color). The proportion of de novo variants is shown in a darker shade below.

Figure 55 .

 55 Figure 55. Mutational signature of CD exposure based on de novo variants identified on X chromosome.

Figure 56 .

 56 Figure 56. Comparison of the average number of de novo variants in GSTM1+/+ and GSTM1-/-children.*p<0.05, Wilcoxon-Mann-Whitney test.

Table 2

 2

). Replication stress likely 57

Table 2 .

 2 Very large conserved genes play an important role in cancer development

	Murine Genes	Role of human analogues in cancer	References
	Pard3b	Loss of the function promotes breast tumorigene-	(McCaffrey et al., 2012)
		sis and metastasis.
	Erbb4	Over-expressed in human colon cancer and en-	(Kurppa et al., 2016; Williams et
		hances cellular transformation. Activating ERBB4	al., 2015)
		mutations are present in non-small cell lung can-
		cer.
	Ptprd	Loss of function leads to aberrant STAT3 activa-	(Molenaar et al., 2012; Ortiz et al.,
		tion and promotes gliomagenesis. Structural al-	2014)
		terations recurrently affected PTPRD in neurito-
		genesis.
	Magi2	Rearrangement of Magi2 is associated with pros-	(Berger et al., 2011)
		tate cancer.
	Kcnip4	Disrupted in renal cancer patients.	(Bonne et al., 2007)
	Auts2	A recurrent fusion gene in childhood B-cell pre-	(Denk et al., 2012)
		cursor acute lymphoblastic leukemia.
	Cntnap2	Tumor suppressor gene in glioma.	(Bralten et al., 2010)
	Ccser1	Deleted in malignant mesothelioma.	(Klorin et al., 2013)
	Grid2	Associated with development of osteonecrosis.	(Karol et al., 2016)
	Ctnna2	A tumor suppressor frequently mutated in laryn-	(Fanjul-Fernández et al., 2013)
		geal carcinomas.
	Csmd1	Loss of Csmd1 may contribute to the poor prog-	(Zhang and Song, 2014)
		nosis of colorectal cancer patients.
	Ctnna3	Displays tumor specific monoallelic expression in
		urothelial carcinoma of the bladder.

[START_REF] Meehan | Alpha-T-catenin (CTNNA3) displays tumour specific monoallelic expression in urothelial carcinoma of the bladder[END_REF]

  )

	Nrxn1	Three-way translocation involving MLL, MLLT1,	(Lee et al., 2010)
		and a novel third partner, NRXN1 was detected
		in a patient with acute lymphoblastic leukemia
		and t(2;19;11) (p12;p13.3;q23).

Table 4 .

 4 Summary of the combined chromatin state types. From (The ENCODE ProjectConsortium, 2012)

	Label	Description	Details
	CTCF	CTCF-enriched ele-	Sites matching to CTCF motif in general are lacking histone modi-
		ment		fications, and are often associated with open chromatin. Many sites
				are likely to function in insulators assays. They are also enriched in
				the cohesion components RAD21 and SMC3; CTCF is known to
				recruit the cohesion complex.
	E	Predicted enhanc-	Regions of open chromatin associated with H3K4me1 signal. They
		ers		are enriched in other enhancer-associated marks, including TFs
				known to act at enhancers. In enhancer assays, many of them
				(>50%) function as enhancers. A more conservative alternative
				would be cis-regulatory regions. Regions are enriched in sites for
				the proteins encoded by EP300, FOS, FOSL1, GATA2, HDAC8,
				JUNB, JUND, NFE2, SMARCA4, SMARCB1, SIRT6, and TAL1 in
				K562. The regions have nuclear and whole-cell RNA signal, partic-
				ularly poly A minus fraction.
	PF	Predicted promoter	Regions that are generally surrounding TSS segments.
		flanking region
	R	Predicted	Re-	This is a merged state that includes H3K27me3 polycomb-enriched
		pressed or Low Ac-	regions, along with regions that are silent in terms of observed sig-
		tivity region	nal for the input assays to the segmentations (low or no signal).
				They may have other signals (e.g., RNA, not in the segmentation
				input data). They enriched in sites for the proteins encoded by
				REST and some other factors (e.g. proteins encoded by BRF2, CE-
				BPB, MAFK, TRIM28, ZNF274, and SETDB1 genes in K562).
	TSS	Predicted promoter	They found close to or overlapping Gencode TSS sites, have high
		region	including	precision/recall for TSSs, enriched for H3K4me3. They are sites
		TSS		with open chromatin and enriched in TF known to act close to pro-
				moters and polymerases Pol II and Pol III. In these regions the short
				RNAs are most abundant.
	T	Predicted	tran-	They normally overlap the gene bodies with H3K36me3 transcrip-
		scribed region	tional elongation signal and enriched in phosphorylated form of Po-
				lII signal (elongating polymerase) and poly A-plus RNA, especially
				cytoplasmic.
	WE	Predicted weak en-	They are similar to the E state, but have weaker signals and weaker
		hancer or open	enrichments.
		chromatin cis regu-
		latory element

