Panpan Zhang

Christel Llauro

Alain Ghesquière

R Keith Slotkin

Frédéric Pontvianne

Marie Mirouze

eccDNA and structural variants analysis reveals massive genome instability in Arabidopsis epigenetic mutants

Keywords: extrachromosomal circular DNA, genome assembly, transposable element, long read sequencing long read, genome assembly, assembly reconciliation, assembly graph

Transposable elements (TEs) are repetitive DNA sequences with the intrinsic ability to move and amplify in genomes. Active transposition of TEs is linked to the formation of extrachromosomal circular DNA (eccDNA). However, the complete landscape of this eccDNA compartment and its interactions with the genome are not well defined. In addition, at the beginning of my thesis, there were no bioinformatics tools available to identify eccDNAs from long-read sequencing data.

To address these questions during my PhD, we first developed a tool, called ecc_finder, to automate eccDNA detection from long-read sequencing and optimized detection from short-read sequences to characterize TE mobility. By applying ecc_finder to Arabidopsis, human and wheat eccDNA-seq data (with genome sizes ranging from 120 Mb to 17 Gb), we documented the broad applicability of ecc_finder as well as optimization of its computational time, sensitivity and accuracy.

In the second project, we developed a meta-assembly tool called SASAR to reconcile the results of different genome assemblies from long-read sequencing data. For different plant species, SASAR obtained high quality genome assemblies in an efficient time and resolved structural variations caused by TEs.

In the last project, we used SASAR-assembled genome and ecc_finder-detected eccDNA to characterize eccDNA-genome interactions. In Arabidopsis thaliana hypomethylated epigenetic mutants, we highlighted the role of the epigenome in protecting genome stability not only from TE mobility but also from genomic rearrangements and gene chimerism. Overall, our findings on eccDNA, genome stability and their interactions, as well as the development of tools, offer new insights into the role of TEs in the adaptive evolution of plants to rapid environmental change.

Résumé de la thèse en 5 pages

Les éléments transposables (TE), qui désignent des éléments génétiques mobiles, sont des composants majeurs des génomes eucaryotes, représentant de ~3% chez la levure S. cerevisae [START_REF] Kim | Transposable elements and genome organization: a comprehensive survey of retrotransposons revealed by the complete Saccharomyces cerevisiae genome sequence[END_REF] à 45% chez l'homme [START_REF] Lander | Initial sequencing and analysis of the human genome[END_REF] et plus de 85% chez certaines espèces végétales, comme le blé [START_REF] Wicker | Impact of transposable elements on genome structure and evolution in bread wheat[END_REF]. Suivant leurs modes de transposition, les TE sont classés en rétrotransposons et en transposons à ADN [START_REF] Feschotte | Plant transposable elements: where genetics meets genomics[END_REF][START_REF] Wicker | A unified classification system for eukaryotic transposable elements[END_REF]. Les TE actifs initient la formation de particules de type viral et la réverse transcription qui s'ensuit aboutit à la synthèse de l'ADN extrachromosomique (ADNe). L'ADN extrachromosomique sous forme double brin s'insère dans de nouveaux loci génomiques grâce à l'intégrase ou forme de l'ADN circulaire extrachromosomique (ADNecc) (Lanciano et al., 2017).

L'ADNecc a été observé chez de nombreuses espèces eucaryotes comme la levure, la drosophile, les nématodes, les plantes et les humains (Hotta et Bassel, 1965;Hirochika et Otsuki, 1995;Sinclair et Guarente, 1997;Cohen et Méchali, 2002;[START_REF] Cohen | Mouse major satellite DNA is prone to eccDNA formation via DNA Ligase IV-dependent pathway[END_REF]Kumar et al., 2017).

L'ADNecc a été découvert depuis plusieurs décennies, mais au cours des dernières années, grâce au séquençage à haut débit, son étude a connu un véritable engouement car il joue un rôle important dans l'évolution des cellules cancéreuses (Verhaak et al., 2019). Dans ces cellules, il contribue à l'évolution adaptative en favorisant les variations rapides du nombre de copies [START_REF] Kim | Extrachromosomal DNA is associated with oncogene amplification and poor outcome across multiple cancers[END_REF]. Chez les plantes, l'ADNecc a été caractérisé pour la première fois par un protocole qui séquence sélectivement l'ADN circulaire enrichi suite à la digestion de l'ADN linéaire, à savoir le mobilome-seq (Lanciano et al., 2017). Cette technique, basée sur le séquençage à lectures courtes a révélé que les ADNecc proviennent notamment des TE actifs dans la plante. Avec l'arrivée des technologies de séquençage en lectures longues proposées par deux plateformes fondamentalement différentes : Pacific Biosciences (PacBio) et Oxford Nanopore Technologies (ONT), le mobilome-seq ou eccDNA-seq permet de capturer la structure des ADNecc en couvrant leur longueur totale en une seule lecture (Koche et al., 2020). Cependant, au début de ma thèse, il n'existait pas d'outil bioinformatique dédié à la détection des ADNecc à partir du séquençage en lectures longues (Figure Résumé).

Premier objectif : outil pour caractériser le paysage des ET dans les ADNecc

Au cours de ma thèse, le premier objectif était de caractériser le contenu en TE dans les ADNecc. La thèse présentera tout d'abord les propriétés des TE, les mécanismes de transposition et de « silencing » des TE, et s'étendra aux modèles proposés pour les captures de gènes par les TE. En particulier, les résultats de l'état de l'art en matière d'ADNecc tels que l'ADNecc correspondants aux TE actifs chez les plantes, ou aux oncogènes dans les cellules cancéreuses seront discutés. Mes résultats concernant le développement d'une méthode bioinformatique de détection d'ADNecc à partir de données eccDNA-seq seront présentés, ainsi que leur application chez Arabidopsis thaliana avec un stress thermique et chez le blé tendre Triticum aestivum, illustrant la puissance de calcul, la sensibilité et la précision de l'outil développé. Grâce à cet outil, l'ADNecc peut être détecté de manière robuste et précise à partir de séquençage en lecture courtes mais aussi longues, comblant ainsi les lacunes dans ce domaine.

Deuxième objectif : outil pour l'assemblage haute qualité des génomes en lectures longues

Pour annoter les polymorphismes de TE au sein d'un génome, puis pour explorer l'interaction entre l'ADNecc et le génome, il est primordial d'obtenir un assemblage de génome de haute qualité. Le processus de reconstruction du génome à partir des millions de lectures générées par les plateformes de séquençage à haut débit est appelé assemblage de novo [START_REF] Nagarajan | Sequence assembly demystified[END_REF]. Depuis que le premier génome végétal a été déchiffré en 2000, plus de 700 génomes végétaux ont été assemblés (www.plabipd.de) [START_REF] Bolger | From plant genomes to phenotypes[END_REF]. La plupart des assemblages de génomes de plantes sont basés sur le séquençage d'ADN à lecture courte et composés de milliers de contigs fragmentés [START_REF] Belser | Chromosome-scale assemblies of plant genomes using nanopore long reads and optical maps[END_REF]. Deux génomes de référence modèles de plantes, la dicotylédone Arabidopsis thaliana (The Arabidopsis Genome Project, 2000) et la monocotylédone Oryza sativa (International Rice Genome Sequencing Project, 2005) ont été séquencés sur la base du séquençage Sanger et de l'assemblage par une approche clone par clone et des améliorations ultérieures, et figurent parmi les meilleurs assemblages de génomes végétaux. Cependant, même les génomes de référence contiennent des lacunes. La séquence du génome d'A. thaliana Col-0 a été publiée en 2000, et après des décennies de recherche, le génome de référence TAIR10 est devenu l'étalon standard pour Arabidopsis. Cependant, l'enrichissement en séquences hautement répétées dans les régions centromériques, télomériques et au niveau des ADN ribosomiques a fait que ces régions présentent des erreurs d'assemblage ou ne sont pas séquencées. Ce génome contient encore 165 lacunes avec des bases inconnues (N-stretches) et environ 25 Mb de régions manquantes, principalement au niveau des centromères [START_REF] Long | Massive genomic variation and strong selection in Arabidopsis thaliana lines from Sweden[END_REF]. Pour obtenir le génome de télomère à télomère d'A. thaliana Col-0, Wang et al. (2021) ont introduit la stratégie de substitution de séquence clonée en chromosome artificiel bactérien (BAC) avec le séquençage Pacbio, résolvant les centromères et les lacunes (Wang et al., 2021). Pour évaluer les caractéristiques génétiques et épigénétiques des centromères, Naish et al. ont assemblé un génome Col-0 d'A. thaliana hautement contigu à l'aide de lectures ultra-longues générées par ONT, fournissant un paysage approfondi de l'évolution des centromères (Naish et al., 2021).

Les progrès réalisés en matière de longueur moyenne des lectures, d'algorithmes d'assemblage et de logiciels ont grandement contribué à l'intégrité et à la qualité de l'assemblage des génomes. Les difficultés liées au comblement des lacunes, à la caractérisation des haplotypes et à la construction de génomes gigantesques sont en cours de résolution [START_REF] Marx | Long road to long-read assembly[END_REF][START_REF] Sun | Chromosome-scale and haplotype-resolved genome assembly of a tetraploid potato cultivar[END_REF]. Au cours des deux dernières années, l'analyse comparative de génomes ou de plusieurs individus d'une même espèce a montré qu'un seul génome de référence ne suffit pas à rendre compte de la diversité génétique d'une espèce [START_REF] Bayer | Plant pangenomes are the new reference[END_REF]. De nombreux facteurs ont conjointement favorisé la construction et la recherche sur les pan-génomes végétaux et animaux. Le pan-génome est un terme général désignant tous les gènes d'une espèce, où les gènes totaux sont distincts de ceux du génome individuel [START_REF] Tettelin | Genome analysis of multiple pathogenic isolates of Streptococcus agalactiae: Implications for the microbial "pan-genome[END_REF]. Ainsi, le séquençage à long terme à l'échelle de la population a progressivement commencé à se développer dans la recherche en génomique évolutive et fonctionnelle et dans la recherche sur la sélection des plantes cultivées. Des pan-génomes ont été réalisés sur diverses plantes modèles et cultivées, notamment la tomate [START_REF] Gao | The tomato pan-genome uncovers new genes and a rare allele regulating fruit flavor[END_REF]Alonge et al., 2020), le riz (Qin et al., 2021), le blé [START_REF] Walkowiak | Multiple wheat genomes reveal global variation in modern breeding[END_REF], le maïs (Hufford et al., 2021), etc.

Dans ce manuscrit de thèse, les percées clés pour l'assemblage des génomes des plantes seront présentées, notamment le comblement des lacunes, la mise en phase des haplotypes, la construction de très gros génomes et le pan-génome mentionné cidessus. Cependant, dans la pratique, le défi de l'assemblage du génome demeure.

Différents assemblages produits par différents assembleurs ou le même assembleur avec différents paramètres ont des performances différentes, et le meilleur assemblage ayant à la fois une haute résolution en termes de contiguïté et de répétition ne peut pas être obtenu dans un seul assemblage. Mes résultats sur le développement d'un outil de méta-assemblage (SASAR) pour réconcilier le résultat de différents assemblages à partir de données de séquençage en lectures longues seront présentés. Les résultats obtenus sur les génomes d'A. thaliana Col-0 et du riz Oryza sativa ssp. japonica cv.

Nipponbare seront discutés. Grâce à SASAR, l'assemblage du génome sera construit de manière robuste avec une grande contiguïté, permettant de détecter les variants structuraux avec une précision accrue.

Troisième objectif : quel impact des ADNecc sur la stabilité du génome et les variations structurales ?

Les variations structurales (SV) font référence à l'altération de fragments chromosomiques qui sont différents du génome de référence, les fragments variants étant généralement plus grands que 50 pb. Les principaux types de SV sont l'insertion, la délétion, la duplication, l'inversion et la translocation [START_REF] Stankiewicz | Structural variation in the human genome and its role in disease[END_REF].

Un grand nombre d'études ont montré que les SV jouent un rôle clé dans des caractéristiques agronomiques importantes, telles que la résistance aux stress biotiques et abiotiques, le temps de floraison, l'architecture de la plante, le rendement, la qualité des grains ou des fruits [START_REF] Tao | Exploring and Exploiting Pan-genomics for Crop Improvement[END_REF]. De nombreux SV détectés dans 100 variétés de tomates ont un impact sur le dosage et les niveaux d'expression des gènes, entraînant des changements dans le goût, la taille et le rendement (Alonge et al., 2020). [START_REF] Zhou | A 1.7-Mb chromosomal inversion downstream of a PpOFP1 gene is responsible for flat fruit shape in peach[END_REF] ont identifié une inversion chromosomique de 1,67 Mb dans le génome de la pêche plate, responsable du passage de la pêche ronde à la pêche plate. En outre, plusieurs études ont montré que les SV peuvent aider à résoudre la structure de la population et fournir des informations supplémentaires valables pour mieux comprendre les processus de domestication des plantes (Alonge et al., 2020 ;Hufford et al., 2021 ;Qin et al., 2021).

L'insertion de TE dans le génome peut provoquer des changements spectaculaires dans la structure des chromosomes, à la fois par l'intégration de fragments de gènes et par l'induction de SV [START_REF] Feschotte | DNA transposons and the evolution of eukaryotic genomes[END_REF]. Dans le génome du riz, par exemple, le nombre de copies de TE et la distribution des inversions et des délétions contribuent à la variation au sein du genre Oryza [START_REF] Piegu | Doubling genome size without polyploidization: Dynamics of retrotransposition-driven genomic expansions in Oryza australiensis, a wild relative of rice[END_REF][START_REF] Hurwitz | Rice structural variation: a comparative analysis of structural variation between rice and three of its closest relatives in the genus Oryza[END_REF]. Dans le génome du maïs, les translocations des éléments Ac peuvent entraîner des délétions, des inversions, des translocations ou d'autres réarrangements [START_REF] Yu | A transgenic system for generation of transposon Ac/Ds-induced chromosome rearrangements in rice[END_REF]. En outre, les TE à capacité de capture, tels que Pack-MULE chez le riz et Pack-TIR chez 100 espèces animales, ont été décrits comme favorisant l'évolution adaptative en formant de nouveaux gènes [START_REF] Talbert | Characterization of a highly conserved sequence related to mutator transposable elements in maize[END_REF]Jiang et al. 2004[START_REF] Jiang | Pack-Mutator-like transposable elements (Pack-MULEs) induce directional modification of genes through biased insertion and DNA acquisition[END_REF][START_REF] Tan | DNA transposons mediate duplications via transposition-independent and -dependent mechanisms in metazoans[END_REF]. De plus, les fusions entre les transposons d'ADN et les gènes codant pour les protéines dans tous les génomes de tétrapodes démontrent que les TE constituent un réservoir pour façonner de nouvelles structures protéiques [START_REF] Cosby | Recurrent evolution of vertebrate transcription factors by transposase capture[END_REF]. Cependant, on sait encore peu de choses sur les fusions entre TE et gène dans l'ADNecc en raison du faible nombre d'exemples mis en évidence chez les plantes.

Dans ce manuscrit de thèse, mes résultats sur les SV associés aux TE et SV dans le génome de mutants épigénétiques seront décrits. L'accent sera mis sur l'algorithme et la validation visuelle des SVs dans le développement d'outils, favorisant l'étude de l'interaction entre l'ADNecc et le génome. Pour cette partie de ma thèse, le matériel végétal choisi sera un mutant hypométhylé d'A. thaliana, qui possède un fort taux d'ADNecc généré par des TEs actifs. Des plantes combinant des mutations dans la méthylation de l'ADN associée à DDM1 (Decrease DNA Methylation 1), le silencing post-transcriptionnel et la méthylation de l'ADN dirigée par l'ARN (triple mutants ddm1 rdr6 pol4) ont été étudiées au niveau ADNecc et génome en utilisant le séquençage en lectures longues. D'après ces résultats sur la dynamique de l'ADNecc et des SV dans des mutants épigénétique d'A. thaliana, je montrerai que les voies épigénétiques contrôlent la stabilité du génome au-delà de la mobilité des TE. Les réarrangements chaotiques du génome et le chimérisme des gènes mis en évidence dans cette étude renforcent le concept d'une évolution du génome à deux vitesses chez A. thaliana, guidée par l'épigénome.

Résumé

Les éléments transposables (TEs) sont des séquences d'ADN répétitives avec la capacité intrinsèque de se déplacer et de s'amplifier dans les génomes. La transposition active des TEs est liée à la formation d'ADN circulaire extrachromosomique (ADNecc). Cependant, le paysage complet de ce compartiment d'ADNecc ainsi que ses interactions avec le génome n'étaient pas bien définies. De plus, il n'existait au début de ma thèse aucun outil bioinformatique permettant d'identifier les ADNecc à partir de données de séquençage en lectures longues.

Pour répondre à ces questions au cours de mon doctorat, nous avons tout d'abord développé un outil, appelé ecc_finder, pour automatiser la détection d'ADNecc à partir de séquences en lectures longues et optimisé la détection à partir de séquences de lecture courte pour caractériser la mobilité des TE. En appliquant ecc_finder aux données eccDNA-seq d'Arabidopsis, de l'homme et du blé (avec des tailles de génome allant de 120 Mb à 17 Gb), nous avons documenté l'applicabilité d'ecc_finder ainsi que l'optimisation du temps de calcul, de la sensibilité et de la précision.

Dans le deuxième projet, nous avons développé un outil de méta-assemblage appelé SASAR pour réconcilier les résultats de différents assemblages de génomes à partir de données de séquençage en lectures longues. Pour différentes espèces de plantes, SASAR a obtenu des assemblages de génome de haute qualité en un temps raisonnable et a permis de détecter les variations structurales causées par les TE. A big thank you to my thesis director Marie Mirouze. Thank you for being so amazing, so nice, so cool, for letting me do this thesis under the best conditions a PhD student could dream of, and for supporting me through the years. Thank you for welcoming me as a non-French speaker at the beginning, you were very kind to help me with many uncountable tasks including administration, apartment and basic weekend activities. I also want to thank you Alain Ghesquière for following my thesis work, for all your advice, encouragement and support. Thank you for your patience.

The life of a PhD is a roller coaster, with ups and downs, and Covid brings a cliff drop.

However, when I look back on four years, I realize that there were many more ups than downs and this thanks to all the people in LGDP. Especially, I would like to thank Frédéric Pontvianne with whom shared an office at the beginning of my PhD. Thank you for the welcome and every scientific discussion. I would also like to thank Guillaume Moissiard for organizing every journal club, inviting amazing speakers and many international congresses. Thanks to Elisabeth Goetschy for managing all the administrative questions. My words are pale, thank you all for countless effort to make this friendly and enjoyable environment. I also want to thank the best officemate Avilien Dard and Jean Loup Zitoun. We made it through those four years, not without pain, questioning and muscle building, but we made it. I am very happy to have shared this experience with you, so thank you. And to Eduardo Muñoz, you know that I will miss your hugs a lot! I sincerely want to thank you for the moments we spent together, our passionate and angry. Thanks for all that and for all the other stuff.

A big thank you also to my research consortium, Epidiverse, for providing multiple travel fellowships for secondments and organizing five summer schools to enrich the interaction between cross-disciplinary research. TEs are repetitive DNA sequences with the intrinsic ability to move within the genome by a mechanism called transposition. They replicate and expand in the genome like a virus, are usually ranging from 100 to 10,000 bp in length, but sometimes far larger [START_REF] Arkhipova | Giant transposons in eukaryotes: is bigger better?[END_REF]. In recent years, genome sequencing of many species has been able to demonstrate that TEs and their relics are major components of eukaryotic genomes ranging from ~3% in the yeast S. cerevisiae [START_REF] Kim | Transposable elements and genome organization: a comprehensive survey of retrotransposons revealed by the complete Saccharomyces cerevisiae genome sequence[END_REF] and up to 45% in humans [START_REF] Lander | Initial sequencing and analysis of the human genome[END_REF] and >85% in some plants, such as maize [START_REF] Schnable | The B73 maize genome: complexity, diversity, and dynamics[END_REF] and wheat [START_REF] Wicker | Impact of transposable elements on genome structure and evolution in bread wheat[END_REF]. TEs are very diverse in nature [START_REF] Feschotte | Plant transposable elements: where genetics meets genomics[END_REF][START_REF] Wicker | A unified classification system for eukaryotic transposable elements[END_REF]

SASAR

Class I retrotransposons

Class I elements or retrotransposons are the most abundant and widespread in eukaryotes. This is due to their "copy-and-paste" transposition mechanism that allows the generation of a large number of copies from a single DNA sequence. LTR retrotransposons are characterized by one or two Open Reading Frames (ORFs) flanked by two LTRs, usually starting with TG in the 5' and ending with CA in the 3'. LTR sequences range in length from a few hundreds to over a thousand nucleotides. They contain promoter and regulatory regions separated into 3 functional domains (U3, R and U5). U3 domain harbors trans-activator binding sites, while U5 domain marks the start of transcription but also indicates the end of transcription and the signal for polyadenylation. The ORFs typically code for Group-specific antigen (GAG), a capsid polyprotein participating in the formation of a virus-like particle (VLP), and polyprotein (POL) cleaved into 4 active functional domains for: RT, a reverse-transcriptase, RH, a RNase H, AP, an aspartic protease, and IN, an integrase (Figure I.2) [START_REF] Havecker | The diversity of LTR retrotransposons[END_REF][START_REF] Sabot | Parasitism and the retrotransposon life cycle in plants: a hitchhiker's guide to the genome[END_REF].

