Les bactéries symbiotiques d'arthropodes et de nématodes De nouvelles alliées dans le contrôle des maladies infectieuses

Fabrice Vavre, Patrick Mavingui > Les arthropodes et les nématodes sont des acteurs importants de la santé humaine en étant soit des vecteurs de pathogènes (bactéries, champignons, protozoaires, virus), soit eux-mêmes des parasites. Si la lutte contre les maladies infectieuses repose essentiellement sur l'utilisation de la vaccination ou de traitements curatifs chez l'homme, la réduction des populations de vecteurs ou la limitation de leur compétence vectorielle constitue des stratégies alternatives de contrôle. Dans ce domaine, des travaux récents sur les bactéries symbiotiques hébergées par les arthropodes et les nématodes permettent d'envisager, et même de mettre en place, des stratégies originales de contrôle. < hôtes-bactéries [START_REF] Moran | Lifestyle evolution in symbiotic bacteria: insights from genomics[END_REF]. Par ailleurs, l'étude de ces interactions a ouvert de nouvelles voies pour le développement de méthodes de lutte contre les parasites et les pathogènes vectorisés. Le transfert vers l'application clinique de certaines recherches fondamentales a été exceptionnellement rapide et les récents développements dans le domaine ouvrent des perspectives particulièrement innovantes et prometteuses. Faisons un petit tour d'horizon d'un domaine en pleine expansion…

Des symbiotes qui font partie du patrimoine génétique des individus

Les arthropodes et les nématodes sont fréquemment infectés par des bactéries avec lesquelles ils entretiennent une relation durable. Ces symbiotes sont pour la plupart intracellulaires (raison pour laquelle on les qualifie fréquemment d'endosymbiotes). Ils infectent notamment les cellules reproductrices comme les ovocytes, ce qui assure leur transmission de mère à descendants. Les mâles, dont les spermatozoïdes sont pourvus d'un cytoplasme très réduit, peuvent également être porteurs, mais ils ne sont en aucun cas transmetteurs directs des symbiotes. Cette hérédité maternelle est identique à celle des mitochondries, qui ne sont rien d'autre que des symbiotes intégrés. En présence de ces symbiotes, le génotype des individus porteurs est donc composé du génome nucléaire, du génome mitochondrial et du génome de leur(s) symbiote(s).

Peut-on comprendre la biologie des organismes sans considérer leurs symbiotes ?

Diverses études, conduites notamment chez les insectes, indiquent que la majorité des espèces hébergent des endosymbiotes. Par exem-

Une bactérie n'est pas nécessairement un pathogène !

L'impact considérable des pathogènes sur la santé humaine, animale et végétale, et les conséquences dramatiques des infections sur les individus et les sociétés ont conduit la microbiologie à se focaliser sur l'étude des taxons pathogènes, et en particulier sur l'étude des interactions entre bactéries et eucaryotes. On en aurait presque oublié que ces pathogènes ne représentent qu'une infime fraction de la fantastique biodiversité du monde microbien. L'intestin humain, par exemple, est colonisé par une flore microbienne riche et diversifiée, estimée à 10 14 cellules représentant environ 800 espèces bactériennes, soit dix fois plus que le nombre de cellules de notre propre organisme [START_REF] Backhed | Host-bacterial mutualism in the human intestine[END_REF][START_REF] Ley | Ecological and evolutionary forces shaping microbial diversity in the human intestine[END_REF]. L'importance de la flore microbienne dans les processus de mise en place et de fonctionnement de notre système immunitaire et dans le contrôle des organismes pathogènes commence juste à être appréciée [START_REF] Swynghedauw | L'évolution biologique : grande oubliée de l'enseignement médical et base rationnelle d'une politique de santé[END_REF]. Chez les animaux, les arthropodes et les nématodes offrent un exemple particulièrement frappant de la diversité des interactions entre les bactéries et leurs hôtes. Leur étude permet d'appréhender la multitude de formes que peuvent prendre ces interactions qui font intervenir de nombreux aspects des relations diéthylcarbamazine, ivermectine) qui entraînent la mort des nématodes et la libération des bactéries. Un autre aspect de la nature obligatoire de l'association entre Wolbachia et les nématodes est qu'elle permet de mettre en place de nouvelles stratégies de traitement ciblant directement la bactérie symbiotique. En effet, l'administration d'antibiotiques, comme la doxycycline, a un impact sur la bactérie avec pour conséquence une réduction importante de la croissance et de la reproduction des filaires [START_REF] Taylor | Macrofilaricidal activity after doxycycline treatment of Wuchereria bancrofti: a double-blind, randomised placebo-control led trial[END_REF][START_REF] Hoerauf | Wolbachia endobacteria depletion by doxycycline as antifilarial therapy has macrofilaricidal activity in onchocerciasis: a randomized placebocontrolled study[END_REF][START_REF] Debrah | Macrofilaricidal effect of 4 weeks of treatment with doxycycline on Wuchereria bancrofti[END_REF]. Ces antibiothérapies, associées à des traitements nématicides, permettent également de réduire la réponse inflammatoire associée à ces traitements. Des essais cliniques associant ces molécules ont été réalisés dans les filarioses lymphatiques et l'onchocercose et leurs résultats sont particulièrement encourageants [START_REF] Taylor | Lymphatic filariasis and onchocerciasis[END_REF]. Certains développements sont encore nécessaires (les effets secondaires des antibiotiques utilisés ne permettent pas leur utilisation chez les enfants et les femmes enceintes), mais des progrès considérables ont été réalisés dans le traitement contre ces parasites.