  Etudes des altérations épigénétiques promues par l'exposition au chlordécone au cours du développement chez l'homme et la souris Mots clés : épigénétique, héritage transgénérationnel, chlordécone, système reproducteur

	Genes	Biological process	Cluster
	CDC7	double-strand break repair via break-induced replication
	CHD2	transcription, DNA-templated
	HIST2H2AB	chromatin silencing
	RNF168 NUP107	double-strand break repair mRNA export from nucleus	chromosome organization
	PRIM2	DNA replication synthesis of RNA primer DNA replication
	ATF7IP	positive regulation of chromatin silencing
	JMJD1C	histone H3-K9 demethylation
	AFF1	regulation of transcription DNA-templated
	TAF12	DNA-templated transcription initiation
	GDF1	BMP signaling pathway
	RGMA	BMP signaling pathway	transcription factors and sig-
	SCYL1	regulation of transcription DNA-templated	nalling
	CTNNA3	cell-cell adhesion
	FRMD8	positive regulation of tumor necrosis factor secretion
	RFTN1	B cell receptor signaling pathway
	HARBI1	nucleic acid phosphodiester bond hydrolysis
	KLHL8	protein ubiquitination
	MANBA	carbohydrate metabolic process
	CHST1 SELENOP	keratan sulfate metabolic process selenium compound metabolic process	metabolic process
	AGA	proteolysis
	UBXN8	ubiquitin-dependent ERAD pathway
	TIMM21	mitochondrial respiratory chain complex I assembly
	PPFIBP1	neuromuscular junction development
	CRYBA4	camera-type eye development
	ADAMTS6	coronary vasculature development	development
	TBC1D7	response to growth factor
	ELP3	central nervous system development
	RPS12	rRNA processing translation
	CWC27	mRNA splicing
	FCF1 QRSL1	mRNA splicing mitochondrial translation	RNA processing
	CSTF3	polyadenylation of mRNA
	CSTF2T	pre-mRNA cleavage required for polyadenylation
	NECAP1	protein transport
	CYTH1 DNAH17	vesicle-mediated transport microtubule-based movement	transport
	DYNLRB1	microtubule-based movement
	ATG7	cellular response to nitrogen starvation
	VMP1 ATG13	autophagy autophagosome assembly	autophagy
	NRBF2	regulation of autophagy

Titre :