LTR retrotransposons are grouped into 2 superfamilies that differ in the relative position of the POL gene-encoded enzyme domains (Figure I.2). TEs of the Gypsy superfamily sometimes possess an ORF called putative env, similar to the env encoding the retrovirus envelope glycoprotein. Indeed, the identification of common protein motifs between the sequences of integrases, reverse transcriptases and env proteins of retrotransposons and retroviruses indicates an evolutionary linkage [START_REF] Mcclure | Evolution of retroposons by acquisition or deletion of retroviruslike genes[END_REF][START_REF] Capy | Relationships between transposable elements based upon the integrase-transposase domains: Is there a common ancestor?[END_REF][START_REF] Lerat | Retrotransposons and retroviruses: analysis of the envelope gene[END_REF]. [START_REF] Havecker | The diversity of LTR retrotransposons[END_REF][START_REF] Sabot | Parasitism and the retrotransposon life cycle in plants: a hitchhiker's guide to the genome[END_REF].

Retrotransposons without LTRs, are divided into two classes: LINEs and SINEs (Long and Short Interspread Nuclear Elements). Both types of elements terminate at the 3' end with a polyA sequence of variable length. LINEs have coding regions that include: ORF1, a gag-like protein; EN, an endonuclease; and RT a reverse transcriptase. LINEs represent up to 20% of the human genome [START_REF] Lander | Initial sequencing and analysis of the human genome[END_REF] whereas in plants LINEs appear to be rare. SINEs do not encode a protein and are non-autonomous elements that depend on LINEs to transpose. The internal region of SINEs is highly variable and depends on the family of the element. The most studied element belonging to the SINE class is the Alu element, which alone represents 11% of the human genome [START_REF] Lander | Initial sequencing and analysis of the human genome[END_REF]. Although the 3' half of these elements is of unknown origin, the 3' end shows similarities with LINE sequences indicating that SINE elements may parasitize the transposition machinery of LINE elements [START_REF] Ogiwara | Retropositional parasitism of SINEs on LINEs: identification of SINEs and LINEs in elasmobranchs[END_REF]. SINEs are thought to result from reverse transcripts of short RNAs (usually tRNAs in plants) followed by their integration into the genome [START_REF] Deragon | Short interspersed elements (SINEs) in plants: origin, classification, and use as phylogenetic markers[END_REF].

Unlike LTR retrotransposons and despite the presence of an ORF encoding a gag-like protein, non-LTR retrotransposons do not produce a DNA copy of their RNA in the cytoplasm. Indeed, the transposition of these elements is achieved by reverse transcription at the integration site [START_REF] Cost | Human L1 element targetprimed reverse transcription in vitro[END_REF][START_REF] Kazazian | Mobile Elements: Drivers of Genome Evolution[END_REF]. Finally, it has been shown that most LINE sequences in genomes are truncated at a priori random 5' region by a mechanism called "5' truncation" [START_REF] Kazazian | Mobile Elements: Drivers of Genome Evolution[END_REF].

Class II DNA transposons

Class II TEs, or DNA transposons, do not require RNA as a mediator in the transposition process. They move by a mechanism of excision from one genomic position and then integration at another position by a transposase. This "cut and paste" mechanism usually does not lead to an increase in copy number. However, a gap repair mechanism can allow the restoration of the sequence of the element at the donor site.

DNA transposons are characterized by the presence of terminal inverted repeats (TIRs) at both ends, with TIR ranging from 14-500 bp in length. Autonomous elements encoding a transposase are divided into different superfamilies such as Ac/Ds, CACTA, MULE. Like class I TEs, class II elements can become non-autonomous via accumulating mutations in their coding region or by complete deletion of the coding region. Finally, some non-autonomous elements called MITE ("Miniature Invertedrepeat Transposable Elements") are composed only of TIR sequences. This type of non-autonomous transposons can rapidly increase in copy number until they exceed the copy number of autonomous elements from which they originate. For example, in the rice genome, MITEs are the elements with the highest copy number (about 90,000 copies in some varieties, Jiang et al., 2004).

A special case of DNA transposon that transpose using a rolling circle, called Helitrons was discovered more recently in eukaryotic genomes with typical 5'TC and 3'CTRR (R as A or G) termini and a stem-loop structure about 15-20 bp upstream of the 3' terminus [START_REF] Kapitonov | Rolling-circle transposons in eukaryotes[END_REF]. These transposons have the specificity of not possessing terminal repeats and of not generating target site duplications (TSDs). Their transposition would be done by a still hypothetical mechanism called "rolling-circle" close to the replication mechanism of certain bacteriophages and plasmids. Helitrons transposons, after transposition, are usually inserted into AT-rich regions of the AT target site [START_REF] Kapitonov | Helitrons on a roll: eukaryotic rolling-circle transposons[END_REF].

Each class of TEs has both autonomous and non-autonomous elements. Autonomous elements encode the enzymes required for their transposition in contrast to the mobility of non-autonomous elements, which depends on the enzymes produced by autonomous elements of the same or related families. For example, in the Activator (Ac) / Dissociator (Ds) system, Ac is the autonomous type and Ds is the non-autonomous type. Without Ac, Ds cannot function by itself. Non-autonomous family members are usually derived from an autonomous family member by internal deletion [START_REF] Mcclintock | The origin and behavior of mutable loci in maize[END_REF][START_REF] Howard | Transposable elements in maize -the Activator-Dissociation (Ac-Ds) System[END_REF]. Since TEs were first discovered in maize by Barbara McClintock in 1948[START_REF] Mcclintock | Mutable loci in maize[END_REF] and have since been found in all animals and plants, as well as in various eukaryotes. The transposition is the hallmark feature of TEs, and the integration of a TE from a donor site to a target site is known as a complete transposition process.

TE transposition and gene capture

The mechanism of an LTR retrotransposon transposition is close to that of retroviruses. This mechanism involves a complete transcription of the element from the 5' R region of the 3' LTR to the 3' R region of the 5' LTR. These transcripts are translated in the cytoplasm where they are used as a template for translation and also as a template for reverse transcription into DNA double strands [START_REF] Schulman | Retrotransposon replication in plants[END_REF]. In the cytoplasm, the polyprotein is processed by retrotransposon-encoded proteases into reverse The model for the formation of these eccDNAs has been established from work on retroviruses [START_REF] Li | Role of the non-homologous DNA end joining pathway in the early steps of retroviral infection[END_REF][START_REF] Kilzer | Roles of host cell factors in circularization of retroviral dna[END_REF]Lanciano et al., 2017).

Over time, the newly integrated copies undergo mutations. Based on the divergence between the two LTRs, insertion age can be estimated. However, it should be noted that Sanchez et al. observed that new insertions of the Arabidopsis thaliana LTR retrotransposon ATCOPIA78/ONSEN, a heat-induced retrotransposon family, corresponded to high-frequency recombination between old and recent copies [START_REF] Sanchez | High-frequency recombination between members of an LTR retrotransposon family during transposition bursts[END_REF] suggesting that the widespread involvement of young autonomous copies may revive 'older relatives' [START_REF] Sanchez | High-frequency recombination between members of an LTR retrotransposon family during transposition bursts[END_REF][START_REF] Drost | Becoming a Selfish Clan: Recombination Associated to Reverse-Transcription in LTR Retrotransposons[END_REF].

DNA transposons have a transposition cycle that appears to be relatively short compared to class I elements and takes place only in the nucleus (Figure I.3).

Transposase enzymes recognize and bind to terminal inverted repeats (TIRs) at both ends of the element. The element is excised from its locus and inserted at a new locus (Muñoz-López and García-Pérez, 2010). However, prior to reinsertion, the eclDNA can be recognized by DNA repair mechanisms (NHEJ or HR) inducing the formation of eccDNA [START_REF] Sundaresan | An extrachromosomal form of the Mu transposons of maize[END_REF][START_REF] Li | Role of the non-homologous DNA end joining pathway in the early steps of retroviral infection[END_REF].

DNA transposons can take along, in addition to its sequence, a potentially coding genomic segment: this is the mobilization of endogenous elements. The ability of DNA transposons to mediate gene duplication has been revealed in plants, where MULE elements (Mutator Like transposable Element) have captured 1500 parental genes in rice, for instance, forming a Pack-MULE chimeric structure [START_REF] Talbert | Characterization of a highly conserved sequence related to mutator transposable elements in maize[END_REF]Jiang et al., 2004[START_REF] Jiang | Pack-Mutator-like transposable elements (Pack-MULEs) induce directional modification of genes through biased insertion and DNA acquisition[END_REF][START_REF] Cerbin | Duplication of host genes by transposable elements[END_REF]. What's more, a recent study identified 370 Pack-TIRs mediated gene duplications in 100 animal reference genomes. This study demonstrates that Pack-TIRs prefer to capture exon sequences and most exons are fused to genes with transcriptional signals, and thus remodel gene structure and generate new genes [START_REF] Tan | DNA transposons mediate duplications via transposition-independent and -dependent mechanisms in metazoans[END_REF]. [START_REF] Tan | DNA transposons mediate duplications via transposition-independent and -dependent mechanisms in metazoans[END_REF]. Similar processes have been widely reported in human genetics and cancer genomics (summarized from [START_REF] Tan | LTR-mediated retroposition as a mechanism of RNA-based duplication in metazoans[END_REF][START_REF] Tan | DNA transposons mediate duplications via transposition-independent and -dependent mechanisms in metazoans[END_REF].

Mechanisms of TE silencing

To suppress the activity of TEs, the host genome has evolved mechanisms triggering and maintaining the silencing of TEs through DNA methylation, repressive histone modifications, small RNA and chromatin pathways [START_REF] Fultz | Silencing of active transposable elements in plants[END_REF].

DNA methylation corresponds to the addition of a methyl group on certain nucleotides.

In eukaryotes this modification affects almost exclusively cytosines. In plants, unlike mammals, methylation is not restricted to cytosines in a CG context but can also be observed at cytosines in a CHG and CHH context (where H can be any nucleotide except G). Cytosine methylation is mainly detected at pericentromeric regions rich in repeated sequences and poor in genes (Inagaki et al., 2017). This methylation is also strongly correlated with the presence of a heterochromatin-specific mark, histone 3 lysine 9 (H3K9me2) dimethylation, and with the presence of siRNAs [START_REF] Kasschau | Genome-Wide Profiling and Analysis of Arabidopsis siRNAs[END_REF][START_REF] Roudier | Chromatin indexing in Arabidopsis: an epigenomic tale of tails and more[END_REF][START_REF] Inagaki | Silencing and anti-silencing mechanisms that shape the epigenome in plants[END_REF]. TEs are methylated in all 3 cytosine contexts.

Their methylation is thought to be associated with their repression, since loss of this methylation leads to transcriptional reactivation of TEs [START_REF] Lippman | Role of transposable elements in heterochromatin and epigenetic control[END_REF] and an increase in their mobilization [START_REF] Kato | Role of CG and non-CG methylation in immobilization of transposons in Arabidopsis[END_REF][START_REF] Mirouze | Selective epigenetic control of retrotransposition in Arabidopsis[END_REF]Tsukahara et al., 2009). Maintenance of these methylation patterns over generations is mediated by specific methyltransferases such as MET1 (METHYLTRANSFERASE 1), CMT2 and CMT3 (CHROMOMETHYLASES 2 and 3) (Figure I.5). But while most methylations are passed down through generations, they can also occur de novo, in any context, through a mechanism of RNA-directed DNA methylation (RdDM) [START_REF] Wassenegger | RNA-directed de novo methylation of genomic sequences in plants[END_REF][START_REF] Law | Establishing, maintaining and modifying DNA methylation patterns in plants and animals[END_REF]Lloyd and Lister, 2022).

Additional proteins, such as the chromatin remodeler protein DDM1 (DECREASE IN DNA METHYLATION 1) protein, related to the SW12/SNF2 family of ATP-dependent chromatin remodeling factors, are essential for the maintenance of DNA methylation in different cytosine contexts (Vongs et al., 1993;[START_REF] Lippman | Role of transposable elements in heterochromatin and epigenetic control[END_REF]). DDM1 appears to primarily control the silencing of TEs (approximately 40% of TEs in Arabidopsis thaliana), and in particular of long TEs localized in heterochromatin, thus preventing their reactivation and transcription [START_REF] Lyons | DDM1 and Lsh remodelers allow methylation of DNA wrapped in nucleosomes[END_REF]. Recently, Berger et al. showed that DDM1 is involved in depositing the histone variant H2A.W to silence TEs (Bourguet et al., 2021;Osakabe et al., 2021). The ddm1 mutants have been widely observed as hypomethylated in all cytosine contexts. Some phenotypes revealed in a ddm1 context are related to alterations in genome structure (Tsukahara et al., 2009), but some others are associated with epigenetic modifications that influence gene expression and generate stable epialleles (Kinoshita et al., 2007). To assess the stability of DNA methylation perturbations and their consequences, epiRIL (epigenetic Recombinant Inbred Lines) populations were generated from ddm1 or met1 mutants [START_REF] Johannes | Assessing the impact of transgenerational epigenetic variation on complex traits[END_REF][START_REF] Reinders | Compromised stability of DNA methylation and transposon immobilization in mosaic Arabidopsis epigenomes[END_REF]. The principle of these populations is to maximize epigenetic variability by minimizing nucleotide changes. The ddm1 mutantderived epiRIL population was obtained by a cross between the ddm1 mutant and a wild-type (WT) plant followed by a back-cross between the F1 and a WT plant. The resulting F2 plants were genotyped to select DDM1 homozygous individuals.

Genotypes and epigenotypes were then fixed by self-fertilization for 6 generations (Cortijo et al., 2014a). The met1 epiRIL population was obtained using a similar design except that the F1 was selfed to obtain the F2 material [START_REF] Reinders | Compromised stability of DNA methylation and transposon immobilization in mosaic Arabidopsis epigenomes[END_REF]. The RdDM pathway mediated by RNA polymerases Pol IV and Pol V acts on TEs that already contain methylation modifications to enhance the silent state of TE (Panda et al., 2016). Pol-IV allows the synthesis of transcripts matured into siRNAs via RDR2 (an

SWI-SNF

RNA-dependent RNA polymerase) that polymerizes the complementary strand and DCL3 (Dicer protein) that cleaves the duplex into 24-nt small RNAs. These siRNAs are then modified and loaded the AGO4 Argonaute protein. Pol-V dependent transcripts serve as a template for the pairing of the siRNAs carried by AGO4. Finally, DNA methylation is catalyzed by DRM2, allowing the deposition of repressive chromatin marks (H3K9me2) [START_REF] Castel | RNA interference in the nucleus: roles for small RNAs in transcription, epigenetics and beyond[END_REF]. In contrast, the silencing of transcribed or unmethylated TEs is mediated by RNA-dependent RNA polymerase 6 (RDR6) that produces 21-22 nt siRNAs triggering RNAi and ab initio DNA methylation, in a process known as RDR6-RdDM [START_REF] Nuthikattu | The Initiation of Epigenetic Silencing of Active Transposable Elements Is Triggered by RDR6 and 21-22 Nucleotide Small Interfering RNAs[END_REF]. RDR6-RdDM is essential for triggering silencing of active transposons. Previous studies have shown that initial cleavage of mRNA is a critical prerequisite for RDR6 recognition and that siRNA production is confined in the cell space to siRNA vesicles co-localized with RDR6 and SGS3. To investigate how RDR6 specifically recognizes transposon transcripts and selectively process siRNA, a recent study demonstrated that plant transposon RNAs contain non-optimal codons leading to a common ribosomal arrest during translation.

That ribosomal arrest subsequently induces RNA truncation and localization to cytoplasmic siRNA vesicles [START_REF] Kim | Ribosome stalling and SGS3 phase separation prime the epigenetic silencing of transposons[END_REF].

Genome instability mediated by TEs

A major structural effect of TE insertion on the genome is that it can cause dramatic changes in chromosome structure both through the embedding of genes or gene fragments upon recombination and through the induction of chromosome rearrangements [START_REF] Feschotte | DNA transposons and the evolution of eukaryotic genomes[END_REF]. Chromosomal rearrangements may involve a number of mechanisms that affect DNA structure and play an important role in genome evolution. For instance, TE copy number contribute to variation in genome size within the genus Oryza [START_REF] Piegu | Doubling genome size without polyploidization: Dynamics of retrotransposition-driven genomic expansions in Oryza australiensis, a wild relative of rice[END_REF][START_REF] Hurwitz | Rice structural variation: a comparative analysis of structural variation between rice and three of its closest relatives in the genus Oryza[END_REF]; In the maize genome, translocations of Ac elements can lead to deletions, inversions, translocations or other rearrangements [START_REF] Yu | A transgenic system for generation of transposon Ac/Ds-induced chromosome rearrangements in rice[END_REF]; This type of movement, can allow the insertion and duplication of genes or gene fragments into new chromosomal environments, sometimes altering their regulation, which may then lead to the emergence of new phenotypic features [START_REF] Liu | Evolutionary interplay between sister cytochrome P450 genes shapes plasticity in plant metabolism[END_REF]. These rearrangements may also lead to the formation of "island", such as a set of sequences with both genes and TEs, facilitating local adaptation [START_REF] Turner | Chromosomal rearrangements as a source of local adaptation in island Drosophila[END_REF].

TEs in the form of extrachromosomal circular DNA (eccDNA)

As the genetic material of life, DNA can be divided into linear form, such as genomic chromosomal DNA, and circular form. Circular DNA includes organelles (mitochondria and chloroplasts), most bacteria, and some viral genomic DNA. Extrachromosomal circular DNA (eccDNA) refers to extrachromosomal, non-organelle and circular structural DNA found in eukaryotes. It has been observed in many eukaryotic species for decades, including yeast, Drosophila, nematodes, plants and humans (Hotta and Bassel, 1965;Hirochika and Otsuki, 1995;Sinclair and Guarente, 1997;Cohen and Méchali, 2002;[START_REF] Cohen | Mouse major satellite DNA is prone to eccDNA formation via DNA Ligase IV-dependent pathway[END_REF]Kumar et al., 2017). In plants, eccDNA is found to originate from tandem repeats (such as ribosome DNA copies or telomeric repeats) but also active TEs (Hotta and Bassel, 1965;Lanciano et al., 2017).

The discovery of eccDNA greatly predated the completion of the Human Genome Project, and no sequence analysis was performed, until recently. In the past few years, with the prevalence of high-throughput sequencing, eccDNA has been studied in a spurt and its role, notably in cancer cells, was revealed (Verhaak et al., 2019). Because of the huge variation in size: ranging from hundreds of base pairs to hundreds of kilobase pairs, extrachromosomal circular DNA has been classified into: 1) microDNA, which mainly refers to circular DNA within 400 bp (Shibata et al., 2012); 2) ecDNA (extrachromosomal DNA), which describes extrachromosomal DNA found in cancer cells that is hundreds of kb in size or more, and is large enough to comprise full-length genes and DNA replication initiation sites. EcDNA can replicate and amplify autonomously, and thus is associated with oncogene amplification and cancer development [START_REF] Turner | Extrachromosomal oncogene amplification drives tumour evolution and genetic heterogeneity[END_REF][START_REF] Zhu | Oncogenic extrachromosomal DNA functions as mobile enhancers to globally amplify chromosomal transcription[END_REF]; 3) In contrast, eccDNA refers to all extrachromosomal circular DNAs smaller than ecDNA.