Des symbiotes protecteurs comme agents limitant la compétence vectorielle

Certains endosymbiotes confèrent des avantages à leurs hôtes sans pour autant être indispensables. Parmi ces avantages, très divers, on peut citer la résistance à différents stress abiotiques 1 ou biotiques. En particulier, les endosymbiotes protègent fréquemment leurs hôtes contre des ennemis naturels. Le spectre d'action des endosymbiotes est particulièrement étendu puisque les organismes qui y sont sensibles comprennent aussi bien des microparasites (virus, bactéries) que des macroparasites (nématodes, insectes). Cette interaction négative entre symbiotes à transmission verticale et parasites s'explique par le conflit entre ces deux protagonistes. Les parasites diminuent la capacité reproductive de leurs hôtes et entravent donc également la transmission des symbiotes. Un symbiote protecteur sera donc sélectionné puisqu'en préservant son hôte de l'infection parasitaire, il favorisera sa propre transmission par rapport à celle de symbiotes non protecteurs. Les mécanismes de la protection peuvent prendre différentes formes. Ils peuvent notamment impliquer des interactions directes entre le symbiote et les parasites. C'est le cas chez le puceron du pois : la bactérie Hamiltonella defensa symbiote du puceron possède un phage codant des toxines probablement à l'origine de la résistance de l'insecte à des attaques de parasitoï- 1 Un facteur écologique non dépendant des êtres vivants est dit abiotique.

ple, des inventaires menés sur la bactérie Wolbachia (un membre des Rickettsiales qui a fait l'objet de nombreuses études) indiquent qu'elle infecterait plus de 60 % des espèces d'insectes [START_REF] Hilgenboecker | How many species are infected with Wolbachia? A statistical analysis of current data[END_REF] ; et Wolbachia n'est qu'un représentant parmi d'autres de l'importante diversité des endosymbiotes d'arthropodes. L'infection par des endosymbiotes est donc la règle plutôt que l'exception. Par ailleurs, ces symbiotes ont des effets particulièrement variés chez leurs hôtes : ils participent à des fonctions nutritionnelles [START_REF] Baumann | Biology of bacteriocyte-associated endosymbionts of plant sap-sucking insects[END_REF], manipulent la reproduction [START_REF] Engelstädter | The ecology and evolution of microbes that manipulate host reproduction[END_REF] ou protègent contre des ennemis naturels [START_REF] Brownlie | Symbiont-mediated protection in insect hosts[END_REF] (Figure 1). La découverte de ces différents effets a tout simplement révolutionné l'étude de la biologie de ces organismes.