et TRIM28 étaient sur-représentés parmi les régions affectées par l'exposition au CD. Suite à l'observation de ces résultats, nous avons souhaité déterminer si le CD pouvait être responsable d'altération dans la population folliculaire ovarienne. Dans cet objectif, nous avons quantifié les follicules à chaque stade de la folliculogénèse à partir des ovaires de souris âgées de trois mois. L'analyse quantitative a révélé que les souris exposées au CD au cours de leur développement présentaient une diminution du nombre de follicules primordiaux et une augmentation du nombre de follicules atrétiques. Ces observations étaient accompagnées d'une diminution du niveau d'AMH, un marqueur d'évaluation de la réserve ovarienne, ainsi qu'une réduction de la masse ovarienne chez les souris exposées. Des analyses immunohistochimiques ont également révélé une augmentation de la marque histone γH2AX, un marqueur des DSBs, dans les ovaires de souris exposées. Ces DSBs pourraient être à l'origine de l'augmentation du nombre de follicules atrétiques. Ainsi, nos données suggèrent que l'exposition au CD au cours du développement est responsable d'une réduction du pool folliculaire et d'une altération de la folliculogénèse.La diminution du pool de follicules primordiaux laisse supposer que certains d'entre eux ont été éliminés lors de la prophase I de la méiose. Il est envisageable que le point de contrôle des dommages à l'ADN dépendant de CHK2 soit responsable de cette élimination.En effet, il a été suggéré que la réparation de l'ADN des ovocytes ayant plus de 10 DSBs soit inhibée puis que ces ovocytes soient éliminés par apoptose.En résumé, nos données montrent clairement que l'exposition au CD au cours du développement entraine des défauts méiotiques, similaires à ceux observés dans la lignée mâle, et diminue le stock d'ovocytes. La dynamique épigénétique au sein de l'ovaire semble être l'un des facteurs responsables des effets.

leads to SV at the genome-wide level in the human population. Recently, analysis of data from 2,504 human genomes revealed the presence of large number of SV of DNA in human populations. In many individual human genome, clusters of copy-number variants were identified, which are likely caused by replication errors and located in regions defined as "fragile sites"[START_REF] Sudmant | An integrated map of structural variation in 2,504 human genomes[END_REF].

https://bioconductor.org/packages/release/bioc/manuals/DESeq2/man/DESeq2.pdf

Acknowledgments

you that, yes, I did it! Thanks to the TF (Alice, Anaïs, Axelle, Dédé, Imad, Justine, Mégane, Solène and Vincent), to my Barbouzes (Alex, Ben'j, Cendrine, J-B and Romain) and to all my Angers people.

Emmanuelle, perhaps it is you that I thank the most, for your incredible patience and the unwavering support that you have shown. I know how long this wait has been. I am happy to see new horizons opened up for us.

I would like to thank my parents, Pierre-Yves and Valérie, as well as my sisters, Esther and Romane, who have always believed in me. I want to say thank you to you very sincerely. Thank you for everything you have done so that I can get to this today. I am sure that it was within our family that my curiosity germinated and developed, which prompted me to want to do research.

National Human Genome Research Institute

variants were stored within databases freely available online. Short variants (up to 50bp) were added to dbSNP, an expansive catalog of nucleotide changes for human, available at: www.ncbi.nlm.nih.gov/snp/. dbSNP is a collaboration between the NCBI (National Center for Biotechnology Information) and the NHGRI (National Human Genome Research Institute) which has celebrated its 20 years of existence in 2019. Longer variants from the 1,000 Genomes are accessible in the DGVa (Database of Genomic Variants archive) available at: www.ebi.ac.uk/dgva/.

Other smaller-scale projects existed before the launch of the 1,000 Genomes project, including the Human Genome Diversity Project or the international HapMap project [START_REF] Altshuler | Integrating common and rare genetic variation in diverse human populations[END_REF]. Nowadays, other studies complement the data accumulated by the 1,000 Genomes project. For example, there are many national initiatives from certain countries carrying out studies on their populations, such as Estonia [START_REF] Leitsalu | Cohort Profile: Estonian Biobank of the Estonian Genome Center[END_REF], the Netherlands (van [START_REF] Van Leeuwen | Genome of The Netherlands population-specific imputations identify an ABCA6 variant associated with cholesterol levels[END_REF], Qatar [START_REF] Rodriguez-Flores | Indigenous Arabs are descendants of the earliest split from ancient Eurasian populations[END_REF], Vietnam [START_REF] Le | A Vietnamese human genetic variation database[END_REF], South Korea (Korean Genome Project), United Kingdom (UK10K) among many others.

with the exception of inactive X. This is the first observed difference at the chromatin level, other than DNA methylation.