Our laboratory previously developed eccDNA-seq (or mobilome-seq) to selectively sequence eccDNA from any plant or animal tissue (Lanciano et al., 2017(Lanciano et al., , 2021)). The method involves first digesting linear DNA using an ATP-dependent DNase and then enriching circular DNA by rolling cycle amplification. Circle-seq established in yeast (Møller et al., 2015) and CIDER-seq established in plants and virus [START_REF] Mehta | Full-length sequencing of circular DNA viruses and extrachromosomal circular DNA using CIDER-Seq[END_REF] are similar methods, increasingly coming to be used in the cancer field.

In cancer research, eccDNA is a key feature which can encode a variety of genes that promote tumor development (Kumar et al., 2017) and drug resistance [START_REF] Yan | Current understanding of extrachromosomal circular DNA in cancer pathogenesis and therapeutic resistance[END_REF].

eccDNA is also able to promote the transcription of oncogenes through highly open chromatin and ultra-long-range regulation (Wu et al., 2019). Furthermore, oncogenes and their adjacent enhancers can be amplified as eccDNAs, suggesting that eccDNA plays a central role in accelerating tumor evolution. Notably, eccDNA-seq in neuroblastoma not only identified a variety of unidentified eccDNA, but also revealed that eccDNA is a major source of genomic rearrangement in somatic cells, revealing that eccDNA leads to oncogenic gene rearrangement through chimeric cyclization and reintegration into the linear genome (Koche et al., 2020). The fetal eccDNA detected in pregnant women's plasma can be used as a novel non-invasive molecular marker for prenatal testing, suggesting that eccDNA does not only play a significant role in tumor development, but may also be a highly promising molecular marker [START_REF] Sin | Identification and characterization of extrachromosomal circular DNA in maternal plasma[END_REF].

Given that a large number of TEs in the genome are activated during early embryonic development and are capable to reinsert and destabilize the genome, it is an important scientific question to understand how the embryo can avoid the damage caused by activated TEs. Wang et al., proposed that the activated TEs end up as eccDNA thus preventing their reinsertion in the genome (Wang et al., 2021c). With full-length sequence and genomic origin location information of more than 1.6 million eccDNA extracted from mouse embryonic stem cells, they proved that (1) eccDNA is randomly derived from chromosomal genomic DNA with no apparent location or sequence specificity; (2) eccDNA is a cyclization product of Lig3-mediated apoptotic DNA fragments; (3) and eccDNA has a superb ability to stimulate innate immune responses. (Wang et al., 2021c).

Obtaining a high-quality genome assembly prior to TE annotation

Note that the following part will serve as a basis for a review on genome assembly and structural variation in plants.

What is a genome assembly

In order to annotate the full picture of TEs in a given genome, it is necessary to obtain a high-quality genome assembly. The process of reconstructing the original genome from the millions of reads generated by high-throughput sequencing platforms from scratch is named de novo assembly. Some basic terms are involved: a contig refers to a long fragment formed by the assembly of multiple reads; a scaffold is a longer fragment formed by joining multiple contig sequences. Since the orientation and order of these contigs have been determined, the linkage between contigs is generally denoted by NNNN [START_REF] Nagarajan | Sequence assembly demystified[END_REF][START_REF] Compeau | How to apply de Bruijn graphs to genome assembly[END_REF][START_REF] Miller | ReadDepth: A Parallel R Package for Detecting Copy Number Alterations from Short Sequencing Reads[END_REF][START_REF] Nagarajan | Sequence assembly demystified[END_REF][START_REF] Sohn | The present and future of de novo whole-genome assembly[END_REF]. Note that the overlap between reads is the core of the assembly algorithm. A graph which refers to a network of nodes (points) connected by edges (bridges), represents overlapping reads [START_REF] Compeau | How to apply de Bruijn graphs to genome assembly[END_REF][START_REF] Rizzi | Overlap graphs and de Bruijn graphs: data structures for de novo genome assembly in the big data era[END_REF].

Three criteria, namely completeness, correctness and contiguity are assessed to measure the quality of genome assembly [START_REF] Gurevich | QUAST: quality assessment tool for genome assemblies[END_REF][START_REF] Mikheenko | Versatile genome assembly evaluation with QUAST-LG[END_REF][START_REF] Seppey | BUSCO: Assessing Genome Assembly and Annotation Completeness[END_REF]. Completeness requires that the total length of the assembled sequence be as large as possible in proportion to the length of the genomic sequence; correctness requires that the assembled sequence conform as closely as possible to the true sequence; contiguity requires that the length of the sequences obtained by assembly is as long as possible, measured by the N50. N50 reflects the smallest contig length so that 50% of the entire assembly is contained in contigs equal to or larger than this value. If all contigs are sorted from longest to shortest (e.g., Contig 1, Contig 2, Contig 3,,, Contig 25), the added contig for which the total length of the contigs reaches 50% of the entire assembly, gives the N50. The higher the value of N50, the longer the contiguity of the assembly.

The revolution of long read sequencing technologies

Due to the fact that plant genomes are large, complex, and have a large number of repetitive regions, it is difficult to obtain high-quality genome assemblies [START_REF] Michael | Building near-complete plant genomes[END_REF]. In particular, genome assembly is limited by short sequencing technologies and related assembly algorithms. The main challenges rely on (1) read length being very short compared to genome length, producing a puzzle with millions to billions of pieces; (2) lots of overlaps between reads due to short length making assembly ambiguous; (3) highly repeated regions causing difficulties in genome assembly. In addition, the insufficient sequencing depth, which refers to the ratio of the total number of bases obtained by sequencing to the size of the genome to be sequenced, will leave gaps in assembly algorithms [START_REF] Alkan | Limitations of next-generation genome sequence assembly[END_REF][START_REF] Sohn | The present and future of de novo whole-genome assembly[END_REF].

In the last four years, long-read sequencing technologies offered by two fundamentally different platforms: Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) have emerged as a strong player in the genomics field. PacBio SMRT (single molecule real time sequencing) technology applies the idea of sequencing while synthesizing and uses the SMRT chip as the sequencing vector. In the base pairing stage, the addition of different bases (4 bases will be 4-color fluorescence labeled), will emit different light. According to the wavelength and peak of light, the type of bases entered can be determined [START_REF] Eid | Real-Time DNA Sequencing from Single Polymerase Molecules[END_REF]. Of all the long reads generated by Pacbio sequencing, including continuous long reads (CLR) and cyclic consensus sequencing reads (CCS), as well as the latest high-fidelity (HiFi) reads, HiFi reads have the highest accuracy rate (99%). Nanopore sequencing technology is based on a special nanopore with covalent binding for sequencing. When DNA bases pass through the nanopore, they cause a change in charge that transiently affects the strength of the current flowing through the pore, and sensitive electronics detect these changes to identify the bases being passed [START_REF] Ashton | MinION nanopore sequencing identifies the position and structure of a bacterial antibiotic resistance island[END_REF]. Advances in average read length, optimized assembly algorithms, and software have greatly contributed to the integrity and quality of genome assemblies. Gap filling, haplotype phasing, construction of very long genomes, and pangenome remain key breakthroughs for future plant genome assembly [START_REF] Marx | Long road to long-read assembly[END_REF][START_REF] Sun | Twenty years of plant genome sequencing: achievements and challenges[END_REF] that will be introduced below.

Assembling centromeres: first « gap free » plant genomes

Gap free (also known as genome completion map) is the highest standard for genome assembly, and the construction of a gap free genome not only provides the most comprehensive reference genome information for population genetic studies and gene function localization, but also allows for structural and functional analysis of the centromeric and telomeric regions.

The Arabidopsis thaliana (ecotype Columbia-0 or Col-0) genome sequence was published in 2000, and after decades of research, the reference genome has become the "gold standard". However, the enrichment of highly repetitive sequence units in centromeric, telomeric and nucleolar organizing regions (NORs) has left these regions either with assembly errors or not sequenced. To obtain the telomere-to-telomere A.

thaliana Col-0 genome, Wang et al. (2021) introduced the bacterial artificial chromosome (BAC)-anchored sequence substitution strategy into the Col-XJTU genome assembly strategy, resolving the complete centromeric sequence of chromosomes 3, 4, and 5 and partially centromeric sequence of chromosomes 1 and 2.

The A. thaliana Col-XJTU genome was assembled with high accuracy, and the sequencing quality score was significantly higher than that of TAIR10.1 (Wang et al., 2021a). To assess simultaneously genetic and epigenetic features of the centromeres, Naish et al. assembled a highly contiguous A. thaliana Col-0 genome using ultra-long reads generated by ONT, filling the gap of centromeres and providing an in-depth landscape of centromere evolution. The resulting Col-CEN assembly reveals the detailed architecture of the A. thaliana centromeres, i.e., the retrotransposon ATHILA interfering with the CEN180 satellite arrays and DNA methylation inhibiting the meiotic DNA double stand breaks within centromeres. Thus, A. thaliana centromeres evolved under the opposing forces of satellite homogenization and retrotransposon interference (Naish et al., 2021).

In the construction of two gap-free rice genomes, [START_REF] Song | Two gap-free reference genomes and a global view of the centromere architecture in rice[END_REF] used high-depth Pacbio sequencing to assemble 0 gap genomes of ZS97 and MH63 (genome size 391.56Mb and 395.77Mb, respectively). Based on these gap free reference genomes, they investigated the structure and function of the centromeric region on 12 rice chromosomes in detail and found that the length of the core region of the centromeric region differed 10-fold on different chromosomes. In the ZS97 and MH63 centromeric regions, a total of 395 and 539 non-TE genes were identified respectively, but their transcriptional activity and the percentage of specific expression were low, and most of the actively transcribed genes were located in the peri-centromeric region. Additionally, they found that the similarity of CentO, which refers to a 155-bp satellite repeat [START_REF] Dong | Rice (Oryza sativa) centromeric regions consist of complex DNA[END_REF], in the same chromosome was higher than that across chromosomes; the length of CentO satellite repeat sequences in the core region of the same chromosome differed significantly between varieties in the same subspecies (or natural population) of Asian rice [START_REF] Song | Two gap-free reference genomes and a global view of the centromere architecture in rice[END_REF].

In general, due to the complex structure and large number of repetitive regions in the centromeric regions, the road to constructing a plant genome completion map is extremely winding, and often requires a combination of different sequencing platforms, different sequencing modes, and different assembly softwares. Using PacBio HiFi sequencing to take advantage of the results of different assembly softwares and adding manual error correction may make the journey of constructing a plant genome completion map a little easier (Wang et al., 2021;[START_REF] Song | Two gap-free reference genomes and a global view of the centromere architecture in rice[END_REF].

The challenge of assembling very large plant genomes

Very large genomes usually have highly repetitive sequences, high heterozygous segments, and it is challenging to decipher their complete genome sequences.

For instance, garlic (Allium sativum) has a unique smell and high economic value, but its high heterozygosity and large genome size had hampered the characterization of its genome sequence. Combining PacBio, Nanopore, Illumina, 10X Genomics and Hi-C technology, [START_REF] Sun | A chromosome-level genome assembly of garlic (Allium sativum) provides insights into genome evolution and allicin biosynthesis[END_REF] have constructed a chromosome-level reference genome of garlic with a genome size 16.24Gb. Comparative genome analysis showed that the root cause of the huge garlic genome is multiple whole genome duplication (WGD) events and rapid expansion of repeat sequences. Combined with the transcriptome data, they also established the allicin biosynthesis pathway and identified 4 genes related to the accumulation of garlic alliinase [START_REF] Sun | A chromosome-level genome assembly of garlic (Allium sativum) provides insights into genome evolution and allicin biosynthesis[END_REF].

As a typical relict species, Ginkgo biloba is the only extant member of the Ginkgo family.

The assembled genome assembled is 9.88 Gb in size (contig N50=1.58 Mb), and 27,832 protein-coding genes have been annotated. The intron length is the largest among the plant species studied so far, further suggesting that repetitive sequences not only facilitate genome expansion but also increase the size and complexity of proteincoding genes. Both genome and transcriptome studies helped understanding some of the ginkgo specific phenotypes, such as the preserved sperm flagellum, unformed flowers, and fan-shaped leaves, important features for environmental adaptations and gymnosperm evolution in Ginkgo (Liu et al., 2021).

Conifers are also known for their gigantic genomes. [START_REF] Xiong | The Taxus genome provides insights into paclitaxel biosynthesis[END_REF] constructed a reference genome at the chromosome level of southern Taxus (Taxus chinensis Rehd. var. mairei) with a genome size of 10.23 Gb (contig N50=2.44 Mb), using DNA extracted from endosperm call containing haploid chromosomes.

Comparative genomic analysis showed that a WGD event occurred in the Taxus genus, and the unique families of Gypsy and Copia retrotransposons have expanded in this genus. Taxus conifers are used for the production of paclitaxel (Taxol for the commercial name), a well-known anti-cancer drug. Combining genomic, transcriptomic and metabolomic data, the authors showed that the paclitaxel synthesis-related genes are organized and co-expressed as clusters. They further identified a gene cluster consisting of six genes in tandem that is responsible for the first two steps of paclitaxel biosynthesis [START_REF] Xiong | The Taxus genome provides insights into paclitaxel biosynthesis[END_REF].

Resolving haplotypes in plant genomes

Genome haplotyping aims at reflecting the differences in allele composition between homologous chromosomes and is critical for genomic analyses for many plant and animal models, notably for polyploid organisms.

The pineapple strawberry (Fragaria × ananassa), which is widely grown around the world, is an octoploid complex genome formed by crossing the wild Virginia strawberry (Fragaria virginiana) with the Chilean strawberry (Fragaria chiloensis). The parents are wild-type octoploids and are derived from four diploid ancestral species. [START_REF] Edger | Origin and evolution of the octoploid strawberry genome[END_REF] have used second-and third-generation sequencing techniques, combined with 10X Genomics and Hi-C, to construct a nearly complete genome (805.5 Mb) of the bromeliad strawberry, combined with transcriptome data, to provide a new basis for the evolutionary history of the origin of the octoploid strawberry. Transcriptome sequencing of 31 RNAseq datasets from four diploid strawberries and phylogenetic analysis of octoploid strawberries in combination with geographic distribution and historical evolution showed that octoploid strawberries originated in North America, and also indicated that Fragaria iinumae, Fragaria nipponica, Fragaria viridis and Fragaria vesca are the ancestral species of the octoploid strawberry. In addition, the evolutionary dynamics analysis of strawberry disease resistance genes (R genes) showed that TEs are closely related to R gene expression (e.g., Fragaria vesca subgenome has increased gene expression and its TE density is the lowest compared to the other three diploid strawberry species), leading to the identification of a dominant subgenome in strawberry [START_REF] Edger | Origin and evolution of the octoploid strawberry genome[END_REF]. [START_REF] Zhou | Haplotype-resolved genome analyses of a heterozygous diploid potato[END_REF] resolved the haplotyped genome of an heterozygous diploid potato using a complex strategy based on long read sequencing and genetic mapping (assembly size 1,67 Gb, N50=2Mb). Briefly, they produced two assemblies using (1) ONT data and 10xGenomics and (2) PacBio HiFi reads, respectively. For each assembly, the scaffolds were assigned to the 24 genetic groups (2n=24) thanks to the resequencing data of an F2 population. Then the authors used Hi-C data to perform a scaffolding step combining the two assemblies into a final one. Comparative analysis of the two sets of haplotyped sequences revealed the presence of more than 20,000 deleterious mutations in the diploid potato, with 16.6% of alleles differentially expressed and 30.8% differentially methylated. These mutations are dispersed in the genome. The authors located on the phased genome several loci involved in inbreeding depression and displaying segregation distortion. For instance, the seedling albino gene (white seedling WS1) and the plant architecture gene (PA1) are two linked genes on chromosome 1. The deleterious genotypes of these two genes (ws1 and pa1) are located on two different haplotypes and closely linked to the « normal » genotypes (WS1 and PA1) with very low segregation probability in the offspring (2 recombinants out of 1200 screened F2 plants). The phased genome thus offers the possibility to improve breeding in this clonally propagated plant. Importantly, the authors highlight the fact that despite the use of long-reads and HiC data, the availability of genetic data was instrumental in the determination of this large haplotype-resolved genome [START_REF] Zhou | Haplotype-resolved genome analyses of a heterozygous diploid potato[END_REF]. (Zhang et al., 2021a). Despite the two above-mentioned genome assemblies of diploid potato, the homozygous tetraploid genome of cultivated potato had not been assembled and genomic haplotyping of the tetraploid potato remained a challenge. In a recent BiorXiv study, inbred homozygous tetraploids were successfully haplotyped. In this analysis, the haplotigs (contigs representing only one haplotype) were determined using a large dataset of diploid gamete sequences (717 short-reads low-coverage single-cell sequencing of pollen cells), reasoning that from this large number the underlying sets of haplotypes could be uncovered. Then HiFi reads were assigned to each haplotig and HiC data was used for scaffolding. The authors noted that when assembling the long reads first, around one third of the haplotypes were collapsed and could not be subsequently untangled. This analysis revealed that 50% of the tetraploid genome is fragmentally identical in at least two haplotypes. This high level of inbreeding contrasts with the extreme structural rearrangements found in about 20% of the genome and enriched for retrotransposons. In addition, 148,577 gene were annotated, of which only 54% were present in all four haplotypes, with an average of 3.2 copies for each gene (Sun et al., 2021a), reinforcing the importance of obtaining phased genomes.

Today, the improvement of technology and algorithms has greatly improved our capacities to address the challenge of obtaining phased plant genomes with a high sequence resolution. In this context, HiFi reads have proved to be more promising for haplotype-resolved assembly than ONT reads due to their accuracy. Indeed, the combination of high read length and improved base accuracy is a game changer. One current way to obtain phased information through HiFi reads is: (1) to use HiFi reads to sequence a single individual; (2) to use diploid genome assembly softwares, such as hifiasm [START_REF] Cheng | Haplotyperesolved de novo assembly using phased assembly graphs with hifiasm[END_REF] or HiCanu [START_REF] Nurk | HiCanu: accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads[END_REF] for genome assembly; (3) to use softwares including Google DeepVariant [START_REF] Poplin | A universal SNP and small-indel variant caller using deep neural networks[END_REF] for mutation detection, and use WhatHap [START_REF] Patterson | WhatsHap: Weighted Haplotype Assembly for Future-Generation Sequencing Reads[END_REF] for haplotype phasing; (4) to combine HiFi data with other technologies such as Hi-C or Strand-seq to extend haplotype phasing to chromosomes, enabling phase analysis of the entire genome. Eventually, if there are three samples available from both parents and offspring, before the genome is assembled, the short read data from the parents can be used to phase the HiFi data into the respective parental data [START_REF] Sun | A chromosome-level genome assembly of garlic (Allium sativum) provides insights into genome evolution and allicin biosynthesis[END_REF][START_REF] Garg | Computational methods for chromosome-scale haplotype reconstruction[END_REF]Sun et al., 2021a;Zhang et al., 2021a).

Pan-genomes: One genome is not enough

In the last two years, the comparative analysis of genomes or genome fragments of multiple individuals of the same species has shown that a single reference genome is not enough to capture the genetic diversity of a species [START_REF] Bayer | Plant pangenomes are the new reference[END_REF]. These findings indicate that the genome within a species may differ in more significant ways, including the diversity of structural variants (SV), and these variants may contain one or more genes. A large number of studies have shown that SVs play a key role in important agronomic traits, such as resistance to biotic and abiotic stress, flowering time, plant architecture, yield, grain or fruit quality (for a review see [START_REF] Tao | Exploring and Exploiting Pan-genomics for Crop Improvement[END_REF]. These results imply that the functional gene content of a species is more variable than previously thought. Therefore, for a species, if only a single reference genome is used for the study of genetic domestication and/or selection, a lot of meaningful genetic information may be lost. The above factors have jointly promoted the construction and research on plant and animal pan-genomes.