Des symbiotes obligatoires comme cible thérapeutique : exemple des filaires

La transmission verticale des symbiotes a pour conséquence qu'ils dépendent de la reproduction de leurs hôtes pour leur propre dissémination. Cet « alignement des intérêts » des deux partenaires limite de fait l'évolution vers la pathogénie : un symbiote qui diminuerait la valeur reproductive de son hôte limiterait également sa propre transmission. Mieux encore, les symbiotes qui augmentent la capacité reproductive de leurs hôtes sont mieux transmis et donc sélectionnés, favorisant ainsi l'émergence du mutualisme (voir Glossaire). Entre 10 et 20 % des insectes dépendent de leurs partenaires bactériens pour leur propre développement ou leur reproduction [START_REF] Baumann | Biology of bacteriocyte-associated endosymbionts of plant sap-sucking insects[END_REF]. En général, ces symbiotes obligatoires apportent à leur hôte des compléments nutritifs et se rencontrent chez des hôtes qui se développent sur des ressources pauvres ou déséquilibrées. De nombreux ravageurs de culture -comme les pucerons -hébergent ainsi des bactéries symbiotiques qui leur fournissent des acides aminés essentiels, présents en très faible quantité dans la sève des plantes qu'ils consomment. Chez les hématophages stricts, comme la mouche tsé-tsé, les symbiotes fournissent des vitamines B dont le sang des vertébrés est dépourvu [START_REF] Aksoy | Tsetse: a haven for microorganisms[END_REF]. L'utilisation des symbiotes obligatoires comme cible thérapeutique est préconisée dans les pathologies dues aux nématodes filaires [START_REF] Taylor | Wolbachia bacterial endosymbionts of filarial nematodes[END_REF], dont l'agent de l'onchocercose (ou cécité des rivières), Onchocerca volvulus, ou encore les agents des filarioses lymphatiques (dont l'éléphantiasis) et notamment les genres Brugia et Wuchereria. La majorité des filaires hébergent une bactérie endosymbiotique, Wolbachia, qui est essentielle à leur développement et à leur reproduction [START_REF] Langworthy | Macrofilaricidal activity of tetracycline against the filarial nematode Onchocerca ochengi: elimination of Wolbachia precedes worm death and suggests a dependent relationship[END_REF]. Les facteurs responsables du mutualisme restent discutés, mais le séquençage et l'analyse du génome des filaires et de celui de leur symbiote bactérien ont permis d'identifier des candidats dont les gènes assurant la synthèse de l'hème par la bactérie [START_REF] Foster | The Wolbachia genome of Brugia malayi: Endosymbiont evolution within a human pathogenic nematode[END_REF]. En 1995, cette symbiose a été décrite pour la première fois chez les nématodes [START_REF] Sironi | Molecular evidence for a close relative of the arthropod endosymbiont Wolbachia in a filarial worm[END_REF]. Une quinzaine d'années plus tard, cette découverte apparaît comme l'une des plus importantes dans le domaine des pathologies associées à ces filaires. Tout d'abord, chez les patients infectés par les filaires, Wolbachia est à l'origine d'une réponse inflammatoire importante conduisant à l'aggravation de l'expression des symptômes cliniques [START_REF] Andre | The role of endosymbiotic Wolbachia bacteria in the pathogenesis of river blindness[END_REF]. Cette réponse inflammatoire est particulièrement importante lors de l'administration de traitements nématicides (albendazole, SYNTHÈSE REVUES des (voir Glossaire) [START_REF] Moran | The players in a mutualistic symbiosis: insects, bacteria, viruses, and virulence genes[END_REF][START_REF] Oliver | Bacteriophages encode factors required for protection in a symbiotic mutualism[END_REF]. Les endosymbiotes peuvent également entrer en compétition avec les parasites pour certaines ressources, en particulier lorsque les deux protagonistes sont capables de coloniser les mêmes tissus ou cellules, comme c'est le cas chez les moustiques [START_REF] Zouache | Persistent Wolbachia and cultivable bacteria infection in the reproductive and somatic tissues of the mosquito vector Aedes albopictus[END_REF][START_REF] Moreira | A Wolbachia symbiont in Aedes aegypti limits infection with dengue, Chikungunya, and Plasmodium[END_REF] (Figure 2). Enfin, ces effets pourraient être relayés par le système immunitaire de l'hôte. Ainsi, chez la mouche tsé-tsé, le symbiote obligatoire entraîne la surexpression d'un récepteur de l'immunité innée (le PGRP-LB, peptidoglycan recognition protein L), un immunomodulateur qui permettrait le maintien de la symbiose [START_REF] Wang | Interactions between mutualist Wigglesworthia and tsetse peptidoglycan recognition protein (PGRP-LB) influence trypanosome transmission[END_REF]. Toutefois, cette surexpression s'accompagne également d'une résistance de l'insecte à l'infection par Trypanosoma cruzii (l'agent de la maladie de Chagas2 ). Cette résistance s'expliquerait par une action antitrypanosomiale directe du PGRP-LB. Ce résultat est intéressant à deux titres :