From this first observation, numerous other modifications were studied. Extensive study on acetylation revealed that this mark is still present at the PARs (observed as dots in immunofluorescence), although the inactive X is globally depleted in this mark [START_REF] Boggs | Differentially methylated forms of histone H3 show unique association patterns with inactive human X chromosomes[END_REF]. On the other hand, inactive X chromosome is enriched in H3K9me3 compared to other chromosomes, as well as in H3K27me3, two repressive histone marks [START_REF] Hyun | Writing, erasing and reading histone lysine methylations[END_REF]. All of these studies have shown that there are differences in chromatin between the two X chromosomes. placed on identifying cellular states, including stemness, immortality, proliferation, differentiation, senescence and stress, through the study of DNA methylation and histone modifications, accompanied by quantitative data of transcription levels.

The IHEC consortium gathers data from many projects, including those of the ENCODE project. Other projects, generating epigenetic data are also included, notably the American RoadMap project of the NIH, the European project BluePrint and the Canadian project CEEHRC (Canadian Epigenetics, Environment and Health Research Consortium). All these data are stored together in a database freely accessible at https://epigenomesportal.ca/ihec/.

E. Environmentally induced epigenetic alterations

The following section is directly extracted from a review written during my PhD, which was dedicated to environmentally induced transgenerational alterations (Legoff et al., 2019).

Figure 19. A model showing Sry regulation in mouse. From [START_REF] Larney | Switching on sex: transcriptional regulation of the testis-determining gene Sry[END_REF].

c. Epigenetic regulation of SRY

Expression of SRY is regulated via epigenetic mechanisms as well, notably through DNA methylation and methylation of histones. First evidence of epigenetic regulation of SRY came from the analysis of DNA methylation performed by [START_REF] Nishino | DNA methylation-mediated control of Sry gene expression in mouse gonadal development[END_REF]. In this study, the authors showed via sodium bisulfite sequencing that Sry was hypermethylated and not expressed at E8.5, while it was hypomethylated and expressed at E11.5 and its methylated status was unchanged in cells that do not express Sry [START_REF] Nishino | DNA methylation-mediated control of Sry gene expression in mouse gonadal development[END_REF]. Later studies focused on histone modifications implicated in regulation of SRY. For example, it has been shown that mice lacking KDM3A demethylase are subjected to male-to-female reversal, characterized by an increase in H3K9me2 [START_REF] Kuroki | Epigenetic regulation of mouse sex determination by the histone demethylase Jmjd1a[END_REF]. Moreover, another study performed in mice revealed that active H3K27ac marks are essential for the activation of Sry expression [START_REF] Carré | Loss of p300 and CBP disrupts histone acetylation at the mouse Sry promoter and causes XY gonadal sex reversal[END_REF]. Several other epigenetic regulatory mechanisms were reported to be involved in the fine control of Sry expression, including H3K4me3 and H3 acetylation. These processes have been recently reviewed in [START_REF] Kuroki | Epigenetic regulation of mammalian sex determination[END_REF]. transport from the head to the tail of the epididymis. During this process, the surface of the sperm plasma membrane undergoes large modifications, which makes the sperm fully mature when they arrived to the tail of the epididymis. The mature spermatozoa are stored in a quiescent state until ejaculation. The sperm membrane alterations may lead to the incorporation of proteins, sugars and lipids of epididymal origin into the sperm membrane. During the epididymal transition, spermatozoa also acquire the ability to recognize, to bind and to fuse with the eggs. The ejaculate or the semen consists of a fluid part, along with sperm, that mainly comes from the accessory sex glands of the male reproductive system.

B. Prostate

The prostate is an accessory sexual gland present in males under the bladder and surrounding pelvic urethra. Its function is to participle in the production of the semen, along with seminal vesicles. The prostate is divided into a glandular component, containing ducts and glands, as well as a non-glandular component. In humans, the prostate gland is encapsulated inside a fibromuscular layer called the capsule. The prostate produces a clear slightly acidic fluid, which consist of one-third of the semen volume. The secretion of prostate includes calcium, zinc, citric acid and acid phosphatase. Choline, an essential nutrient hydrolyzed from phosphorylcholine by phosphatase, contributes to sperm nutrition. The secretion of prostate also contains the seminal plasmin, which is an antimicrobial protein that combats urinary tract infections. The prostate-specific antigens can break down the high molecular weight proteins of the seminal coagulum into smaller polypeptides which helps the semen to liquefy after ejaculation.