Pan-genome is a general term for all genes of a species, where the whole genes are distinct from those of the individual genome [START_REF] Tettelin | Genome analysis of multiple pathogenic isolates of Streptococcus agalactiae: Implications for the microbial "pan-genome[END_REF]. The genome of an individual is not representative of the genome of the species. Therefore, the analysis of a genome as a reference does not provide a complete picture of the genetic information of a species at the gene level, especially when studying different subspecies or variants of the same species, where the differences in such unique segments are often more important than those in the shared segments. The analysis of core and non-core genes is fundamental to the study of within-species variation from the perspective of unique gene sequences [START_REF] Bayer | Plant pangenomes are the new reference[END_REF]. It has been conducted in various model and crop plants including A. thaliana [START_REF] Jiao | Chromosome-level assemblies of multiple Arabidopsis genomes reveal hotspots of rearrangements with altered evolutionary dynamics[END_REF], tomato [START_REF] Gao | The tomato pan-genome uncovers new genes and a rare allele regulating fruit flavor[END_REF]Alonge et al., 2020), rice (Qin et al., 2021), soybean (Liu et al., 2020b), rapeseed [START_REF] Song | Eight highquality genomes reveal pan-genome architecture and ecotype differentiation of Brassica napus[END_REF]Chawla et al., 2021), wheat [START_REF] Walkowiak | Multiple wheat genomes reveal global variation in modern breeding[END_REF], barley [START_REF] Jayakodi | The barley pan-genome reveals the hidden legacy of mutation breeding[END_REF] and maize (Hufford et al., 2021) et al., 2016), the degree of genomic variation within this species is still poorly understood due to the small number of chromosome-level assemblies. Jiao and Schneeberger's study provided chromosome-level reference assemblies of seven Arabidopsis germplasms, selected from across the globe. In each genome rearrangements of 13-17 Mb in length were detected, as well as 5-6 Mb of nonreference sequences, causing copy number variations (CNVs) in approximately 5,000 genes (including approximately 1,900 non-reference genome-containing genes).

Quantifying the variability between genomes revealed approximately 350 autosomal regions where tandem duplications had occurred. Interestingly, these rearrangement hotspot regions are enriched in genes associated with biotic stress response and display reduced meiotic recombination in hybrids. This suggests that the rearrangement hotspots have undergone differential evolutionary dynamics compared to the rest of the genome, largely based on the accumulation of new variants rather than on recombination of existing variants, allowing for a rapid response to biotic stresses [START_REF] Jiao | Chromosome-level assemblies of multiple Arabidopsis genomes reveal hotspots of rearrangements with altered evolutionary dynamics[END_REF].

The rapeseed pan-genome of 1.8 Gb was constructed based on the genome sequences of 8 Brassica napus germplasms assembled on PacBio, HiC, BioNano platforms, containing about 150,000 genes [START_REF] Song | Eight highquality genomes reveal pan-genome architecture and ecotype differentiation of Brassica napus[END_REF]. Genome-wide association studies (GWAS) based on presence and absence variations (PAVs) identified previously undiscovered differences in traits caused by TE insertion, and differential expression of genes related to different traits caused by PAV among different ecotypes. The study focused on three types of SVs in the FLC gene, involved in flowering time and vernalization. PAV-GWAS peaks corresponded to insertions of a hAT transposon in a BnaA02.FLC exon and the BnaA10.FLC promoter that correlated with early and late flowering, respectively. The genome assemblies further revealed four TE insertions polymorphisms at the BnaC02.FLC locus. Interestingly, the haplotypes of the TEs were more consistent with ecotype information and flowering time than the haplotypes of the SNPs. A LINE insertion in the first exon of BnaA10.FLC in spring oilseed rape leads to a loss of function, and spring rape needs weak or no vernalization to flower. In contrast, a MITE insertion in the BnaA10.FLC promoter upregulates FLC expression, and winter rape requires stronger vernalization to bloom. In conclusion, this study revealed the molecular basis of winter and spring flowering regulation through pan-genome and PAV-GWAS approaches [START_REF] Song | Eight highquality genomes reveal pan-genome architecture and ecotype differentiation of Brassica napus[END_REF].

The rice pan-genome was constructed based on 31 high-quality genome assemblies and two published rice genomes, Nipponbare and Shuhui 498 (Qin et al., 2021), identifying 171,072 SVs and 25,549 gene copy number variations (gCNVs). Detailed studies on the mechanism of SV formation, the effect of SV on gene expression, and the distribution of SV among subpopulations were conducted, demonstrating how SVs and gCNVs affect environmental adaptation and domestication in rice. Especially most of genomic variants had not been found in previous studies that used traditional short read methods, but they play an important role in the regulation of important agronomic traits. For example, the tandem duplication of the OsMADS18 gene in Koshihikari variety was identified by long reads. Considering that increased expression of OsMADS18 has been shown to cause early flowering, it can be inferred that the duplication of OsMADS18 may be the cause of the early flowering phenotype of this variety. In addition, the graphical pangenome-based SV-GWAS identified many phenotype-related genetic variants that could not be detected when using only SNPs and single reference combinations.

Maize is the most widely grown crop in the world and an important model system for studying gene function with high genetic diversity. A pan-genomic analysis was performed on maize nested association mapping (NAM) populations. A total of 26 lines from 25 NAM populations and B73 were selected to construct a pan-genome of maize containing 100,000 genes with only one-third present in all 26 maize lines (Hufford et al., 2021). GWAS analysis based on SNP and SV showed that 93.05% of SNP and SV loci overlapped with each other. However, SV-GWAS, but not SNP-GWAS, identified an association locus for blast disease on chromosome 10, indicating that combining SNP-GWAS and SV-GWAS could improve the accuracy of trait-gene association (Hufford et al., 2021).

Structural variants in the plant genome

Why to detect structural variants (SVs)?

Variants are the most important factors leading to genomic differences and can be specifically classified as single base pair variants, small insertions or deletions, and structural variants [START_REF] Mérot | A Roadmap for Understanding the Evolutionary Significance of Structural Genomic Variation[END_REF]. Single nucleotide variants, often called single nucleotide polymorphisms (SNPs), are differences in individual DNA bases. Small indels (short for insertion and deletion) refer to the insertion or deletion of a small fragment of sequence, usually under 50 bp in length. Structural variants (SVs) refer to the alteration of chromosomal fragments different from the reference genome, usually larger than 50bp. The main types of SVs include insertion deletion, duplication, inversion and translocation (Carvalho and Lupski, 2016). Inversion is when a large segment of DNA is reversed compared to the reference genome. Translocation is when a large segment of DNA is moved out of one place and inserted into another [START_REF] Stankiewicz | Structural variation in the human genome and its role in disease[END_REF].

Importantly, SVs are closely related to a number of key agronomic or breeding-related traits and the basis for crop improvement and domestication. Multiple SVs detected in 100 tomatoes were able to alter gene dosage and expression levels, resulting in changes in taste, size, and yield traits (Alonge et al., 2020). [START_REF] Zhou | A 1.7-Mb chromosomal inversion downstream of a PpOFP1 gene is responsible for flat fruit shape in peach[END_REF] identified a chromosomal inversion of 1.67 Mb in the flat peach genome located approximately 3 Kb downstream of the PpOFP1 gene stop codon (a gene of the OVATE family involved in transcriptional repression). This chromosomal inversion, which is not present in common peaches, is responsible for the change from round to flat peaches (Zhou et al., 2021). In addition, several studies have shown that structural variation can better resolve population structure and provide further valid information to gain insight into plant domestication processes (Alonge et al., 2020;Hufford et al., 2021;Qin et al., 2021).

Algorithms of SV detection

With the rise of second and third-generation sequencing, the throughput of SV detection has started to improve. The SV detection algorithms rely on read depth, short-read pairs, long read alignment or de novo assembly, and these four types of algorithms have some differences in detection accuracy and the range of detectable structural variation (Figure I.8) [START_REF] Mahmoud | Structural variant calling: the long and the short of it[END_REF][START_REF] Mérot | A Roadmap for Understanding the Evolutionary Significance of Structural Genomic Variation[END_REF]. Read depth method assumes that sequencing reads are randomly distributed (e.g., Poisson distribution). Duplicated and missing intervals are calculated primarily by the longitudinal coverage of sequencing reads within a specified region. The duplicated intervals have a higher depth, while the missing intervals have a lower sequencing depth. This method is commonly used for the detection of genomic copy number variation (CNV) as read depth of a genomic region is correlated with its copy number [START_REF] Miller | ReadDepth: A Parallel R Package for Detecting Copy Number Alterations from Short Sequencing Reads[END_REF]. The short read-pair method is based on the distance between the paired-end reads and their direction. Paired-end reads are mapped to the reference genome to identify pairs of abnormal reads, and then the abnormal regions are extracted. Based on the location, size, and number of abnormal reads, the corresponding SVs are determined. Split read pair allow to uncover sequences that may come from different intervals of the genome [START_REF] Cameron | Comprehensive evaluation and characterisation of short read general-purpose structural variant calling software[END_REF][START_REF] Mahmoud | Structural variant calling: the long and the short of it[END_REF]. This principle was applied to characterize new TE insertion polymorphisms (TIPs). On the base of the case where one of the two paired-end reads can match to a certain TE normally, but the other cannot, and the unmatched read maps to the reference genome, many tools have been developed to detect TE insertions from short-read sequencing, such as ngs_te_mapper [START_REF] Linheiro | Whole Genome Resequencing Reveals Natural Target Site Preferences of Transposable Elements in Drosophila melanogaster[END_REF], RelocaTE [START_REF] Robb | The Use of RelocaTE and Unassembled Short Reads to Produce High-Resolution Snapshots of Transposable Element Generated Diversity in Rice[END_REF], PoPoolationTE2 (Kofler et al., 2016, 2), TRACKPOSON [START_REF] Carpentier | Retrotranspositional landscape of Asian rice revealed by 3000 genomes[END_REF] and TEMP2 [START_REF] Yu | A benchmark and an algorithm for detecting germline transposon insertions and measuring de novo transposon insertion frequencies[END_REF].

However, all the methods mentioned above are actually limited by the fact that the reads are too short. Because the reads are too short, they cannot span genomic repeat regions during comparison; nor can they capture many large insertion sequences. To overcome the limitations of tools developed with short sequencing reads, many tools emerged from the use of long-read sequencing data, such as cuteSV [START_REF] Jiang | Long-read-based human genomic structural variation detection with cuteSV[END_REF], Sniffles2 (Sedlazeck et al., 2018;[START_REF] Smolka | Comprehensive Structural Variant Detection: From Mosaic to Population-Level[END_REF] and pbsv (https://github.com/PacificBiosciences/pbsv). However, introducing long sequences requires considering the relatively high sequencing price, hammering its wide application to population genomics. Ideally, long-read based de novo assembly should be the most efficient method for genomic SV detection, as it can detect all types of SVs [START_REF] Mahmoud | Structural variant calling: the long and the short of it[END_REF][START_REF] Mérot | A Roadmap for Understanding the Evolutionary Significance of Structural Genomic Variation[END_REF].

Visual validation for SV prediction

Visual validation is an important step in reducing false positives for structural SV prediction. To visualize SVs from read mapping, Belyeu et al. have developed Samplot, a tool that visualizes read depth and sequence alignment pairs for predicting so-called SV across regions (Belyeu et al., 2021). Samplot is applicable to many biological problems such as SV prioritization in disease research, genetic variation analysis or ab initio SV prediction. It includes a machine learning package that significantly reduces the number of false positives without eye review. Tools such as the Integrative Genomics Viewer (IGV) are also useful for relatively small regions, allowing accurate SV detection at the base pair level [START_REF] Robinson | Integrative Genomics Viewer[END_REF]. However, IGV is very limited in displaying the alignment of large regions, slowing down the process of visual verification. Dot plot is a gold standard tool to detect SVs between genomes, including D-GENIES (Cabanettes and Klopp, 2018), shinyChromosome [START_REF] Yu | shinyChromosome: An R/Shiny Application for Interactive Creation of Non-circular Plots of Whole Genomes[END_REF] and ggplot2 mummerplot (https://jmonlong.github.io/Hippocamplus/2017/09/19/mummerplots-with-ggplot2/). Another popular tool is Syri (Goel et al., 2019). Methods used in the rice pangenome provide a good example (Qin et al., 2021). All 32 rice assemblies were matched against the IRGSP1.0 reference genome using Mummer4 (Marçais et al., 2018). The raw match results were further filtered using delta-filter and then subjected to detect SV using Syri. Then, based on the results of Syri, Qin et al. further subdivided the SVs into three major categories of resultant variants: presence/absence variants, inversions, and translocations.

JBrowse 2 (Buels et al., 2016) provides a superior visual review of SVs in read mapping and genome assembly, including modes for linear and circular genome view. It is able to visualize and analyze files in different formats using synteny analysis, dot plot, and SV inspector mode, which greatly reduces false positive SVs. There is no doubt that there are and will be many tools to visual validate SV detection. A user-friendly usage and high-quality figures produced are always welcome and the tools above are highly recommended.

Objectives of the thesis work and main achievements

The general objective of my work was to characterize the interplay between the eccDNA compartment and the genome. For this I focused on three aspects and technological developments.

First, despite the rapid development of high-throughput sequencing and the continuous updating of eccDNA-seq, the landscape and dynamics of eccDNA are poorly understood due to the lack of dedicated computational tools. To reach this objective, my first project was to fill the gap for tools dedicated to eccDNA detection, notably using long-read sequencing data. I thus developed ecc_finder, a new tool specifically for eccDNA detection from long-read data of eccDNA-seq. In addition, I optimized the algorithm for eccDNA detection from short-read data, previously developed in the group, to improve its computational performance. We tested the pipeline using Arabidopsis thaliana and wheat (genome sizes of 125Mb and 17Gb, respectively). To further evaluate the accuracy of the developed tool, datasets of experimentally validated eccDNA were be used. Second, to understand the impact of TEs on the genome, e.g. TE polymorphisms, a high-quality of genome assembly is required. However, different assemblies produced by different assemblers or the same assembler with different parameters have different performances. The best assembly with high contiguity and high repetition resolution cannot be achieved in one single assembly. My second project consisted in developing SASAR, a meta-assembly tool to reconcile the result of different long read assemblies.

In order to reconcile multiple assemblies and to resolve structural variants with accuracy, I used the strategy of assembly graph.

Finally, thanks to the ability to detect the dynamics of eccDNA and to obtain high quality genome assemblies with long read sequencing, I addressed the question of the impact of a high load of eccDNA on the genome structure. My third project was thus to explore the structural variants in A. thaliana epigenetic mutants with a high load of eccDNA. For this I detected eccDNAs in long-read eccDNA-seq and SVs in long-read assembled genomes, respectively.

Methods and Results

55

Ecc_finder: Developing a new tool for eccDNA detection

My contribution to ecc_finder

Our laboratory previously developed eccDNA-seq (or mobilome-seq) to selectively sequence the eccDNA form of active TEs in order to characterize the mobility of TEs in any plant or animal tissue (Lanciano et al., 2017a). To get familiar with this type of data, I started training on a dataset of Arabidopsis thaliana treated with heat stress. The method was based on a bash script developed by the former PhD student in the lab who developed eccDNA-seq. After examining the results generated at each step, I understood that this bash script was based on screening read coverage of short read mapping.

However, its subsequent steps were not standardized: firstly, the peak calling method was not precise and did not yield the exact boundaries of the eccDNA loci. Secondly, it is worth noting that although our experimental step was to obtain circular DNA enrichment by digesting linear DNA, high coverage of genomic loci was not always caused by circular DNA, and duplicated regions could also have a high coverage.

Therefore, it took me a long time to manually filter the output of this bash script and make it accurate. Considering that our laboratory collaborates with different institutes to provide eccDNA-seq sequencing for many plants and animals, there was a need to automate the eccDNA detection process and achieve a greater capacity, for example at the population level. Although it eventually worked, it still needed improvements to make it more fluid. What's more, I had noticed that sequencing eccDNA using long reads had started to emerge from 2020 (Koche et al., 2020), and had become a hot topic in cancer research. On the basis of my experience writing the pipeline for short reads, I further detected the characteristics of reads originating from circular loci from long read alignment on a dataset of Arabidopsis thaliana.

In order to produce a comprehensive tool that could be used for both short-read and long-read eccDNA-seq, I reasoned that more datasets were needed to support the normalization of the tool. I proposed a collaboration with the laboratory of Etienne Bucher (member of the EpiDiverse consortium) that was performing eccDNA-seq on the very large genome (17Gb) of wheat. Knowing that the larger the genome, the stronger the computational memory needed, I added an option to the aligner to decrease the computation time. A complete framework for the detection tool, which I called ecc_finder, was finally developed.

I contributed to the manuscript by writing a draft on the Results and Discussion sections and describing the usage and commands of ecc_finder on the wiki page on github. Our collaborator Haoran Peng provided us with the long-read sequencing data of wheat that I analyzed with ecc_finder. During the reviewing process I completely rewrote the Methods section and updated the wiki page on github and the ecc_finder manual accordingly. I further uploaded 5 videos of relevant commands on YouTube for the public without bioinformatics background. Finally, the software ecc_finder was published in Frontiers in Plant Science 2021.

Update on ecc_finder

Ecc_finder has gained some attention after its release. Anonymous researchers have asked 10 questions on github about other types of input, output interpretation, computational memory requirements, etc. I have answered them all accordingly. I am also considering a second version of ecc_finder, ecc_finder2, for processing lowcoverage whole-genome sequencing data and ATAC-seq data to explore its broader applications. Considering that ecc_finder2 needs reliable validation, it is best to train on datasets with known eccDNA loci, such as publicly available data from Arabidopsis thaliana.

During the writing of this thesis manuscript, I wondered whether eccDNAs could be either sequence-specific, locus-specific or tissue-specific. The recent study of eccDNA in mammal embryonic cells (using long read eccDNA-seq) gives a negative answer to sequence and locus specificity and mentions that eccDNAs may be generated by random breaks in genomic DNA, notably during apoptosis (Wang et al., 2021c). In this case the authors propose that eccDNAs originate from the entire genome, through random single fragment cyclizations and multifragment cyclizations of the genome producing between 200 bp and 3 kb circles (Wang et al., 2021c). Concerning the tissue specificity, in rice, eccDNAs generated by active TEs have been detected in endosperm tissue, but not in embryo or seed coat (Lanciano et al., 2017a). Similarly, tissue specific eccDNAs have been found in Arabidopsis flower, leaf, stem and root tissues (Wang et al., 2021b).

However, the latter study of eccDNA landscape in different tissues of Arabidopsis thaliana (Wang et al., 2021b) did not take into account that organelle DNA fragments transferred to the nucleus (such as NUPTs for nucleoplasmic DNA and NUMTs for nuclear mitochondrial DNA; Saccone et al., 2000;Yoshida et al., 2014) should be excluded from eccDNAs. Indeed these eccDNAs more likely originate from the organelles themselves, and not the NUPTs and NUMTs. For instance, there are 334 (45%) eccDNAs located in organelle genomes (mitochondria and chloroplast), 152 (20%) eccDNAs located in NUMTs and 79 (11%) eccDNAs located in NUPTs in the Wang et al. dataset. These eccDNAs derived from organelle sequences accounted for 76% of the total eccDNAs detected. In addition, 9 eccDNAs corresponded to ribosomal DNA repeats (rDNA) while 30 eccDNAs corresponded to centromeres (Figure II.1A). All these eccDNAs from organelle genomes, NUPTs and NUMTs, rDNA and centromeric repeats should be discarded in downstream comparisons. Therefore, the 604/743 (81%) eccDNAs detected in this study do not correspond to novel eccDNAs.

In order to really evaluate the differences between eccDNAs detected from leaf, flower, In conclusion for this part, because the field of eccDNA detection is becoming a hot topic, I would suggest to apply stringent computational methods for their rigorous detection. Wang et al. (2021). All eccDNA loci in Supplemental Table 1 were intersected with annotations including NUPTs and NUMTs, rDNA, and centromeric repeats using bedtools and then re-annotated. (B) Comparison of differences between eccDNA detected from leaf, flower, stem, and root tissues of Arabidopsis after removal of positive controls. (C) Intersection of eccDNAs between eccDNA detected from leaf, flower, stem, and root tissues of Arabidopsis in three replicates. 3 3 3 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 When I joined the lab in 2018, genome assembly with long-read sequencing had just started. At that time, about 14 plant genomes ranging in size from 120 Mb to 2.53 Gb had been sequenced with ONT, 5 of which were highly contiguous with N50 over 5 Mb.

However, while ONT rapidly developed new chemistry and basecall workflows to improve read accuracy, some issues with downstream bioinformatics analysis were left to the attempted genomic projects for various laboratories.

Therefore, we sought to establish a standard benchmark for new assembly tools relative to genome size prior to scaffolding using ONT sequencing. We benchmarked five stateof-the-art assembly tools and developed a meta-assembly tool using a super assembly tool from assembly reconciliation, namely SASAR. Genome contiguity, genetic integrity and other quality measures indicated that the A. thaliana Columbia assembly was comparable to or better than the gold standard reference genome TAIR10.1, filling 73% of the centromeric gaps.