(1) il montre que les symbioses peuvent fournir des systèmes modèles pour étudier l'immunité, et notamment pour comprendre comment les organismes modulent leur réponse en fonction de l'agent en jeu ;

(2) il suggère que le compartiment symbiotique pourrait être utilisé pour réduire la compétence vectorielle (voir Glossaire) des insectes vecteurs. Pour ce qui est de la limitation de la capacité de vection (voir Glossaire), des résultats récents obtenus chez le moustique Aedes aegypti (Diptera, Culicidae) sont à souligner. Chez cette espèce, qui n'est pas naturellement infectée par Wolbachia, la souche wMelPop de cette bactérie présente naturellement chez la mouche du vinaigre Droso-phila melanogaster a été introduite ; la bactérie s'est installée et est transmise de manière très efficace à la descendance [START_REF] Mcmeniman | Stable introduction of a lifeshortening Wolbachia infection into the mosquito Aedes aegypti[END_REF]. Chez Ae. aegypti, la présence de Wolbachia entraîne une surexpression de nombreux gènes de l'immunité [START_REF] Moreira | A Wolbachia symbiont in Aedes aegypti limits infection with dengue, Chikungunya, and Plasmodium[END_REF][START_REF] Kambris | Immune activation by lifeshortening Wolbachia and reduced filarial competence in mosquitoes[END_REF] qui est certainement à l'origine de la protection observée contre divers agents infectieux dont les virus du chikungunya (Alphavirus) et de la dengue (Flavivirus), tous deux responsables d'arboviroses qui portent leur nom respectif. On peut citer aussi le protozoaire Plasmodium gallinaceum, agent de la malaria des volailles, et le nématode Brugia pahangi, responsable de la filariose des rongeurs [START_REF] Moreira | A Wolbachia symbiont in Aedes aegypti limits infection with dengue, Chikungunya, and Plasmodium[END_REF][START_REF] Kambris | Immune activation by lifeshortening Wolbachia and reduced filarial competence in mosquitoes[END_REF][START_REF] Bian | The endosymbiotic bacterium Wolbachia induces resistance to dengue virus in Aedes aegypti[END_REF]. Sachant que cette espèce de moustique est un vecteur efficace de pathogènes, ces résultats sont particulièrement encourageants pour le développement de méthodes de lutte, surtout que cette Wolbachia possède d'autres caractéristiques sur lesquelles nous reviendrons dans le paragraphe suivant. Reste à connaître le degré de généralité de ce phénomène. En effet, des études antérieures réalisées sur Drosophila simulans et Aedes albopictus n'avaient pas mis en évidence d'effet de l'infection par Wolbachia sur l'expression des gènes de l'immunité [START_REF] Bourtzis | Wolbachia neither induces nor suppresses transcripts encoding antimicrobial peptides[END_REF]. De plus, chez Ae. albopictus, qui est naturellement infecté par Wolbachia, la bactérie ne semble pas affecter la réplication du virus chikungunya [START_REF] Mousson | Wolbachia modulates Chikungunya replication in Aedes albopictus[END_REF]. L'effet de priming observé chez Ae. aegypti pourrait donc être lié à l'introduction récente du symbiote chez son hôte, mais cet effet pourrait bien s'atténuer après coévolution des partenaires. Toutefois, l'effet protecteur des Wolbachia contre des infections virales a été montré chez des drosophiles naturellement infectées [START_REF] Teixeira | The bacterial symbiont Wolbachia induces resistance to RNA viral infections in Drosophila melanogaster[END_REF][START_REF] Hedges | Wolbachia and virus protection in insects[END_REF], et plus récemment chez le moustique Culex quinquefasciatus confronté au virus West Nile [START_REF] Glaser | The native Wolbachia endosymbionts of Drosophila melanogaster and Culex quinquefasciatus increase host resistance to West Nile virus infection[END_REF][START_REF] Lanteri | Le virus West Nile. I. La conquête de l'Ouest[END_REF][START_REF] Lanteri | Infection par le virus West Nile chez l'homme. II. Aspects physiopathologiques et réponses immunitaires[END_REF], même si, dans ces deux cas, les mécanismes impliqués n'ont pas été identifiés. Des questions subsistent donc sur la généralité et la durabilité des protections conférées par les endosymbiotes, mais il s'agit tout de même d'une ouverture sans précédent pour la mise en place de stratégies de lutte antivectorielle basées sur l'utilisation des endosymbiotes [START_REF] Martinez | Wolbachia : une nouvelle arme dans la lutte contre le virus de la dengue[END_REF] (➜).