The structural and functional integrity of the prostate gland is regulated by testosterone.

The size of the prostate gland increases with aging and could lead to a malignant hyperplasia.

Although there are anatomical differences between the mouse prostate and the human prostate at the age of sexual maturity, the phenomenon of prostate budding that occurs during development is remarkably conserved.

Embryonic development of the prostate

The prostate is derived from the cloaca representing the posterior end of the embryonic gut, being therefore of endodermal origin. Between E12-E14, the cloaca is subdivided into two distinctive tracts. The gastro-intestinal tract, which allows evacuation of feces through the anus, and the genitourinary tract responsible for the evacuation of urine through the urethra.

The primary urogenital sinus (UGS), resulting from the division of the cloaca, is then subdivided into three distinct parts: the bladder, the urogenital sinus and the urethra.

In males, under the influence of sex steroid hormones, mainly testosterone, the lower part of the UGS forms the prostate through an epithelial budding at E17.5 (around 7 weeks in humans). Prostate formation is dependent on complex epithelial-mesenchymal interactions.

At E14, a subpopulation of UGS epithelial cells which contributes to future prostate bud epithelium, start to express Shh (sonic hedgehog signaling molecule). At E15, androgens bind to AR-positive cells in UGS mesenchyme triggering the production of the steroid 5 alpha reductase type 2 (SRD5A2). At this point in time, the earliest marker of prostate identity, Nkx3-1 (NK3 homeobox 1), is detectable in UGS epithelium, before the initiation of budding. SRD5A2, in turn, converts testosterone to dihydrotestosterone (DHT) which stimulates the proliferation IV. Generalities on chlordecone A. Physical, chemical and biological properties of chlordecone

Physico-chemical properties

The chemical name of CD is 1,2,3,4,6,7,8,9,10,10-decachloropentacyclo [5.3.0.0 2,6 .0 3,9 .0 4,8 ]decan-5-one, and its chemical formula is C10Cl10O. CD is an odorless white powder that was used as an active compound in pesticide formulations. CD has a relatively high molecular weight (490.68 g.mol -1 ). It is characterized by its cubic/cage-like structure with 10 substitutions of hydrogen by chlorine atoms, which provide high chemical stability. (Figure 27). Because of this feature, CD has relatively low solubility in water (1-3 mg/L) in normal range of pH [START_REF] Chen | DNA 5-Methylcytosine Demethylation Activities of the Mammalian DNA Methyltransferases[END_REF][START_REF] Luger | Crystal structure of the nucleosome core particle at 2.8 A resolution[END_REF] and salinity (0.06-19.5%) [START_REF] Iarc | Chemicals and Industrial Processes Associated with Cancer in Humans[END_REF]. CD is readily absorbed to particulate matter in water and is ultimately deposited in sediments [START_REF] Lunsford | Uptake of Kepone® by the estuarine bivalve Rangia cuneata, during the dredging of contaminated sediments in the James river, Virginia[END_REF]. Therefore, exposure from drinking water does not constitute a significant exposure route in humans. In contrast, CD is relatively soluble in non-polar solvents. CD is a hydrophobic/lipophilic compound, explaining its ability to accumulate in lipid-rich tissues of the organism, such as liver or fat tissues. An overview of the physico-chemical properties of CD is provided in Table 7. Several studies have shown that CD can bioaccumulate in living organisms and therefore can contaminate the food chain [START_REF] Coat | Contamination of some aquatic species with the organochlorine pesticide chlordecone in Martinique[END_REF][START_REF] Lafontaine | Bioaccumulation, distribution and elimination of chlordecone in the giant freshwater prawn Macrobrachium rosenbergii: Field and laboratory studies[END_REF]. At the same time and for the same reasons, CD can accumulate in soils rich in organic matters, such as those found in the French West Indies where CD was massively used [START_REF] Cabidoche | Long-term pollution by chlordecone of tropical volcanic soils in the French West Indies: a simple leaching model accounts for current residue[END_REF]. This property leads to a potent long-term pollution of the ground. Therefore, in 2009, CD was classified as a persistent organic pollutant (POP), which means the ability to persist in the environment, to bioaccumulate and to be toxic to humans and to the environment (Stockholm Convention on persistent organic pollutions, available at: http://chm.pops.int/). Workers included in this study presented symptoms of CD toxicity and their blood CD levels were superior to 600ng/mL. Around 60% of the workers (20 out of 32) exhibited a hepatomegaly [START_REF] Guzelian | Liver structure and function in patients poisoned with chlordecone (kepone)[END_REF]. Normal levels in serum were observed for alanine transaminase (ALT) and aspartate transaminase (AST), which are commonly used to diagnose liver disease.