However, the SASAR manuscript was rejected in 2019 and is now surpassed by other genome assemblies of A. thaliana. To follow up on future breakthroughs in assembly I updated SASAR's algorithm to implement the assembly graph, especially to annotate SV in the assembly. Although its release has been delayed, the updated version of SASAR will provide a pan-SV together with a genome assembly, which will be novel in the field. In the next section I summarize and give an update on the main results from the 2019 manuscript. other assemblies. This will create the minimum "pan-contigs" to all assemblies. In the second phase, SASAR will extend "pan-contigs". SASAR will go through two ends of the "pan-contigs" and information about contig extensions are recorded. The certain regions are further added to the head or tail of the aligned contigs (Figure II.2: step 2).

In the third phase, SASAR will correct mis-assemblies. Most assembly errors are due to repetitive sequences, especially transposable elements (TEs). Structural variants (SVs) detected from the "pan-contigs" via building assembly graph will be stored and annotated into different mechanisms. SVs present at least in any two assemblies will be used to correct "pan-contigs". Regions with TE domain will be expanded to find the boundaries of TE, and the insertion or deletion of internal paralogs will be polished based on the consensus of TE within the "pan-contigs". Several rounds of polishing will be performed and the SV at the point of discordant alignments will be recorded. Note that users have the option to break the contigs at points of potential mis-assembly (Figure II.2: step 3). As the last step, SASAR will rescue some small contigs. According to the user's choice, contigs that appear once in a particular assembly can be rescued (Figure II.2: step 4).

Figure II.2. Schematic pipeline of SASAR (Super ASsembly from Assembly Reconciliation).

Different colors represent contigs assembled by different long read assemblers.

Step 1: Identifying « pan-contigs », using whole genome alignment with minimap2.

Step 2: Extending "pan-contigs".

Step 3: Correct mis-assembly.

Step 4: Rescuing some small contigs. According to the user's choice, contigs that appear once in a particular assembly can be rescued.

Input: assemblies (n >=2)

Step 1: identify "pancontigs" from whole genome alignments.

Step 2: extend possible two ends of "pancontigs"

Step 3: correct misassembly via building assembly graph.

Step 4: rescue small contigs

SASAR performance on merging assemblies from different assemblers

We evaluated SASAR performance on three datasets and compared it with assemblies generated by five state-of-the-art assemblers, namely Canu, Flye, Shasta, Canu-SMARTdenovo and wtdbg2 (Table 1). Each assembly was aligned to the corresponding reference genomes using minimap2, and basic metrics were extracted using QUAST-

LG. In all assemblies of Arabidopsis datasets, SASAR assembly greatly balanced the longest NG50 of the SMARTdenovo assembly, the highest amount of BUSCO gene of the Flye assembly, and the highest resolution of centromeric repeats of the Canu assembly. It maintained an optimal continuity through 36 contigs and centromeric regions, with a total length approximately 10 Mb longer than TAIR10.1. In all assemblies of rice datasets, SASAR assembly kept the longest NG50 of the SMARTdenovo assembly and the highest score of BUSCO genes of the Canu assembly. In all assemblies of tomato datasets, SASAR assembly improved the reference assembly by 100Mbp (Table 1).

Notably, most of the extra 10 Mb genomic regions in the SASAR assembly of A. thaliana are centromeric regions. Compared to the estimated centromere size obtained from BAC sequencing, almost all centromeric sequences of chromosomes 2, 3, 4, 5 of A.

thaliana have been assembled (Figure II.3). The SVs detected between our A. thaliana SASAR-assembly and the gold-standard reference genome (TAIR10) enabled us to close 80% of all N-stretches within TAIR10 (not shown). Most of SVs that filled N-stretch were aligned to transposable elements and microsatellites, consistent with the previous finding that the A. thaliana centromeric regions are rich in repetitive DNAs. In the noncentromeric regions of the A. thaliana genome, one 1 kb insertion and one solo Copia LTR insertion were detected in chromosome 5, located at Chr5:2610117 and Chr5:7876830, respectively. The 1 kb insertion was further amplified by PCR (Figure II.4) and was identified in the Col-XJTU assembly (Wang et al., 2021a), showing that this insertion is not restricted to our plant material. Most importantly, SASAR assembly corrected large mis-assemblies mediated by TEs, which were not shown in Col-XJTU assembly (Wang et al., 2021a) and Col-CEN assembly (Naish et al., 2021). For instance, the mis-assembly of ONSEN/ATCOPIA78 in A. thaliana was confirmed in different sequencing technologies and datasets generated by different studies and also validated by PCR [START_REF] Gilly | TE-Tracker: systematic identification of transposition events through wholegenome resequencing[END_REF], indicating the sensitivity of SASAR assembly in the TE region.

Table 1. The quality and performance of long-read assemblies. The best value for each metric is highlighted in bold. ONSEN 2.8kb deletion treated with RNase A; second, we precipitated the DNA with a 1/10 volume of sodium acetate 3M pH 5,2 and 2,5 volumes of ethanol 100 %. The pellet was dissolved in 100 µl TE and incubated overnight at 4°C. Both a Nanodrop and a Qubit quantification were performed to control that the ratios 260/280 and 260/230 were as recommended for the MinIon library preparation and to be sure that the results of these two different quantifications were identical or close.

MinIon library preparation

The MinIon sequencing library was generated with the sequencing kit SQK-LSK108

(ONT, Oxford, UK) according to the manufacturer's instructions. All DNA samples were end-repaired and dA-tailed using the NEBNext Ultra II end-repair/dA-tailing module (Biolabs, New England, USA, cat. no. E7546S) as per the manufacturer's instructions except for the thermocycler program performed for 30 min at 20 °C, followed by 30 min at 65°C and 5 min at 4°C. The DNA was further purified with one volume of Agencourt AMPure XP beads (Beckman Coulter, High Wycombe, UK). After two washes with 70% ethanol, beads were air-dried and the DNA was eluted with 31 μl UltraPure™ DNase/RNase-Free Distilled Water (Thermo-Fisher scientific, USA). A Qubit quantification was performed with 1 µl. A ligation was then performed by adding 50 μl Blunt/TA ligase master MIX (Biolabs, New England, US, cat. no. M0367S) and 20 µl of Adapter Mix 1D (AMX1D, ONT, Oxford, UK) to the 30 µl A-tailed library and incubated at RT for 30 min. The DNA was further purified with 0.4 X volume of Agencourt AMPure XP beads (Beckman Coulter, High Wycombe, UK). After two washes with 140 µl of adapter bead binding (ABB, ONT, Oxford, UK), beads were pelleted and air-dried a few seconds and the DNA was eluted with 15 μl of elution buffer (ELB, ONT, Oxford, UK). A

Qubit quantification was performed with 1 µl.

Raw signal data processing

R9 ONT flow cells were used in this study. The number of available pores of each flow cell used was first recorded to evaluate the flow cell's quality with the MinKNOW™ software (version v0.51.1.62). The libraries were loaded on the flow cell following the manufacturer's instructions. Between 700 ng to 1650 ng of prepared library in 14 µl were added to 35 µl of RBF and 25,5 µl of LL buffers.This library mix was loaded on the flow cell via the SpotON sample. Raw signal FASTA5 files were base-called using threshold. To count alignment breakpoints, we mapped all assemblies to the corresponding reference genomes with minimap2 under the option '--pafno-hit -cxasm20 -r2k -z1000,500'. Structural variant was called by paftools.js to collect various metrics (Whole command line: bash sv_from_asm.sh). N-stretches in the corresponding reference genomes were extracted using the script "findN.py" to check for misassembled regions. Breakpoints of shared structural variants detected were compared with N-stretch coordinates using bedtools intersect [START_REF] Quinlan | BEDTools: a flexible suite of utilities for comparing genomic features[END_REF].

Data availability

Raw MinION sequencing data for A. thaliana Col-0 were deposited in the European Nucleotide Archive under the project name PRJEB34954, with samples ERS3901322.

For validation of mis-assembly in TAIR10, Illumina sequencing data of A. thaliana Col-0 (MPI: Weigel's lab) were extracted from Sequence Read Archive SRR013327. Reads from the S. pennellii acc. LA5240/LYC1722 were obtained from https://plabipd.de/portal/solanum-pennellii.

Tracking TE mobility and genome instability with long reads

My contribution to the discovery of genome instability in Arabidopsis epigenetic mutants

When I first got in touch with the long-read data of eccDNA-seq, I manually did a lots of dotplots to understand the fine structure of active TEs. I observed different structures of a certain TE, incomplete circles and chimeric circles. To investigate the origin of chimeric eccDNA including partial genes and partial TEs, we performed whole genome sequencing (WGS) using long reads.

However, there was no dedicated tools to detect TE insertion polymorphisms (TIPs) from long read sequencing that time (around 2020), I first developed a script based on the TRACKPOSON algorithm, namely CIGAR_SV (https://github.com/njaupan/CIGAR_SV). The CIGAR_SV uses CIGAR from read alignment to output insertion and deletion sequences. With the observation of partial TE in the WGS data, I further focused on the chimerism in the genome, especially "3hit" reads that is to say reads mapping to three different locations in the genome (hence the name « Chimera » for the manuscript).

While focusing on the TIPs for each active TE, I found that there was a 2Mb large sequence inverted in the genome of the hypomethylated ddm1 mutant. By performing many dotplots, I realized it was a true inversion. Then I collected all the public data associated with ddm1 to understand the origin of inversion. I downloaded 123 EpiRILs WGS data and calculated the occurrence of the inversion. We produced two new WGS datasets of ddm1 using ONT sequencing. In this material I further detected large duplications, opening a door to discuss the epigenetic control of genome stability.

In writing this manuscript, Hajk brought a lot of brainstorming to discuss the function of eccDNA, and Marie provided a lot of thoughtful discussion to help me understand the role of epigenetics. I hope to publish this work soon after we submit the thesis.

Introduction

Extrachromosomal circular DNA (eccDNA) has been described for decades in eukaryote cells including yeast, Drosophila, nematodes, plants and humans (Hotta and Bassel, 1965;Hirochika and Otsuki, 1995;Sinclair and Guarente, 1997;Cohen and Méchali, 2002;Kumar et al., 2017). Only recently this fraction of the cell genetic material has gained attention thanks to the development of specific eccDNA-seq sequencing approaches allowing its characterization (Møller et al., 2015;Lanciano et al., 2017).

EccDNA is found in all eukaryotes cells where it originates from spurious homologous recombination between tandem copies (for example ribosomal DNA or telomeric DNA)

or between micro homologies (Shibata et al., 2012) or from linearization of extrachromosomal linear DNA of active transposable elements [START_REF] Møller | Formation of Extrachromosomal Circular DNA from Long Terminal Repeats of Retrotransposons in Saccharomyces cerevisiae[END_REF]Lanciano et al., 2017) through HR or NHEJ. EccDNA is associated with senescence in yeast and with apoptosis in mammal cells (Wang et al., 2021;[START_REF] Arrey | A unifying model for extrachromosomal circular DNA load in eukaryotic cells[END_REF]. In cancer cells eccDNA is abundant and can originate from chromothripsis, a phenomenon describing a massive and catastrophic event of genome rearrangement. In these cells eccDNA is associated with gene amplification and contributes to tumor evolution. The adaptive role of eccDNA has also been demonstrated in plants where eccDNA encoded genes can contribute to herbicide resistance in weed species (Koo et al., 2018). Despite the growing literature on eccDNA, its impact on the genome is not well described. In cattle an early work suggested that eccDNA could be linked to structural variations [START_REF] Durkin | Serial translocation by means of circular intermediates underlies colour sidedness in cattle[END_REF]. Other indirect evidence links the presence of highly active TEs and structural variations (Hufford et al., 2021). However, the lack of ongoing TE mobility has prevented a comprehensive analysis of the impact of eccDNA on genomic structural variants.

We thought to address this question in Arabidopsis by analyzing the eccDNA repertoire of mutants with a high eccDNA load. In plants TEs are controlled at different steps in their life cycle by a combination of epigenetic regulations involving notably DNA methylation (for gene silencing) and post-transcriptional gene silencing (PTGS) [START_REF] Sigman | The First Rule of Plant Transposable Element Silencing: Location, Location, Location[END_REF][START_REF] Nicolau | The Evolutionary Volte-Face of Transposable Elements: From Harmful Jumping Genes to Major Drivers of Genetic Innovation[END_REF]Lloyd and Lister, 2022). DNA methylation is maintained directly by methyltransferases and by the RNA-directed DNA methylation pathway (RdDM). It is also indirectly maintained by the chromatin remodeler DDM1 (Decrease DNA Methylation 1) involved in the deposition of the heterochromatic histone variant H2A.W (Osakabe et al., 2021) at full length TEs. In order to increase the load of TE-driven eccDNA in Arabidopsis thaliana, we selected mutant plants with mutated DDM1, RDR6 (involved in PTGS) and NRPD1 or POL4

(involved in RdDM). Mutant plants affected in one or a combination of these pathways have a high level of TE transcription (Panda et al., 2016;He et al., 2021a). We used eccDNA-seq and long read sequencing of their genome to analyse the impact of eccDNA on genomic stability. We discovered that the triple mutant plants display a high

Results

Diverse TE families are present in the eccDNA repertoire of epigenetic mutants,

and trigger new genomic insertions

We used the mobilome-seq or eccDNA-seq approach (Lanciano et al., 2017) to sequence eccDNAs from WT, ddm1, ddm1 pol4, ddm1 rdr6 and ddm1 pol4 rdr6 mutant plants using Illumina short reads. Briefly linear genomic DNA was digested and the circular DNA was amplified using random primed rolling circle and sequenced. The enrichment of the mapped reads as well as the circle-specific head-to-tail reads corresponding to eccDNAs were analyzed using ecc_finder (Zhang et al., 2021). The two most abundant TE-eccDNAs corresponded to the long terminal repeat (LTR)

retrotransposon EVD [START_REF] Mirouze | Selective epigenetic control of retrotransposition in Arabidopsis[END_REF] and the DNA transposon of the Mutator family VANDAL21 (Tsukahara et al., 2009). These eccDNAs were detected in ddm1, inversion. The probability that epiRILs selected from eight generations of self-crosses generated after two backcrosses with wild-type Col-0 contained the Chr2-2M inversion is 55%, which is consistent with our observations (54,4%). Given the fact that the Chr2-2M inversion could be detected in both ddm1 alleles, it most likely occurred during or before the EMS mutagenesis of wild-type Col-0 that was used to generate the ddm1 mutants back in 1993. As the DDM1 gene is located on chromosome 5, it is nevertheless intriguing that the inversion was not segregated away during the multiple backcrosses of this mutant over nearly 30 years. Nevertheless, the Chr2-2M inversion was not found in ddm1 pol4, nor in the recent whole-genome sequencing of the ddm1-1 mutant from Zhu's group (He et al., 2021b), demonstrating that it can actually be segregated away.

ddm1
Interestingly the left Chr2-2M breakpoint at ATGP1 is completely hypomethylated in ddm1 plants (not shown). Given that it was not possible to obtain whole-genome sequencing data of ddm1 generated 30 years ago, the mechanism of the Chr2-2M We did not detect SNPs in the two tandem copies suggesting a recent event. To investigate the relationship between this new tandem repeats and DDM1-related DNA methylation, we examined the cytosine methylation pattern of the genes located at the breakpoints of the 55kb region. For this purpose, we used genes overlapping the junctions that could be unambiguously mapped. This showed that the second copy of the two tandem replicates is hypomethylated at the left breakpoint, while the first one is Large genomic rearrangements are frequently found in T-DNA mutants and mutagenized plants (Jupe et al., 2019;[START_REF] Pucker | Large scale genomic rearrangements in selected Arabidopsis thaliana T-DNA lines are caused by T-DNA insertion mutagenesis[END_REF]. The 2Mb inversion that we have uncovered in ddm1 mutant plants probably occurred nearly 30 years ago during the original EMS screen, as two alleles from this screen (ddm1-1 and ddm1-2) display the inversion. This inversion segregated in a Mendelian fashion in the ddm1-epiRIL population, and was recently segregated away in ddm1 (He et al., 2021b). The reason why this inversion was never segregated away in our ddm1 plants remains obscure. It could have been present in the original line with which the ddm1 alleles were backcrossed (Vongs et al., 1993). Nevertheless, this observation illustrates the power of long reads in detecting SVs in long-studied mutants and advocate for a closer examination of the genomes or commonly used genetic mutants.

Three examples of independent large duplications in ddm1

We have identified two independent large duplications (55 and 56 kb) in two ddm1-2 individuals that occurred in the lab and was thus not due to EMS mutagenesis. A large duplication has already been observed in the ddm1 mutant background at the bal locus (Yi andRichards, 2008, 2009), suggesting that duplications are frequent in this background. The bal duplication, also 55 kb in length, is associated with a dwarf plant phenotype due to overexpression of a duplicated gene at the RPP5 locus, a disease resistance locus containing tandem repeats of R genes clustered with TEs [START_REF] Yi | Gene Duplication and Hypermutation of the Pathogen Resistance Gene SNC1 in the Arabidopsis bal Variant[END_REF]. Large tandem duplications have also been reported in lines derived from a fas2 mutant with a decrease number of rDNA copies [START_REF] Picart-Picolo | Large tandem duplications affect gene expression, 3D organization, and plantpathogen response[END_REF].

Loss of DDM1 or FAS2 correlates with higher rates of meiotic (Melamed-Bessudo and Levy, 2012) or homologous recombination [START_REF] Endo | Increased frequency of homologous recombination and T-DNA integration in Arabidopsis CAF-1 mutants[END_REF]Muchova et al., 2015), respectively. Our study suggests that DDM1 is involved in genome stability. The detection of duplications was probably facilitated by the use of ONT sequencing together with the use of single plants for sequencing, increasing our SV detection sensitivity.

101

DDM1, a DHL chromatin remodeler involved in DNA repair?

DDM1 has recently been defined as belonging to DHL chromatin remodelers, an acronym for a family comprising DDM1 (in plants), HELLS (Human helicase lymphoid specific, in humans) and LSH (lymphoid specific helicase, in mice) [START_REF] Berger | Seminars in cell and development biology on histone variants remodelers of H2A variants associated with heterochromatin[END_REF].

Both DDM1 and HELLS are involved in the deposition of heterochromatic histone variants, namely H2A.W and macroH2A1.2, respectively [START_REF] Berger | Seminars in cell and development biology on histone variants remodelers of H2A variants associated with heterochromatin[END_REF]Osakabe et al., 2021). Recent studies suggest an increasing role of histone variants in DNA repair [START_REF] Davarinejad | The histone H3.1 variant regulates TONSOKU-mediated DNA repair during replication[END_REF]. HELLS plays a role in homologous recombination repair of heterochromatic breaks [START_REF] Ni | LSH mediates gene repression through macroH2A deposition[END_REF][START_REF] Xu | The epigenetic regulator LSH maintains fork protection and genomic stability via MacroH2A deposition and RAD51 filament formation[END_REF][START_REF] Caron | DNA Double-Strand Break Repair: All Roads Lead to HeterochROMAtin Marks[END_REF]. HELLS and LSH are expressed in lymphoid where they participate in V(D)J recombination but are also expressed in testis. During meiosis, HELLS interacts with PRDM9 to open chromatin and direct recombination DSBs [START_REF] Spruce | HELLS and PRDM9 form a pioneer complex to open chromatin at meiotic recombination hot spots[END_REF][START_REF] Imai | PRDM9 activity depends on HELLS and promotes local 5hydroxymethylcytosine enrichment[END_REF]. LSH promotes DNA repair [START_REF] Burrage | The SNF2 family ATPase LSH promotes phosphorylation of H2AX and efficient repair of DNA double-strand breaks in mammalian cells[END_REF] in mice. Indirectly, DHL remodelers have an impact on DNA methylation, and their loss is associated with TE reactivation. We propose that the two phenotypes observed in this study highlight these dual roles of DDM1. In one hand, DDM1 is indirectly involved in DNA methylation: its loss releases silencing at TEs, leading to a high eccDNA load and new TE insertions. When combined with rdr6 and pol4 this mutation leads to truncated and complex SVs. On the other hand, DDM1 is involved in H2A.W deposition and ensures HR repair of DSBs: its loss leads to tandem duplications. More examples of epigenetically induced SVs will be instrumental to address the precise role of DDM1 in genome stability.