Symbiotes manipulateurs de la reproduction : contrôle des populations et paratransgenèse Les ruses du symbiote pour favoriser sa transmission par les femelles

La transmission uniquement maternelle des symbiotes a une conséquence importante : les mâles sont généralement des hôtes sans issue pour les symbiotes (Figure 1). Dans ces conditions, toute stratégie permettant une augmentation de la production de femelles infectées dans la descendance peut être sélectionnée, même si elle est réalisée au détriment des mâles. Plusieurs stratégies de manipulation de la reproduction par les symbiotes illustrent ce phénomène (revue dans [START_REF] Engelstädter | The ecology and evolution of microbes that manipulate host reproduction[END_REF]). La manière la plus directe d'augmenter la production de filles infectées est de changer les mâles non transmetteurs en femelles. C'est ainsi que différents endosymbiotes sont capables de transformer les embryons génétiquement mâles en femelles fonctionnelles ! Dans certains cas, cette féminisation est uniquement phénotypique (les individus restent génétiquement mâles), comme c'est le cas chez des cloportes. Chez les organismes haplodiploïdes (voir Glossaire), où les mâles se développent à partir d'oeufs haploïdes et les femelles à partir d'oeufs diploïdes, les embryons haploïdes (génétiquement mâles) sont diploïdisés par l'endosymbiote et ainsi transformés en femelles génétiques. Dans ce dernier cas, les femelles sont alors capables de se reproduire de manière clonale, entraînant la fixation rapide de l'asexualité dans les populations ou les espèces infectées [START_REF] Kremer | A new case of Wolbachia dependence in the genus Asobara: evidence for parthenogenesis induction in Asobara japonica[END_REF]. Une autre stratégie adoptée par ces endosymbiotes est le male-killing, qui consiste à tuer spécifiquement les fils de la portée. Ceci confère un avantage à l'infection notamment lorsqu'il existe une forte compétition pour les ressources dans la fratrie. Enfin, la dernière stratégie, de loin la plus prometteuse en termes d'application, est l'induction de l'incompatibilité cytoplasmique (voir Glossaire). Dans sa forme la plus simple, l'incompatibilité cytoplasmique se traduit par la stérilité du croisement entre un mâle infecté par l'endosymbiote et une femelle non infectée, tous les autres croisements étant fertiles. Ainsi, seules les femelles infectées pourront avoir des descendants (et donc produire des filles infectées) avec tous les types de mâles de la population, favorisant ainsi l'augmentation en fréquence de l'infection dans les populations.