These abnormal changes were found to be resolved within years following cessation of exposure, suggesting that the hepatic changes represented adaptative responses to CD. Liver biopsies performed on 10 patients revealed that concentration of CD in the liver was 15 times higher than the corresponding concentration in blood [START_REF] Guzelian | Liver structure and function in patients poisoned with chlordecone (kepone)[END_REF].

Neurotoxicity

More than half of the workers (76 out of 133) at the Hopewell industry developed clinical illness. Symptoms included nervousness, tremor, weight loss, opsoclonus (i.e., uncontrolled, irregular and nonrhythmic eye movement), inflammation of the pleurae (pleurisy), joint pain and oligospermia [START_REF] Cannon | Epidemic kepone poisoning in chemical workers[END_REF]. Also, irritability and short-term memory loss were reported.

Mice and rats exposed to CD were reported to have tremors and presented exaggerated startle responses. These observations were consistent between several studies using different doses as well as single or multiple exposures. Effects reported from these animal studies were similar to those reported from occupationally exposed humans (Agency for Toxic Substances and Disease Registry (ATSDR), 2019). Intermediate-to long-duration studies were also performed in mice and rats (90 days, 80 weeks or 2 years exposure through diet), which revealed that CD has similar neurotoxic effects that led to tremors [START_REF] Larson | Acute, subchronic, and chronic toxicity of chlordecone[END_REF][START_REF] Linder | Spermotoxicity and tissue accumulation of chlordecone (Kepone) in male rats[END_REF].

Reprotoxicity

It has been observed in male workers, in the factory of Hopewell, that CD induced some fertility problems. Notably it was observed that workers had decreased libido, which was not associated with changes in sexual hormone levels [START_REF] Guzelian | Comparative toxicology of chlordecone (Kepone) in humans and experimental animals[END_REF]. Besides, in males with CD levels superior to 1mg/L, a decrease in spermatozoa number (< 25 million / mL) and motility were observed. Follow-up of these males several years after the end of the exposure revealed that the semen quality has improved, suggesting that these changes were reversible. The use of bar-coded indexed primers allows to reduce the price by multiplexing, i.e., mixing, the samples in a single lane of the flowcell. The barcodes provide a unique identifier to each sample, making it possible to recognize with certainty the sample of origin for each read. In our projects, we multiplexed up to six samples per lane.

In our studies, RNAs were extracted from murine testis and prostate. The libraries were sequenced either on Illumina HiSeq2500 or HiSeq4000 as strand specific paired-end 50/100 base reads. The main steps that will be described are (1) quality control of the sequencing reads, (2) mapping of the high-quality reads onto the reference genome, (3) building of the transcriptome, (4) quantification of gene or transcript abundance and ( 5) comparison between several experimental conditions. How many biological replicates need to be used? The Encode recommends to use minimum three replicates per condition. However, it is better to increase the number to 4-5 replicates, or even more, to get more reproducible results.