Methods

Detection of eccDNAs from Illumina and ONT eccDNA-seq

The eccDNA producing loci from each Arabidopsis epigenetic mutant were detected using ecc_finder (Zhang et al., 2021) with default parameters of short-read-mapping and long-read-mapping mode (for Illumina and data ONT data, respectively). eccDNAs originating from organelle DNA fragments mapping to their nucleic copy (such as NUPTs for nucleoplasmic DNA and NUMTs for nuclear mitochondrial DNA (Saccone et al., 2000;Yoshida et al., 2014)), from ribosomal DNA repeats (rDNA) and from centromeric repeats were removed. The remaining eccDNAs were grouped into TE

Remaining questions on eccDNA inheritance and the emergence of new genes

The inheritance of eccDNA is still a mystery. Due to the absence of centromeres, eccDNA segregation may be heterogeneous, resulting in progeny cells containing different eccDNA copy numbers (Verhaak et al., 2019). Cells with a high copy number of eccDNAs may have a selective advantage for adaptation to certain environments, as

shown for the glyphosate resistance in Amaranthus palmeri (Koo et al., 2018b).

In order to better understand eccDNA inheritance and its role in chimeric gene formation, it would be interesting to find a model system in which eccDNA might be abundant and passed to the next generation. In C. elegans spermatocytes, a brief temperature shift significantly increase the Tc1/mariner transposition activity [START_REF] Kurhanewicz | Elevated Temperatures Cause Transposon-Associated DNA Damage in C. elegans Spermatocytes[END_REF], increasing DNA double-strand breaks in spermatocytes by 25-fold. Despite this, heat shocked males produced offspring with surprisingly low non-viability, with only a 3-fold increase, demonstrating the biological stability of spermatogenesis [START_REF] Bhalla | Meiosis: Is Spermatogenesis Stress an Opportunity for Evolutionary Innovation[END_REF][START_REF] Kurhanewicz | Elevated Temperatures Cause Transposon-Associated DNA Damage in C. elegans Spermatocytes[END_REF]. Transposition of transposons during spermatogenesis also validates a hypothesis about the origin of new genes--out of testis [START_REF] Nyberg | Out of the testis: biological impacts of new genes[END_REF]. Because testis is subject to extremely strong selective pressures, such as competition between spermatocytes and gender conflict, testicular tissue is evolutionarily extremely voracious and able to accommodate a variety of new genes.

Many studies have shown that genes related to sperm formation are often subject to strong natural selection pressures [START_REF] Kaessmann | Origins, evolution, and phenotypic impact of new genes[END_REF][START_REF] Wu | De Novo Origin of Human Protein-Coding Genes[END_REF][START_REF] Zhao | Origin and Spread of de Novo Genes in Drosophila melanogaster Populations[END_REF][START_REF] Oss | De novo gene birth[END_REF]. In mammals and flies, newly formed genes tend to be specifically expressed only in testis [START_REF] Wu | De Novo Origin of Human Protein-Coding Genes[END_REF][START_REF] Zhao | Origin and Spread of de Novo Genes in Drosophila melanogaster Populations[END_REF]. Moreover, there is substantial DNA demethylation during formation, providing excellent conditions for transposon activation. Although the presence of eccDNA was not yet described in this model, it would be a nice experimental system to investigate the impact of transposition on SVs and possibly on chimeric gene formation, transmitted the next generation.

Young gene emergence was also studied in Arabidopsis and rice genomes and this revealed that a number of recently evolved young genes are involved in defense and reproductive processes. Transcriptomic analysis further showed that plant male reproductive cells are associated with high expression of young genes [START_REF] Cui | Young Genes out of the Male: An Insight from Evolutionary Age Analysis of the Pollen Transcriptome[END_REF].

Therefore, it is exciting to consider future experiments to address eccDNA inheritance patterns during sexual reproduction. In the case of hypomethylated ddm1 mutants, for example, it would be interesting to detect fluorescently labeled EVADE and get a livecell image during cell division and reproductive development. Of note, DDM1 plays an important role in pollen development. It is expressed in the sperm cells but lost in the vegetative nucleus [START_REF] Slotkin | Epigenetic Reprogramming and Small RNA Silencing of Transposable Elements in Pollen[END_REF][START_REF] Calarco | Reprogramming of DNA methylation in pollen guides epigenetic inheritance via small RNA[END_REF].

Towards eccDNA detection directly from genomic data

Plant population genomes assembled from long read sequences are emerging, for instance in Arabidopsis thaliana [START_REF] Jiao | Chromosome-level assemblies of multiple Arabidopsis genomes reveal hotspots of rearrangements with altered evolutionary dynamics[END_REF], tomato [START_REF] Gao | The tomato pan-genome uncovers new genes and a rare allele regulating fruit flavor[END_REF]Alonge et al., 2020) and rice (Qin et al., 2021). In particular, a large number of SVs associated with phenotypes in these species, including duplication, TE insertions, and translocations have been resolved. DNA double-strand breaks, chromosomal rearrangements, and other possible chromosomal events can lead to DNA fragment cyclization to form eccDNA [START_REF] Liao | Classification of extrachromosomal circular DNA with a focus on the role of extrachromosomal DNA (ecDNA) in tumor heterogeneity and progression[END_REF]. Nevertheless, it is still questionable whether hotspots of SVs will be the hotspots that generate eccDNAs.

To address this question, it would be important to characterize eccDNA producing loci directly from genomic datasets (not only from eccDNA-seq). However, most software currently available for eccDNA detection are based on the input from eccDNAseq data, such as ecc_finder [START_REF] Zhang | ecc_finder: a robust and accurate tool for detecting extrachromosomal circular DNA from sequencing data[END_REF]. Is it possible to use the whole genome sequencing (WGS) data in hand to predict the loci that produce eccDNA? The answer is clearly yes.

If to consider the short read mapping, read pairs can be grouped by chromosome and orientation. Circular specific reads (discordant read pairs with outward-facing labels and split read pairs with inward-facing labels) used for identification in eccDNA-seq data will remain the target of WGS data. Could we speed up the computational performance (compared to Python scripts), e.g. by using SAMBLASTER [START_REF] Faust | SAMBLASTER: fast duplicate marking and structural variant read extraction[END_REF]? So far a few tools such as SAMBLASTER can detect discordant and split read in linear DNA. Similarly, loci displaying more than two sub-reads alignment in the long-read mapping will be candidate eccDNA producing loci. However, more tests to improve the short read with long read length data does not work well; complex sequences of genome need longer read length to be resolved [START_REF] Mascher | Longread sequence assembly: a technical evaluation in barley[END_REF].

To date, plant genome studies have shown that the analysis of the very large genomes and polyploid plant genomes requires a smart material selection. The combination of genome + transcriptome + resequencing is still a necessary routine. Finally, HiFi + ONT ultra long reads provides technical support for the completion of plant genomes. With even complex genome assemblies in our hands, the most exciting part of genomics resides now in the characterization of "core" and "dispensable" genome for a given species.

Emerging tools to characterize SVs in pan-genomes

Using a pan-genome approach rather than a single reference genome allows for a more comprehensive characterization of genetic variation and can improve genomic analysis used widely. However, there are very few pan-genomic related tools and they are still in the developmental stage. Giraffe is a new tool that efficiently maps genomic sequences to a "pangenome" representing a wide range of different human genomic sequences. From 5,202 different individuals, Giraffe identified 167,000 SVs using short read mapping and further identified haplotypes based on the sequence graph, demonstrating its broad applicability and functionality [START_REF] Sirén | Pangenomics enables genotyping of known structural variants in 5202 diverse genomes[END_REF].

Benchmark of all long-read SV callers reveals the strengths and weaknesses of each SV detection algorithm and provided the basis for integrating multiple algorithms in a new SV detection pipeline, namely combiSV [START_REF] Dierckxsens | A benchmark of structural variation detection by long reads through a realistic simulated model[END_REF]. The Perl script combines VCF output from Sniffles, pbsv, and so on into a superior call set. CombiSV achieves higher recall, precision and accuracy than SURVIVOR, an existing algorithm for generating consensus VCFs [START_REF] Dierckxsens | A benchmark of structural variation detection by long reads through a realistic simulated model[END_REF].

A just-published tool, TEsorter, can accurately classify LTR retrotransposons in the maize and rice genomes and can be drawn upon for integration into a pan-genomic SVs tool [START_REF] Zhang | TEsorter: an accurate and fast method to classify LTR-retrotransposons in plant genomes[END_REF]. Based on the classified conserved protein structural domains (database source REXdb or GyDB), TEsorter first searches for structural domains using Hidden Markov Models and then filters hits for classification. The classification results

Future trends to uncover the relationship between TEs, eccDNAs and SVs

On the role of VLP in fast TE and TE-gene chimerism evolution

Given the capture capacity of TEs, well described for Pack-MULEs in rice and Pack-TIRs in 100 species of animals, TEs have been described to promote adaptive evolution by forming new genes [START_REF] Talbert | Characterization of a highly conserved sequence related to mutator transposable elements in maize[END_REF]Jiang et al. 2004[START_REF] Jiang | Pack-Mutator-like transposable elements (Pack-MULEs) induce directional modification of genes through biased insertion and DNA acquisition[END_REF]Ta n et al. 2021). Furthermore, fusions between DNA transposons and protein-coding genes in all tetrapod genomes demonstrate that TEs provide a recurrent supply for shaping novel protein structures [START_REF] Cosby | Recurrent evolution of vertebrate transcription factors by transposase capture[END_REF].

However, little is still known about fusions between TE, notably retrotransposons, and gene in terms of biogenesis, stability and transgenerational impact.

Considering that during retrotransposon life-cycle, transcripts are encapsidated in the VLP, how do TE and gene transcripts fuse together? Do they peel off from the genome and form chimeric ecDNA? Or are they wrapped together in the VLP and then transferred to the nucleus as chimeric eccDNA? To answer these questions, recent VLP-related studies studies on domesticated gag proteins open new perspectives.

Arc, for instance, is a gag domesticated protein present in human neuronal cells and derived from Gypsy retrotransposons. Arc proteins form a VLP in which their own mRNA is encapsulated and transferred from one neuronal cell to another, participating in memory consolidation [START_REF] Pastuzyn | The Neuronal Gene Arc Encodes a Repurposed Retrotransposon Gag Protein that Mediates Intercellular RNA Transfer[END_REF]. Similarly, other animals have independently evolved their own Arc. The Arc gene in Drosophila also transports RNA between neurons in a VLP [START_REF] Ashley | Retrovirus-like Gag Protein Arc1 Binds RNA and Traffics across Synaptic Boutons[END_REF]. Similarly, the Gypsy retrotransposons-derived protein PEG10 is also capable of transferring or binding RNA and has also been reported to be involved in the formation of the mammalian placenta [START_REF] Ono | Deletion of Peg10, an imprinted gene acquired from a retrotransposon, causes early embryonic lethality[END_REF][START_REF] Korb | Arc in synaptic plasticity: from gene to behavior[END_REF]. Since genes derived from gag homolog can form VLP and then serve as RNA delivery, can they deliver also other gene transcripts of interest? The paper by [START_REF] Segel | Mammalian retrovirus-like protein PEG10 packages its own mRNA and can be pseudotyped for mRNA delivery[END_REF] is noteworthy as it is the first example of a specific biotechnological RNA delivery within a cell. The authors show that target mRNAs can be reprogrammed with the untranslated region flanking Peg10 allowing their encapsidation by PEG10 for RNA delivery. Excitingly, 500 bp of the 3' UTR of the mouse PEG10

were sufficient to efficiently transfer exogenous mRNA into target reporter cells [START_REF] Segel | Mammalian retrovirus-like protein PEG10 packages its own mRNA and can be pseudotyped for mRNA delivery[END_REF].

Figure

  Figure Résumé. Méthode de l'eccDNA-seq ou mobilome-seq. Les eccDNA provenant de l'eccDNA-seq à lecture courte (orange) et de l'eccDNA-seq à lecture longue (bleu) sont indiqués.

  Dans le dernier projet, nous avons utilisé le génome assemblé par SASAR et l'ADNecc détecté par ecc_finder pour caractériser les interactions entre les ADNecc et le génome. Dans les mutants épigénétiques hypométhylés d'Arabidopsis thaliana, nous avons mis en évidence le rôle de l'épigénome dans la protection de la stabilité du génome non seulement contre la mobilité des TE mais aussi envers les réarrangements génomiques et le chimérisme des gènes. Globalement, nos découvertes sur l'ADNecc, la stabilité du génome et leurs interactions réciproques, ainsi que le développement d'outils, offrent de nouvelles perspectives pour comprendre le rôle des TE dans l'évolution adaptative des plantes à un changement rapide de l'environnement. Mots clés: ADN circulaire extrachromosomique, assemblage du génome, élément transposable, séquençage en lectures longues. A PhD thesis is a long journey that no one travels alone. I would like to thank all the people who accompanied me throughout these 4 long years. First of all, I would like to thank Marie Mirouze and Alain Ghesquière for welcoming me in their institute. I thank the members of the jury, my rapportrice Anne Roulin and rapporteur Todd Blevins as well as my examiners, Nathalie Picault, Romain Guyot and Magnus Nordborg who accepted to evaluate my work. I would also like to thank Romain Guyot, Moaine El Baidouri, Olivier Panaud and Hajk-Georg Drost for having accepted to be part of my thesis committee.

  You have always praised me without hesitation and this has kept me motivated. From Montpellier to Versailles, from Tubingen to Leipzig, from Amsterdam to Udine… you offered me so many opportunities, freedom in my research. When I had difficulty expressing in English, you never lost patience and helped me improve my presentation skills. Thank you for the tremendous support you have given me especially under difficulties of the pandemic, no matter what I write, words won't be enough to express the immense pleasure that it was to do my PhD with you. I hope I would not have made you too desperate, especially with my procrastination in writing. I hope you keep having great PhD students, because you deserve it. If one day I become a researcher, I hope I can be like you. I am fortunate to be part of the MANGO team of bioinformaticians and technicians. I would like to thank Olivier Panaud who was always available for scientific or not conversations, listened to me, taught me and advised me despite his busy. I would also like to thank Christel Llauro for her great help in the wet lab, without her I would have no data to analyze. Thank you for all your efforts to manage the sequencing perfectly. I would like to thank Moaine El Baidouri, not only for having shared so many times your experience and advice on research, but especially for your help in helping me to get acquainted and integrate into the French environment. I would like to thank Eric Lasserre for your huge help in solving different difficulties in data analysis, without which I would have been lost. Thanks to Joris Bertrand for constantly providing so many fascinating orchid images that open the door to outdoor exploration. It is my pleasure to work with all the PhD students of the team: Marie Christine Carpentier, thank you for having took us different academic and cultural activities, and for having made us laugh. Emilie Aubin, thanks for those days spent together talking about everything and for the countless times we experienced laughter and sadness together. Assane Mbodj and Abirami Soundiramourtty, even though I haven't known you for a long time. Thank you for your good cheer and for your kindness in any situation.

I

  would like to thank Detlef Weigel for hosting me in his open, friendly and wellorganized research group. Thank you for deepening my knowledge and helping me tremendously in the direction of my research. To Haik Georgi Drost, thank you for every brainstorming conversation during the lunch and for availability during my numerous questions. To Benjamin Buchfink, thank you for those days spent together talking about every little thing that later mattered and huge help in bioinformatics. To Angel Wibowo, thank you for caring and looking after me like a big brother. To Adrian Contreras, thank you for your perfect hosting and for the compliments on my work. I would also like to thank Peter Stadler for welcoming me on secondment to his group. Thank you, Adam Nunn, for great help in developing tools and for having a great time in Germany. I would also like to thank Etienne Bucher for continuous discussion and cooperation. Thank you all the remaining members of Epidiverse: Dr. Koen Verhoeven, programme manager Margreet Bruins and their students: Morgane van Antro and Cristián Peña from NIOO-KNAW, Netherland; Dr. Noe Fernandez Pozo, Dr. Katrin Heer, Dr. Lars Opgenoorth, Dr. Stefan Rensing and their students: Nilay Can and Bárbara Díez Rodríguez from Philipps University Marburg, Germany; Dr. Oliver Bossdorf, Dr. Niek Scheepens and their student Dario Galanti from University Tübingen, Germany; Dr. Vit Latzel and his student Iris Sammarco from Botanicky Ustav AVCR, Czechia; Dr. Etienne Bucher's student Maria Estefanía Lopéz from University of Geneva, Switzerland; Dr. Claude Becker and his student Daniela Ramos Cruz from LMU Munich, Germany; Dr. David Langenberger from ecSeq , Germany; Dr. Conchita Alonso and her student Anupoma Niloya Troyee from CSIC, Spain; Dr. Emanuele DePaoli and his student Bhumika Dubay and Paloma Perez Bello Gil; Dr. Ivo Grosse and his student Samar Fatma from Martin Luther University, Germany. What a great journey to have 15 PhD students and 18 principal Investigators to work on a project, words can't express my thanks and love enough! A big thank you also to all my friends who supported me during these 4 years of thesis or since much longer, Abraham, Sandrine, Benjamin, Dadi, Yuanyuan, Jiayue, Jiaqi and I surely forget some... Finally, I would like to express my gratitude to my parents. I'm sorry you couldn't come to my defense because long flights are being cancelled by the terrible war, but I thank you for your none-stop support so that I could achieve my dreams without worry. To my fiancé Shiva, thank you for your efforts to maintain a long-distance relationship, without your support and optimism I would not be as happy as I am now. Thank you, Daksh, my youngest and sweetest nephew, your constant laughter is the best thing in the world. Carl Sagan said: "Extinction is the rule. Survival is the exception". When our life, when the world, feels like a never-ending emergency. Sometimes, just making it through the day can be a struggle. But we collect scars, physical and mental reminders of what we've been through. The journey itself is all that life has to offer. I sincerely thank everyone I have met and I wish you all happiness every day. Stay curious and optimistic about the days ahead. Thank you, thank you, and thank you !!! Table of Contents List of Figures ...................................................................................................... 1. Introduction ..................................................................................................... 1.1. Tracking transposable elements mobility in plants .......................................... 1.1.1 Characterization of Transposable Elements (TEs) ........................................... 1.1.2 TE transposition and gene capture ................................................................... 1.1.3 Mechanisms of TE silencing ............................................................................. 1.1.4 Genome instability mediated by TEs ................................................................ 1.1.5 TEs in the form of extrachromosomal circular DNA (eccDNA) ......................... 1.2 Obtaining a high-quality genome assembly prior to TE annotation ................. 1.2.1 What is a genome assembly ............................................................................. 1.2.2 The revolution of long read sequencing technologies ...................................... 1.2.3 Assembling centromeres: first « gap free » plant genomes .............................. 1.2.4 The challenge of assembling very large plant genomes .................................. 1.2.5 Resolving haplotypes in plant genomes ........................................................... 1.2.6 Pan-genomes: One genome is not enough ...................................................... 1.3 Structural variants in the plant genome .............................................................. 1.3.1 Why to detect structural variants (SVs)? .......................................................... 1.3.2 Algorithms of SV detection ............................................................................... 1.3.3 Visual validation for SV prediction .................................................................... 1.4 Objectives of the thesis work and main achievements ..................................... 2. Methods and Results ...................................................................................... 2.1 Ecc_finder: Developing a new tool for eccDNA detection ................................ 2.1.1 My contribution to ecc_finder ............................................................................ 2.1.2 ecc_finder manuscript (Frontiers in Plant Science, 2021) ................................ 2.1.3 Update on ecc_finder ........................................................................................

4.

  Figure I.1. Classification and structural features of transposable elements Figure I.2. Detailed structure of the Gypsy and Copia LTR retrotransposons.

Figure I. 3 .

 3 Figure I.3. TE transposition mechanisms and formation of eccDNA.

Figure I. 4 .

 4 Figure I.4. Proposed models through which TE capture host sequences.

Figure I. 5 .

 5 Figure I.5. Main epigenetic actors involved in DNA methylation maintenance and de novo mechanisms in Arabidopsis thaliana. 1.2 Obtaining a high-quality genome assembly prior to TE annotation ................. 36 Figure I.6. Sequencing technologies used for plant genome assemblies until September 2021.

Figure

  Figure I.7. An overview of genomic population-scale studies in plant using longread sequencing. 1.3 Structural variants in the plant genome .............................................................. 48 Figure I.8. Detecting structural variants using de novo assembly and read mapping modes.

2. 2

 2 Figure II.2. Schematic pipeline of SASAR (Super ASsembly from Assembly Reconciliation).

Figure

  Figure II.3. SASAR performance in assembling the centromeres in A. thaliana Col-0.

Figure

  Figure II.4. SASAR performance in a 1kb insertion in the non-centromeric region of A. thaliana Col-0.