A. Quality control of sequencing data Following sequencing and demultiplexing, i.e., the separation of the samples sequenced on the same flowcell lane via the use of barcode specific to each sample, the results are obtained as fastq files. Each read resulting from sequencing is represented within a file by a set of 4 lines (Figure 30), including ( 1) a header containing the information related to the sequencer and the flowcell, ( 2) the nucleotide sequence, (3) a separation line starting with the character "+" which may contain comments, and finally ( 4) a line containing a quality score for each of the nucleotides found in the second line. The use of tools dedicated to the observation of such parameters, such as FastQC (v0.11.7) developed at the Babraham Institute in Cambridge, is recommended in order to ensure the good quality of the data (Figure 31). In our studies, reads are considered to be good enough when the Phred score is greater than 30, i.e., the estimated error probability for the base-call is 1/1000, or a base call precision of 99.99 %. Indeed, the Phred score (q) is related to the error probability of the base call (p) by the following relation: q = -10 x log10(p) [START_REF] Ewing | Base-calling of automated sequencer traces using phred. I. Accuracy assessment[END_REF].

D. Peak annotation

Once the differential peaks are identified, it is necessary to determine the genes present in their vicinity, and likely to be regulated by the corresponding epigenetic mark (peak).

For this, it is possible to use GREAT 1 (Genomic Regions Enrichment of Annotations Tool) [START_REF] Mclean | GREAT improves functional interpretation of cis-regulatory regions[END_REF], which associates regions with genes using different methods. In our case, we used the "Basal plus extension" association, which is the default behavior of GREAT (v3.0.0 and v4.0.4). In this method, each gene is assigned a basal regulatory domain of a minimum distance upstream (5kb) and downstream (1kb) of the TSS, regardless of other nearby genes. The gene regulatory domain is extended in both directions of the nearest gene's basal domain but no more than the maximum extension in one direction (Figure 45). Following this assignment, GREAT then calculates statistical enrichments for the associations between the genomic regions and the annotations, and finally adjusts p-values for multiple tests. Some other tools, mentioned in Table 8, can then be used to further annotate the gene list provided by GREAT.

To further characterize the differential peaks and predict the effect of these observed changes in the cells, it is possible to look for transcription binding sites within the differential peaks. Two main methods can be used, and dedicated tools are available online on MEME Suite (v5.2.0) [START_REF] Bailey | MEME SUITE: tools for motif discovery and searching[END_REF] (Figure 46). In any case, the tool requires a nucleotide sequence as an input. These sequences corresponding to differential peaks can be retrieved through bedtools using the getFasta function.

First approach consists of identifying specific binding sites with a priori, using FIMO (Find Individual Motif Occurrences). The motif of the binding site for the transcription factor of interest can be obtained from HOCOMOCO 2 v11 (HOmo sapiens COmprehensive MOdel COllection), which provides transcription factor binding models for human and mouse [START_REF] Kulakovskiy | HOCOMOCO: towards a complete collection of transcription factor binding models for human and mouse via large-scale ChIP-Seq analysis[END_REF]. FIMO searches the provided set of sequences for occurrence of the known motif and provides a p-value for putative identified binding sites.

The second approach is performed without any a priori and is designed to discover de novo motif enriched in the input set of sequences. This task is performed by . Following the identification of enriched motif, the algorithm automatically groups those displaying high similarity. Then, using an external tool, named TomTom, MEME-ChIP compares de novo motifs to databases (including HOCOMOCO) to look for similarity with known motifs. and downstream of the base of interest) and the position of the base within the reading (i.e., the sequencing cycle).

The construction of the model is carried out on a set of known positions present within VCF reference files (eg, ExAc, gnomAD or dbSNP), which makes it possible to calculate an empirical probability of error given the co-variables observed for each site. During our work, we used the resources of the 1,000 Genomes project as well as those available in the dbSNP v146 database as known sites.

C. Variant calling with HaplotypeCaller

Following the recalibration of the base quality scores, comes the step of variant calling.

The aim of this step is to define the haplotypes of each of the individuals in our cohort and to report the regions that differ from the reference genome (SNPs or short indels). The tool used, HaplotypeCaller, is also available in GATK (Figure 49).

First, the algorithm determines the active regions, i.e., the regions on which the program needs to operate on (i.e., showing significant evidence of variations after the mapping step).

The sequencing reads present in each of the active regions are assembled de novo (ignoring the mapping information) in order to determine the haplotype. This process often generates several different haplotypes for each active region. To generate a list of possible haplotypes, HaplotypeCaller constructs a De Bruijn graph. This step generally produces complex graphs with many possible paths. However, the program keeps information on the number of reads supporting each segment of the graph, which allows it to keep only the most likely paths.

The next process is to assess how much evidence there is in the data to support each of the candidate haplotypes. To do this, the program individually aligns each read on each of the candidate haplotypes using an algorithm called PairHMM. This calculates a score for each read-haplotype pairing, corresponding to the probability of observing this read given that haplotype. These likelihoods are used to calculate how much evidence there is for individual alleles at each variant sites. This process is called marginalization over alleles.

Once this allele probability table per read is obtained, it is possible to determine, using Bayes' theorem, which is the most probable genotype of the individual for each site. For each individual and each site, the most probable genotype is stored and returned in the gVCF file, as well as various metrics such as likelihoods of the returned genotypes (PL), genotype quality (GQ), among others.

194

Results

In this study, we assessed the genetic mutations induced by by in-utero CD exposure.

CD is an organochlorine insecticide which has estrogenic properties [START_REF] Eroschenko | Surface changes in oviduct, uterus and vaginal cells of neonatal mice after estradiol-17 beta and the insecticide chlordecone (Kepone) treatment: a scanning electron microscopic study[END_REF][START_REF] Hammond | Estrogenic activity of the insecticide chlordecone (Kepone) and interaction with uterine estrogen receptors[END_REF]. It was extensively used from 1973 to 1993 in the French West Indies. This pesticide des not undergo significant biotic or abiotic degradation in the environment [START_REF] Cabidoche | Long-term pollution by chlordecone of tropical volcanic soils in the French West Indies: a simple leaching model accounts for current residue[END_REF]. As a consequence, human beings continue to be exposed to this chemical.

CD is a neurotoxicant, reprotoxicant and cancerogenic substance in both rodents and humans (ATSDR, 2019;[START_REF] Cohn | Treatment of chlordecone (Kepone) toxicity with cholestyramine. Results of a controlled clinical trial[END_REF][START_REF] Multigner | Chlordecone exposure and adverse effects in French West Indies populations[END_REF]. Epidemiological studies have shown that prenatal exposure to CD affects development of the nervous system and child growth [START_REF] Boucher | Exposure to an organochlorine pesticide (chlordecone) and development of 18-monthold infants[END_REF][START_REF] Costet | Perinatal exposure to chlordecone and infant growth[END_REF]. In men, CD exposure at adulthood was associated with an increased risk of prostate cancer [START_REF] Multigner | Chlordecone exposure and risk of prostate cancer[END_REF]. Since populations are still exposed to CD, there is an immediate urge to assess the potential deleterious effects of CD, especially on fragile developmental organisms. Here we show that exposure to CD induce lethal mutations in genes related to DNA repair and detoxification functions and cause large structural variants in some regions of the genome.

A. Experimental design

To reveal the diversity of mutations, we analyzed the coding sequences of 24 human samples. The umbilical cord and mother's blood were obtained at moment of the delivery. The concentration of CD in the blood of mother and child were provided to us. For the analysis, we chose samples from three groups with different concentrations of CD, we defined them as group with "low" concentration of CD which was below the detection limit of detection (0.06 ng/mL), "medium" concentration of CD, between 0.77 and 0.93 ng/mL, and "high" CD concentration, between 1.08 and 12.47 ng/mL. We extracted DNA from the umbilical cord blood. The quality and integrity of the DNA was verified and the whole exome capture and resulting DNA libraries were prepared. The sequencing was performed in paired-end mode. The details of analysis were previously described in the Methods section.

The comparison of exome sequences showed that, in total, there are 2,962,950 variants compared to the hg38 reference genome. Most of the identified mutations are SNPs. Some of the variants such as mutation in CEP164 (centrosomal protein 164) gene were confirmed by Sanger sequencing (data not shown).

I. Supplementary Information -Article 1