Figure

  Figure II.5. SASAR improved the assembly of ONSEN/ATCOPIA78 in A. thaliana Col-0. 2.3 Tracking TE mobility and genome instability with long reads .......................... 83 Figure II.6. The eccDNA repertoire in A. thaliana epigenetic mutants contains active full length and truncated TEs.

Figure

  Figure II.7. TE insertion polymorphisms in A. thaliana epigenetic mutants revealed by ONT genome sequencing.

Figure II. 8 .

 8 Figure II.8. Chimeric eccDNA containing a truncated EVD-gene fusion corresponding to a chimeric genomic integration in A. thaliana ddm1 rdr6 pol4 mutant.

Figure

  Figure II.9. ATCOPIA21 mobility in the A. thaliana ddm1 rdr6 pol4 triple mutant is associated with RPP5 locus duplication.

Figure

  Figure II.10. Detection of a 55kb duplication on chromosome 1 in the A. thaliana ddm1-2 mutant genome.

Figure

  Figure II.11. Overall genomic instability detected in this study in A. thaliana epigenetic mutants. Supplementary Figure 1. A large inversion in the A. thaliana ddm1-2 mutant genome.

  and number. According to the replication mode, TEs can be classified into class I retrotransposons and class II DNA transposons (Figure I.1)[START_REF] Wicker | A unified classification system for eukaryotic transposable elements[END_REF].

Figure I. 1 .

 1 Figure I.1. Classification and structural features of transposable elements. Two classes of TEs, class I retrotransposons and class II DNA transposons, have autonomous and non-autonomous elements, respectively. Gag is highlighted in green, terminal repeats are colored in yellow (edited from[START_REF] Feschotte | Plant transposable elements: where genetics meets genomics[END_REF][START_REF] Wicker | A unified classification system for eukaryotic transposable elements[END_REF]

Figure I. 2 .

 2 Figure I.2. Detailed structure of the Gypsy and Copia LTR retrotransposons. These two TE families differ in the organization of the POL polyprotein domains. The PBS (primer binding site) and PPT (polypurine tract) sites are involved in reverse transcription of the element. (Modified from[START_REF] Havecker | The diversity of LTR retrotransposons[END_REF][START_REF] Sabot | Parasitism and the retrotransposon life cycle in plants: a hitchhiker's guide to the genome[END_REF].

Figure I. 3 .

 3 Figure I.3. TE transposition mechanisms and formation of eccDNA. Active retrotransposons initiate transcription and are translated into proteins and form the VLP. After undergoing reverse transposition, double-stranded extrachromosomal linear DNA enters the nucleus and inserts into new genomic loci thanks to the integrase or form eccDNA through homologous recombination (HR)or non-homologous end-joining (NHEJ). Active DNA transposons can also lead to the formation of eccDNA, for instance here an helitron transposing through a rolling circle mechanism. Edited fromLanciano et al., 2017;[START_REF] Wells | A field guide to eukaryotic transposable elements[END_REF]

  transcriptase, RNAseH, and integrase(Figure I.3). These, along with two transcripts forming a kissing loop structure, are specifically packaged into GAG-derived virus-like particles (VLPs). Subsequent reverse transcription involves two transfers of the DNA strand, resulting in the synthesis of complete copies of the retrotransposon with two identical LTRs in the form of extrachromosomal linear DNA (eclDNA). eclDNA in double-stranded form enters the nucleus by an unknown mechanism, and inserts into new genomic loci mediated by the integrase. Nevertheless, eclDNA can also be recognized by DNA repair mechanisms before its reinsertion into the genome and be captured by the Homologous Recombination (HR) or Non-Homologous End-Joining (NHEJ) pathway inducing the formation of extrachromosomal circular DNA (eccDNA).

  Proposed models for TE capturing additional coding sequences have been proposed (Figure I.4): (A) the template switch model through which LTR TEs capture host sequences. In this model, a transcript originating from a host gene is encapsidated into the VLP. The template switching between a LTR retrotransposon transcript and this gene transcript occurs in the VLP, and thus generates a chimeric eclDNA. After integrating into host genome, the chimeric sequences act like pseudo-LTR retrotransposon and can be transcribed to enter a new cycle of retroposition (Tan et al., 2016). (B) the gap-filling model for the capture sequence of TEs by TIR DNA transposons. Double-strand breaks (DSBs) occur within TEs due to fragile sites (i) or excision of active TEs (ii). The 5' end is excised by exonucleases and gap repaired normally using the TE as template. The repaired strand may switch to a non-TE sequence. (C) The FoSTeST model (Fork Stalling, Template Switching, Transposition) through which TIR TEs capture sequences. 1. replication fork stalls at the transposon and a DSB occurs; 2. transposon and parent sequence are spatially close, leading to template jumping during repair to produce a chimeric fragment; 3. transposase recognizes the chimeric fragment and cleaves the insertion to another position 4 (Figure I.4)

Figure I. 4 .

 4 Figure I.4. Proposed models through which TE capture host sequences. (A) The template switch model through which LTR TEs capture sequences in the VLP, and then integrate into host genome (Tan et al., 2016). (B) Gap-filling model for the capture sequence of TIR TEs. Double-strand breaks (DSBs) occur within TEs due to fragile sites (i) or excision of active TEs (ii) and then gap repair. (C) FoSTeST model through which TIR TEs capture sequences (Tan et al., 2021).

Figure I. 5 .

 5 Figure I.5. Main epigenetic actors involved in DNA methylation maintenance and de novo mechanisms in Arabidopsis thaliana. DNA methyltransferases (green boxes) and chromatin remodeler (green bubble) are highlighted. See text for details. Adapted from Castel and Martienssen, 2013.

  Both sequencing technologies generate single molecule reads longer than 10kb, exceeding the simplest repeat lengths in many genomes, enabling highly contiguous genome assembly. As a result, an increasing number of high-quality genomes of different species are being sequenced and assembled using long reads(Figure I.6).

Figure I. 6 .

 6 Figure I.6. Sequencing technologies used for plant genome assemblies until September 2021. The proportion of plant genome sequenced with long reads is colored in blue.

From

  this knowledge, Zhang et al. (2021) established a genomics-assisted breeding design for hybrid potato that includes four steps: (1) selecting two heterozygous lines of phenotypic interest and breaking self-incompatibility; (2) analyzing the genetic composition of segregating progeny; (3) producing inbred lines with favorable haplotypes, counter-selecting haplotypes with deleterious mutations; (4) crossing the obtained homozygous lines to obtain F1 plants with hybrid vigor

  Since a single reference genome cannot represent the entire sequence diversity within a species, population-scale long-read sequencing has gradually begun to flourish in evolutionary and functional genomics research and crop breeding research (Figure I.7).

Figure I. 7 .

 7 Figure I.7. An overview of genomic population-scale studies in plant using long-read sequencing. Construction strategies based on assembly comparison and/or read mapping are color-coded as indicated. See text for details.

Figure I. 8 .

 8 Figure I.8. Detecting structural variants using de novo assembly and read mapping modes. In de novo assembly mode, segment positions in the dot plot of query and reference sequence comparison indicate the type and size of the SV. In read mapping mode, paired reads (orchid) and split reads (orange) from short read alignment patterns are typically used to detect different types of SV, as indicated. For long reads (green), alignment patterns across junctions are typically used to detect different types of SVs. In addition, read depths showing coverage aberrations can be used to improve the accuracy of deletion and duplication detection (modified from[START_REF] Mahmoud | Structural variant calling: the long and the short of it[END_REF][START_REF] Mérot | A Roadmap for Understanding the Evolutionary Significance of Structural Genomic Variation[END_REF].

  Therefore, I set out to develop a new detection algorithm specifically for circular loci. Lacking relevant experience in software development, I deepened my understanding by interning in a lab that specialized in developing short-read aligners in 2019 (lab of Peter Stadler, who developed segemehl). Through careful screening of the read alignment and positive controls validated by the wet lab experiments, I finally understood that there were specific types of split and discordant reads. I gradually wrote the entire pipeline in Python after being back from my internship.

  stem and root tissues of Arabidopsis in terms of gene content, I reanalyzed this dataset, removing eccDNA originating from repeats and organelles listed above. This showed a dramatic reduction in the total number of root-specific eccDNAs (Figure II.1B). I could detect specific eccDNAs corresponding to flowers/leaves/stems/roots, as follows 94/104/96/38. Of note, there was no common eccDNA between roots and other different tissues (leaves, flowers and stems). To further validate this data, I analyzed eccDNAs from three replicates in the different tissues (Figure II.1C), and this showed a lack of consistency between samples. Additionally, the validation of bona fide eccDNAs is still questionable in this study, therefore I would recommend to use ecc_finder to re-do the step of detection.

Figure II. 1 .

 1 Figure II.1. Reanalysis of the characteristics of eccDNAs from leaf, flower, stem and root tissues of Arabidopsis thaliana in Wang et al. (2021). (A) Reclassification of 743 eccDNAs inWang et al. (2021). All eccDNA loci in Supplemental Table1were intersected with annotations including NUPTs and NUMTs, rDNA, and centromeric repeats using bedtools and then re-annotated. (B) Comparison of differences between eccDNA detected from leaf, flower, stem, and root tissues of Arabidopsis after removal of positive controls. (C) Intersection of eccDNAs between eccDNA detected from leaf, flower, stem, and root tissues of Arabidopsis in three replicates.

  2 versions of SASAR, one for release in 2019 and one for the current version.

Figure

  Figure II.3. SASAR performance in assembling the centromeres in A. thaliana Col-0. (A) A partial assembly graph consisting of chains of bubbles with the reference as the backbone. The bubble represents a 12848bp SV detected in the SASAR-assembly. (B) Dot plot of the 12848bp sequence against itself shows that the SV is a copy number variant of the 178bp centromere repeat. (C) Dot plot of SASAR-assembly versus reference genome TAIR10. SASAR assembled more centromeric regions of A. thaliana represented by "vertical lines"; (D) Raw reads coverage. Peaks of read coverage across the TAIR10 (upper panel) and the SASAR assembly (lower panel). Lower peaks indicate that more repeats are assembled. Note that SASAR assembly is 10 Mbp longer.

  level of TE-derived eccDNAs originating from different TE families of LTR retrotransposons (such as EVD/ATCOPIA93, and ATCOPIA21) and DNA transposons (VANDAL21). Thanks to long read eccDNA-seq we could uncover the structure of these eccDNAs and show that while a fraction of the eccDNA is full-length as expected, the majority consist of truncated circles. Analyzing the genomic content of these mutant plants, we uncovered examples of truncated insertions of these TEs, suggesting that truncated copies are capable of integration. Most notably, we also identified chimeric gene-TE eccDNAs and show evidence of genomic integrations of such gene-TE elements. Finally, we serendipitously discovered large structural variations that promoted us to analyze the SVs in the single ddm1 mutant. One large 2 Mbp inversion was detected in ddm1 and could originate from its original EMS screen. In contrast, two 55 and 56 kb duplications were identified in single ddm1 plants and suggest a high level of genome instability in this genetic background. Our work highlights the hidden consequence of lack of DDM1 on genomic stability and suggest that epigenetic control of genomic stability goes beyond TEs.

  pol 4, ddm1 rdr6 and ddm1 pol4 rdr6 libraries (Figure II.6A). Noticeably, EVD-eccDNA and VANDAL21-eccDNA reads accounted for 130,000 per million reads and 80,000 per million reads, respectively, in the ddm1 pol4 rdr6 triple mutant library. On top of these highly represented eccDNAs, we detected eccDNAs from the LTR retrotransposons ATCOPIA51, ATCOPIA52 and DNA transposon VANDAL3 families (Figure II.6A), where the mobility of LTR retrotransposons is consistent with active reverse transcription[START_REF] Panda | Long-Read cDNA Sequencing Enables a "Gene-Like" Transcript Annotation of Transposable Elements[END_REF] and VLP formation(Lee et al., 2020) in these mutant backgrounds. In order to capture the full picture of the eccDNA circular structures, we performed eccDNA-seq using ONT long reads(Lanciano et al., 2021; Zhang et al., 2021) on the ddm1 pol4 rdr6 triple mutant plants. This analysis further validated that EVD (Figure II.6B) and VANDAL21 (Figure II.6C) lead to the formation bona fide eccDNAs but also truncated ones (Figure II.6D-F).

  Figure II.6. The eccDNA repertoire in A. thaliana epigenetic mutants contains active full length and truncated TEs. (A) Heat map showing the profile of the extrachromosomal circular TEs among all 318 Arabidopsis TE families in Col-0, ddm1, ddm1 pol4, ddm1 rdr6 and ddm1 rdr6 pol4 triple mutant plants using Illumina eccDNA-seq (left panel). The number of circular TE is normalized by the number of mapped reads per million. Low abundant eccDNAs are visualized on a heat map without the top two abundant TEs (EVD and VANDAL21) (right panel) (B) & (C) Coverage of TE circles in the ddm1 rdr6 pol4 triple mutant using short read (replicates rep1, rep2) and long read sequencing compared to the Arabidopsis wild-type Col-0 (replicates rep1, rep2) at the EVD (B) locus and the VANDAL21 (C) loci (Illumina: ILL, Nanopore: ONT). ONT reads result in clearer boundaries and uniform coverage for active TEs. (D) Schematic view of EVD strcutre: 2 LTRs, a GAG (green) and a polyprotein (POL) cleaved into 4 active functional domains: AP (orange), IN (cyan), RT (purple) and RH (dark orchid). (E) Different EVD-eccDNA structures detected using ONT eccDNA-seq. Structure 1: A single read contains more than 2 full-length copies of EVD; Structure 2: A single read contains more than 5 incomplete EVD copies with lost GAG, AP and IN domains. Another single read contains more than 12 incomplete EVD copies with lost GAG, AP, IN and RT domains; Structure 3: A single read contains more than 5 incomplete EVD copies with lost IN and RT domains. Another single read contains more than 8 incomplete EVD copies with lost AP, IN and RT domains; Structure 4: Incomplete EVD with the loss of LTR (Figure 5E). (F) Distribution of read length and percentage of different EVD structures.

Figure

  Figure II.7. TE insertion polymorphisms in A. thaliana epigenetic mutants revealed by ONT genome sequencing. (A) Insertion numbers of 7 mobilized TE families in the genome of the ddm1, ddm1 rdr6, ddm1 pol4 and ddm1 rdr6 pol4 mutants. (B) Target site preferences of different TE families in the ddm1 rdr6 pol4 genome. (C), (D) and (E). Localisation of new insertions of Copia retrotransposons. Truncated insertions are highlighted (EVD, blue triangle, ATCOPIA21 green triangle). The above figure shows the

  Figure II.8. Chimeric eccDNA containing a truncated EVD-gene fusion corresponding to a chimeric genomic integration in A. thaliana ddm1 rdr6 pol4 mutant. (A) A chimeric eccDNA consisting of truncated EVD (701bp) fused to a truncated AT5G66440 gene fragment (708bp). (B) eccDNA-seq reads (Illumina and ONT) containing EVD were selected and mapped to the TAIR10 reference genome and shown at the AT5G66440 locus. The chimeric EVD reads were detected by both short and long read eccDNA-seq in the ddm1 rdr6 pol4 mutant. (C) The chimeric EVD-AT5G66440 corresponds to a new copy of EVD (in red) from whole genome re-sequencing. (D) The EVD insertion at AT5G66440 created a 5bp target site duplication.

  inversion and its function in relation to DDM1 remains unclear. This observation nevertheless reveals that long studied mutants might still hide surprising genomic alterations.Occurrence of large duplication events in the genome of Arabidopsis ddm1-2 mutantsIn addition to the Chr2-2M inversion, we detected a 55kb duplication (Chr1:5,548,395-5,603,615) and a 56kb duplication (Chr2:231,518-287,731) in two ddm1 siblings, respectively. We use the detection of the 55kb duplication (starting at the 5'UTR of AT1G16220 and ending within a AT1G16390 exon) as an example. The coverage of ddm1 ONT reads aligned to the TAIR10 reference genome increased 2-fold at the region of Chr1:5,548,395-5,603,615 whereas the coverage of Col0 reads showed a flat distribution (Figure II.10A). We analyzed long reads crossing the junction of two tandem copies (Figure II.10B) and confirmed the 55kb duplication by dot plots (Figure II.10C).

  Figure II.10. Detection of a 55kb duplication on chromosome 1 in the A. thaliana ddm1-2 mutant genome. (A) Read depth of the A. thaliana wild type Col-0 and ddm1-2 ONT reads aligned to the TAIR10 reference genome on chromosome 1. (B) Scheme indicating how the ONT reads (orange arrows) spanning the junction of the two tandem copies will be split and aligned on the reference. (C) Dot plot showing a raw 46kb long ONT read versus the reference at the duplicated region on chromosome 1. (D) Cytosine methylation at the duplicated gene at the start of the 55kb duplication. From top to bottom, the plot shows the genome coordinates, gene transcripts, ONT read mapping with modified bases as closed (methlated) or open (unmethylated) circles, raw log-likelihood ratios, and smoothed methylated fraction plot. Exons of the AT1G16220 gene are highlighted.

  inversion in the A. thaliana ddm1-2 mutant genome. (A) Comparison of ddm1-2 genome assembly and reference genome on chromosome 2, and ddm1 rdr6 pol4 genome assembly and reference genome on chromosome 2. (B) Diagram of the Chr2-2M inversion which breaks at the retrotransposon ATGP1 and a hypothetical gene (AT2G07806) corresponding to mitochondrial DNA integrated into the nuclear genome (Saccone et al., 2000). (C) Alignment of raw reads spanning the two breakpoints of the Chr2-2M inversion in dot plots. (D) Schematic representation of Chr2-2M inversion at the nucleotide level. (E) Inversion breakpoints correspond to "cold" (blue) spots revealed by Hi-C data (Feng et al., 2014). (F) & (G) Read mapping of whole-genome sequencing of ddm1-1 and ddm1-2 generated by Vongs et al. in 1993, and ddm1-2 EpiRiL mutants by Vongs et al. in 2014. Different sequencing technologies (Illumina: ILL, PacBio: PB and Nanopore: ONT) are indicated. The left side alignment of ATGP1 (AT2TE07550) resulted in a 5bp duplication (G).

: a new tool for meta-assembling plant genomes with long reads ......

  My contribution to SASAR ................................................................................ 2.2.2 SASAR manuscript (bioRxiv, 2022) ..................................................................

	2.2.1

2.3 Tracking TE mobility and genome instability with long reads ..........................

  My contribution to the discovery of genome instability in Arabidopsis epigenetic mutants ...................................................................................................................... 2.3.2 « Chimera » manuscript (bioRxiv, 2022) ..........................................................

	2.3.1

3. General discussion and perspectives ......................................................... 3.1 Future trends to understand the role of eccDNAs ...........................................

  Remaining questions on eccDNA inheritance and the emergence of new genes ................................................................................................................................. 3.1.2 Towards eccDNA detection directly from genomic data .................................

	3.1.1

3.2 Future trends to obtain high-quality genome assembly .................................. 3

  .2.1 Choice of long read sequencing technologies ................................................ 3.2.2 Emerging tools to characterize SVs in pan-genomes ..................................... 3.2.3 Having a pan-genome alternative ...................................................................

3.3 Future trends to uncover the relationship between TEs, eccDNAs and SVs 3

  .3.1 On the role of VLP in fast TE and TE-gene chimerism evolution ................... 3.3.2 Interactions between eccDNA and the genome in the context of the 3D genome .................................................................................................................................

  Whole genome alignment of every two assemblies is conducted using Minimap2 to capture accurate base alignment (Figure II.2: step 1). Then SASAR uses CIGAR string values to parse the PAF file to obtain statistics on alignment length, indel size and gap

	compression	identity	(which	is	defined	by	Minimap2	developer
	http://lh3.github.io/2018/11/25/on-the-definition-of-sequence-identity).	The	non-
	mapped and contigs that only have one hit are retained, and the contigs mapped
	multiple times in the entire area are replaced by the corresponding longest contigs in

2.1.2 ecc_finder manuscript (Frontiers in Plant Science, 2021)

Acknowledgments

Acknowledgments

We thank our colleagues from the IRD and LGDP laboratories, our EpiDiverse colleagues for stimulating discussions. MM is supported by a grant from the French National Agency for Research (ANR-13-JSV6-0002 "ExtraChrom"). This study is set within the framework of the "Laboratoire d'Excellence (LABEX)" TULIP (ANR-10-LABX-41) and of the "Ecole Universitaire de Recherche (EUR)" TULIP-GS (ANR-18-EURE-0019). PZ and MM are members of the European Training Network "EpiDiverse" that received funding from the EU Horizon 2020 program under Marie Skłodowska-Curie grant agreement No 764965.

Data and code availability

All high-throughput sequencing data generated in this study have been the European Nucleotide Archive (ENA, https://www.ebi.ac.uk/ena) under the PRJEBXXX project.

Source codes are available at https://github.com/njaupan/eccDNA-Genome.

Abbreviations

Activator Ac

Argonaute RISC Component 4 AGO4

Aspartic protease

Discussion

We have shown that there is a strong dependency of assembly contiguity on read length and sequencing coverage with reference-free approach. Although Hi-C has been widely adopted and undoubtedly improves the assembly into pseudomolecule level (Jupe et al., 2019), there are still some challenges that may hinder the ability of Hi-C to form chromosome-level pseudomolecules alone [START_REF] Dudchenko | The Juicebox Assembly Tools module facilitates de novo assembly of mammalian genomes with chromosome-length scaffolds for under[END_REF]. In principle, Hi-C data is relatively noisy, and this process relies on the aligning Hi-C reads to the draft assembly. Some small contigs with highly repetitive sequences failed to be accurately scaffolded because of conflicting Hi-C link data [START_REF] Ghurye | Integrating Hi-C links with assembly graphs for chromosome-scale assembly[END_REF]. This issue could be resolved by SASAR before or after using Hi-C.

Methods

Plant material

The Arabidopsis thaliana wildtype Col-0 plants were used in this study. Plants were grown in a growth chamber in soil under a 16h/8h (light/dark) cycle after a 2 days stratification step at 4°C. One-month-old plants (aerial parts) were harvested.

DNA preparation

Genomic DNA from plant material was extracted and ground to a fine powder in liquid nitrogen. The powder was resuspended in 10 ml of 65°C preheated CTAB2X extraction buffer (2% CTAB, 100 mM Tris-HCl pH 8, 20 mM EDTA pH 8, 1.4 M NaCl, 5% Nlauroylsarcosine di-sodium salt, 0.2% 2-mercaptoethanol) and incubated for 60 min at 65°C. Then, an equal volume of chloroform was added and the emulsion was maintained during 10 min before centrifugation at 4,500 rpm for 10 min at room temperature. The nucleic acids were precipitated with isopropanol (0.7 v/v) at -80 °C for 15 min and centrifuged at 4°C at 4,500 rpm for 45 min. Nucleic acids were further washed with 75% ethanol and centrifuged at 4°C at 4,500 rpm for 10 min. Finally, the pellet was air dried and DNA was resuspended in 300 μl TE (Tris-Hcl 10 Mm pH 8, EDTA 1mM pH 8) and was treated with 100 ng of RNase A (Qiagen, Hilden, Germany)

for 30 min at 37°C. In order to purify the DNA, two steps were added: first, we used a Genomic DNA clean and concentrator column (Zymo, D4010, USA) on 10 µg of DNA Guppy (v4.2.2) using the SQK-LSK108 library type. Comparison of read length distribution and quality between the runs displaying different fragmentation size for three biological samples was visualized in R using package ggplot2 [START_REF] Wickham | ggplot2: Elegant Graphics for Data Analysis[END_REF].

Adapters of the ONT Ligation Sequencing Kit 1D (SQK-LSK108) were removed using Porechop (v0.2.1, https://github.com/rrwick/Porechop) with setting -discard_middle, from which reads with internal adapters were discarded. Reads sequenced from the same library of the same species were merged.

Long-read genome assemblies

Raw reads were corrected by Canu (v1.9), which includes a de novo correction module, using MHAP to align long reads against themselves and pbdagcon to correct the long reads by a consensus step. We applied 5 long read assemblers: Canu (v1.9), Minimap2/Miniasm (v0.3-r179-dirty) [START_REF] Li | Minimap and miniasm: fast mapping and de novo assembly for noisy long sequences[END_REF], Flye (v2.7) [START_REF] Kolmogorov | Assembly of long, errorprone reads using repeat graphs[END_REF], SMARTdenovo (Liu et al., 2021), Shasta and WTDBG2 (Ruan and Li, 2019) in our computational cluster with 2 nodes, 300G RAM. Canu was used to build consensus with module "-trim-assemble" and remaining parameters keep the same as described above in the correct method on each correct dataset. Flye was deployed by default parameters with an estimated genome size of corresponding genome size for three species. SMARTdenovo was performed on the Canu corrected reads and parameters were set with -c 1, -k17 as suggested by developers for large genome. WTDBG2 was run with default settings to produce assemblies.

Quality evaluation of draft assemblies

Whole genome alignments between the resulting assemblies and the corresponding reference genomes were rerun by minimap2 with two degrees of alignment divergence, module "asm5" for up to 1%, module "asm20" for up to 10%. Identity percentage was calculated by stats_from_paf.py. Genome-genome alignment dot plots were visualized using D-GENIES (Cabanettes and Klopp, 2018). Quality metrics for each assembly were produced using "stats_from_asm.py" and BUSCO (v3) [START_REF] Waterhouse | BUSCO Applications from Quality Assessments to Gene Prediction and Phylogenomics[END_REF] using corresponding reference genomes. BUSCO was run with default parameters. The 'embryophyta_odb9' was used as a reference gene set. To assess the assembly resolution of repeated regions, centromeric repeats of A. thaliana (178 bp) were mapped to each corresponding draft assembly using blastn with a 100bp match

TE mobility can lead to gene mobility

In the ONT eccDNA-seq data from the triple mutant plants, we observed a striking example of chimeric eccDNA, defined as a circle originating from different genomic loci.

In this EVD-eccDNA, supported by 7 copies in a single long read ( To investigate whether this chimerism was due to the EVD TE family or could be detected for other TE families, we extracted ATCOPIA21 long reads from two replicates of ddm1 rdr6 pol4 ONT genomic datasets. We noticed that these ATCOPIA21 containing long reads displayed complex re-arrangements when mapped to the TAIR10 reference genome (Figure II.9A). They were divided into three segments mapping to distinct genomic regions, and here-after referred to as "3-hit" reads. One "3-hit" read started from the AT4G16950 gene encoding RPP5 (for RECOGNITION of PERONOSPORA PARASITICA 5), then spanned ATCOPIA21, and ended at the cluster that plays an important role in the innate immune response to pathogens in the Arabidopsis thaliana [START_REF] Yi | A Cluster of Disease Resistance Genes in Arabidopsis Is Coordinately Regulated by Transcriptional Activation and RNA Silencing[END_REF]. We further detected TE polymorphisms in 64 natural accessions re-sequenced with long reads (Van de Weyer et al., 2019)

Structural variants in ddm1 background go beyond TEs

To explore further the SVs in the genomes of ddm1 single mutant and ddm1 rdr6 pol4 triple mutants we assembled the corresponding genomes using ONT sequencing reads.

For ddm1 we used data obtained from two single plants with a coverage of 40.7x and 18.6x, respectively. For the triple mutant, as the plants were smaller, we used two datasets corresponding to five or six pooled plants (83.3x and 57.5x respectively). In the ddm1 genome assembly, a fragment in a contig (tig00000083) was reversed endto-end on chromosome 2 compared to the TAIR10 reference genome, suggesting a 2

Mbp inversion (Supp. Fig. 1). This large inversion was also detected in the same region on chromosome 2 in the ddm1 rdr6 pol4 genome assembly. This inversion (named Chr2-2M) breaks at the Gypsy retrotransposon ATGP1 (AT2TE07550) in 5' and at a hypothetical gene (AT2G07806) in 3'. This gene corresponds to mitochondrial DNA integrated into the nuclear genome (Saccone et al., 2000) and is located only 117 kb away from the centromere, in the pericentromeric region. To verify that the Chr2-2M inversion was not due to genome mis-assembly, ONT reads spanning the two breakpoints were extracted and aligned to the TAIR10 reference genome. Dot plots of the reads to the reference validated the accuracy of the Chr2-2M inversion.

Furthermore, the mappings of both ONT and Illumina reads were compared at the two breakpoints and showed consistent results (Supp. Fig. 1). Surprisingly, the Chr2-2M inversion resulted in a 5 bp duplication (AATCT) and an 8 bp deletion (AGATGGTT), which facilitated the detection of the inversion. We noticed that the start of the inverted fragment (GTGA) is the reverse complement (with one mismatch) to the start of the second fragment (CTCA) suggesting that a micro homology might exist between the two breakpoints. Finally, the inversion was validated using PCR amplification (not shown). Of note, the Chr2-2M inversion breakpoints corresponds to cold points in the Hi-C map obtained by [START_REF] Feng | Genome-wide Hi-C analyses in wild type and mutants reveal high-resolution chromatin interactions in Arabidopsis[END_REF].

In order to trace the origin of the Chr2-2M inversion, we thought to detect inversion from all available ddm1 whole-genome sequencing data, including ddm1-1, ddm1-2, and ddm1-2 derived epiRILs [START_REF] Tsukahara | Centromere-targeted de novo integrations of an LTR retrotransposon of Arabidopsis lyrata[END_REF][START_REF] Fu | Mobilization of a plant transposon by expression of the transposon-encoded anti-silencing factor[END_REF]Cortijo et al., 2014).

We not being able to re-integrate the genome (Garfinkel et al., 2007). However, in yeast and cattle, integration of eccDNA has been suggested [START_REF] Durkin | Serial translocation by means of circular intermediates underlies colour sidedness in cattle[END_REF][START_REF] Thierry | Macrotene chromosomes provide insights to a new mechanism of high-order gene amplification in eukaryotes[END_REF]. More recently, studies in cancer cells have shown that eccDNAs that contain oncogenes (Verhaak et al., 2019;Wu et al., 2022) are able to integrate back into the genome (Koche et al., 2020). In our study, we present evidence that suggest the integration of truncated TEs in planta. Whether truncated eccDNAs are formed at the transcript level, in the VLP, or post-integration in the genome requires further investigations. Truncated TE insertions were also detected in the genome of ddm1 single mutant and ddm1 pol4 double mutant, suggesting that the ddm1 mutant background itself is sufficient to promote these truncated TE integrations.

TE-induced SVs in ddm1 rdr6 pol4

SVs are enriched for repeated DNA including TEs [START_REF] Audano | Characterizing the Major Structural Variant Alleles of the Human Genome[END_REF]Carvalho and Lupski, 2016;[START_REF] Krasileva | The role of transposable elements and DNA damage repair mechanisms in gene duplications and gene fusions in plant genomes[END_REF]), as exemplified for NLR genes in pepper retrogenes [START_REF] Kim | New reference genome sequences of hot pepper reveal the massive evolution of plant disease-resistance genes by retroduplication[END_REF] or for the sun locus in tomato [START_REF] Xiao | A Retrotransposon-Mediated Gene Duplication Underlies Morphological Variation of Tomato Fruit[END_REF]. More recently, large scale studies of SV in tomato identified repeats in around 80% of SVs (Alonge et al., 2020).

In a rice pan-genome analysis, half of the SVs (for the c. 80,000 for which they could assign a possible mechanism) were associated with TE insertions (Qin et al., 2021). To date, most TE-mediated SVs have been identified in natural variants, and the mechanism underlying these TE-mediated SVs is not yet clear. Here we show that retrotransposon mobility can lead to gene cluster duplication in ddm1 rdr6 pol4 mutants.

We have not observed TE-mediated SVs at genes in the single ddm1 mutant suggesting that a heavy load of TE mobility is necessary to induce SVs. families by mapping them with BWA to the reference genome and normalized with FPKM (fragments per kilo base per million mapped reads, paired-end).

EVD functional annotation

The two LTR sequences were identified by self-to-self alignment using BLAST. The sh-GAG structure of EVD was identified previously, indicating splicing of AP [START_REF] Oberlin | A genome-wide transcriptome and translatome analysis of Arabidopsis transposons identifies a unique and conserved genome expression strategy for Ty1/Copia retroelements[END_REF], and long read RNA-seq [START_REF] Panda | Long-Read cDNA Sequencing Enables a "Gene-Like" Transcript Annotation of Transposable Elements[END_REF] further confirmed the sequences of GAG and AP. RH sequence was identified using VLP data from the same ddm1 mutant (Lee et al., 2020).

Detection of truncated and chimeric eccDNAs from ONT eccDNA-seq

EccDNA-seq data were filtered for reads containing EVD. These EVD reads were mapped on the annotated structural domains of the EVD sequence using minimap2.

Different profiles, such as the loss of different structural domains, were visualized using dotplot and then systematically grouped using bedtools groupby. In the next step, EVD reads were remapped to the reference genome using minimap2 to check for unmapped sequences. Chimeric eccDNAs supported by at least 5 reads were retained. The same approach was used for ATCOPIA21 eccDNAs.

Structural variant detection from de novo assembly of ONT reads

ONT genomic reads were assembled using Canu v2.0 (Koren et al., 2017) with with the following modification of default parameters: -nanopore genomeSize=130m corMhapSensitivity=high corMinCoverage=0 corOutCoverage=100. The producing genome assemblies were polished with Pilon [START_REF] Walker | Pilon: an integrated tool for comprehensive microbial variant detection and genome assembly improvement[END_REF] and then matched against the TAIR10 reference genome using Mummer4 (Marçais et al., 2018). The raw match results were further filtered using delta-filter and then subjected SV detection using Syri (Goel et al., 2019).

Detection of TE insertion polymorphisms from ONT genomic reads

Reads spanning the entire insertion and deletion sequence do not cause alignment breakpoints, but are flagged in the CIGAR. We developed a script to filter the CIGAR 103 output. This pipeline can be found on GitHub (https://github.com/njaupan/CIGAR_SV).

Briefly, in order to extract all reads containing insertions and deletions, we generated a PAF file from minimap2 (-cs -cx map-ont) (Li, 2018, 2) . The CIGAR metrics were then indexed until the position of the SV on the reference genome. Breakpoints with more than 5 supported reads at the same position were selected. The start and end positions of the breakpoints were extracted from the PAF file and grouped to generate common breakpoints displayed in BED format. The breakpoint locations were finally filtered for the presence of 5-20bp TSDs supporting bona fide TE insertion polymorphisms.

Identification of inversion and duplication

SVs from minimap2 alignments were detected using Sniffles v2.0 (Sedlazeck et al., 2018), which generated a VCF file for each Arabidopsis mutant separately. The VCF file were furthered filtered for duplications, inversions and translocations larger than 1kb. In order to detect inversions, reads at the two junctions were extracted and visualized with dotplot. The final Chr2-2M inversion was visually validated using Jbrowse (Buels et al., 2016) and re-constructed manually. For duplications, read depth was calculated with samtools depth [START_REF] Li | The Sequence Alignment/Map format and SAMtools[END_REF] and visualized with samplot (Belyeu et al., 2021). Read spanning the junctions of two tandem duplications were extracted to identify the different copies.

Detection of DNA methylation from ONT genomic reads

Cytosine methylation patterns were detected from ONT reads using Nanopolish [START_REF] Simpson | Detecting DNA cytosine methylation using nanopore sequencing[END_REF]. The methylation patterns at the two ends of the Chr2-2M inversion and the two duplications were parsed and plotted using methylartist (https://github.com/adamewing/methylartist).

General discussion and perspectives

computational performance are needed to develop this algorithm. The sensitivity of this approach would also have to be evaluated.

Future trends to obtain high-quality genome assembly

Choice of long read sequencing technologies

PacBio and ONT are currently the mainstream long read sequencing technologies, with PacBio HiFi reads having an advantage in high accuracy and ONT reads having an advantage in read length. How to select sequencing technologies and obtain high quality genome assemblies is critical. Recently, the differences between PacBio and ONT in genome assembly of spruce, rice, and maize species have been compared, and we take maize as an example for a detailed description.

Using PacBio sequencing (62X coverage), ONT sequencing (50X coverage), Liu et al.

(2020) compared the assembly results of PacBio alone, ONT alone, and PacBio +ONT+physical mapping, respectively, and the results showed that the contiguity of PacBio assembly was 20 times higher than that of ONT, but ONT assembly showed better results in assembling large repeats and high heterozygous regions. When combining PacBio with ONT+physical map assembly, the overall maize genome Contig N50 reached 162 Mb, and the Gap number was only 1.3 Mb, which is the best maize genome assembly contiguity so far (Liu et al., 2020a). (3) ONT, and (4) lllumina short-read data (TRITEX). The CLR data were assembled separately using MECAT and wtdbg2 softwares; CLR and TRITEX data were mixed using Wengan software; CCS data were assembled using Hi-Canu [START_REF] Nurk | HiCanu: accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads[END_REF] and Falcon (https://github.com/PacificBiosciences/FALCON), respectively; ONT data were assembled using Smartdenovo (https://github.com/ruanjue/smartdenovo). Five LTR_retriever and LTRclassifier), TEsorter has a clear advantage in terms of accuracy and computational speed [START_REF] Zhang | TEsorter: an accurate and fast method to classify LTR-retrotransposons in plant genomes[END_REF].

In the future, more effective SV detection algorithms will consist in a combination of multiple methods in order to produce better results. These above-mentioned methods may still be surpassed by emerging tools to facilitate breakpoint resolution. There is still a lot of room for development in this area.

Having a pan-genome alternative

Although not everyone can have a pan-genome due to sequencing price, is it possible to obtain a whole class of genes or gene families, namely pan-genes? The key question to address is how extensive is the diversity for a gene family of interest, in the target population and how much genome assembly is required to capture most of the variation.

In this respect, the construction of pan-genes for the class of disease resistance genes, the intracellular nucleotide-binding site leucine repeat receptors (NLRs) in A. thaliana The power of genes derived from gag is clearly established, and thus it will not be too surprising that endogenous genes can gain extra ability from integrase, protease, and so on. For example, the Gin2 gene (Gypsy Integrase 2) was domesticated from a retrotransposon integrase in fish, at least 500 million years ago. The Gin2 protein retains the HHCC zinc finger motif suggesting its ability to bind DNA or RNA [START_REF] Marín | GIN transposons: genetic elements linking retrotransposons and genes[END_REF][START_REF] Chalopin | Genetic Innovation in Vertebrates: Gypsy Integrase Genes and Other Genes Derived from Transposable Elements[END_REF]. Although the mechanisms for TE domestication are not known, the VLP offers a possibility for quick evolution of TEs. Indeed, partial retrotransposons were found in the VLP, but also in the eccDNA fraction and in the genome of A. thaliana ddm1 mutants, suggesting a possible route for rapid TE evolution. Re-analyzing the available VLP data of Arabidopsis ddm1 mutants in the genic regions (Lee et al., 2020) could give a hint on the genes and/or TE-gene chimeras entering the VLPs.

Interactions between eccDNA and the genome in the context of the 3D genome

The three-dimensional (3D) structure of chromatin allows for interactions between DNA elements. In tumour cells, the chromatin of eccDNA is highly opened: eccDNA contains histone modifications of enhancers and promoters (H3K4me1/3, H3K27ac), but lacks repressive histone modifications (Wu et al., 2019). Chromatin loop formation mediates the interaction between enhancers and promoters, which drives gene expression. In tumor cells eccDNA enhancers can come in close contact to genes leading to their over-expression. New ultra-long distance chromatin interactions can thus occur within eccDNAs (Wu et al., 2019). reinforces the general view that eccDNA amplification leads to higher transcription of oncogenes [START_REF] Chen | Sequencing of methylase-accessible regions in integral circular extrachromosomal DNA reveals differences in chromatin structure[END_REF].

Therefore, it would be interesting to check chromatin accessibility at loci generating chimeric eccDNA in ddm1 mutants [START_REF] Zhong | DNA methylation-linked chromatin accessibility affects genomic architecture in Arabidopsis[END_REF]. In addition, the expression of 122 chimeric genes located on these eccDNA and integrated in the genome should be measured and compared to the expression of the endogenous gene Finally, one could use Hi-C data for the direct detection of SVs. Some methods were already developed in this direction, such as Hic_breakfinder that can potentially identify all types of SVs, while others, such as HiCnv [START_REF] Chakraborty | Identification of copy number variations and translocations in cancer cells from Hi-C data[END_REF] aims to detect only copy number variants (CNVs) and translocations, respectively [START_REF] Spielmann | Structural variation in the 3D genome[END_REF].

In the thesis, I investigated TE mobility, SVs in de novo assembly and read mapping, as well as development of tools to explore eccDNA landscape, SVs in genomes and mechanisms of eccDNA-genome interaction. Inspired by TE-gene chimera, I will further explore new gene formation in large genomes, or communications between different cells mediated by VLP cargo, as a postdoc in Cédric Feschotte's lab. 181

Appendix

The end