Utilisation de la dynamique invasive des symbiotes au profit de la lutte antivectorielle

L'ensemble de ces manipulations confèrent aux endosymbiotes une dynamique invasive (ils envahissent la population à partir d'une fai-

SYNTHÈSE

REVUES

Le dernier usage potentiel de l'incompatibilité cytoplasmique est analogue à la technique de SIT (pour sterile insect technique). Le SIT était jusqu'ici basé sur le lâcher en masse de mâles rendus stériles par irradiation [START_REF] Klassen | History of the sterile insect technique[END_REF]. Chez de nombreux insectes, les femelles ne s'accouplent qu'une fois et la présence en grand nombre de mâles stériles permet ainsi de limiter les populations. Un des problèmes de cette technique est que l'irradiation limite considérablement la compétitivité des mâles, réduisant l'efficacité de la méthode. Une alternative serait donc de relâcher des mâles infectés par un symbiote induisant de l'incompatibilité cytoplasmique dans une population où ce symbiote est absent. La stérilité sera analogue à celle obtenue par irradiation, mais en revanche, ces mâles seront compétitifs. La preuve que ce concept peut fonctionner avait été obtenue dans les années 1960 chez Culex quinquefasciatus [START_REF] Laven | Eradication of Culex pipiens fatigans through cytoplasmic incompatibility[END_REF], puis plus récemment chez la mouche du fruit Ceratitis capitata [START_REF] Zabalou | Wolbachia-induced cytoplasmic incompatibility as a means for insect pest population control[END_REF]. L'incompatibilité cytoplasmique, combinée ou non au SIT, est actuellement expérimentée sur les moustiques du genre Aedes [START_REF] Martinez | Wolbachia : une nouvelle arme dans la lutte contre le virus de la dengue[END_REF][START_REF] Brelsfoard | Integration of irradiation with cytoplasmic incompatibility to facilitate a lymphatic filariasis vector elimination approach[END_REF] (➜).

Conclusion

La diversité des phénotypes induits par la présence des endosymbiotes et leur utilisation potentielle pour le contrôle des maladies infectieuses, soit directement, soit via le contrôle des populations de vecteurs, rendent leur étude intéressante. Tout d'abord, il est important de considérer les études des interactions hôtes-microorganismes dans un contexte plus large que celui des seules interactions hôtes-pathogènes. Nous avons beaucoup à apprendre d'approches comparatives entre des interactions qui diffèrent largement quant à l'issue de l'infection, mais qui peuvent être gouvernées par des mécanismes très similaires. Ensuite, le rôle majeur des bactéries symbiotiques dans la biologie des organismes parasites ou vecteurs, et la capacité de certains symbiotes à interférer avec le portage ou la vection de pathogènes en font des candidats importants dans les nouvelles stratégies de contrôle des maladies infectieuses. Les exemples prometteurs de contrôle symbiotique de pathogènes et les recherches en cours sur les mécanismes impliqués permettront de mieux exploiter ce potentiel. ‡

SUMMARY Endosymbionts of arthropods and nematodes: allies to fight infectious diseases?

Arthropods and nematodes are important protagonists in human health because either they act as vectors of pathogens (bacteria, protozoa, viruses or fungus), or are themselves parasites. Fighting infectious diseases is based essentially on vaccination (prevention) or chemotherapeutic (curative) approaches in human, but one can envisage as an alternative to reduce the number of vectors or limit their ability to spread pathogens. Such strategies controling dissemination will undoubtedly benefit from the knowledge accumumulated by recent works on powerful mechanisms developped by symbiotic insect bacteria such as Wolbachia to popagate in arthropods and nematods. This review summarizes these recent data, and indicate how these mechanisms can be manipulated to reduce the dissemination of insect vectors propagating human diseases. ‡

REMERCIEMENTS

Avec le soutien du CNRS et de l'ANR (ImmunSymbArt, ANR-10-BLAN-1701).

CONFLIT D'INTÉRÊTS

Les auteurs déclarent n'avoir aucun conflit d'intérêts concernant les données publiées dans cet article.

GLOSSAIRE

Capacité vectorielle : elle représente le potentiel du vecteur à transmettre le pathogène en prenant en compte l'écologie du vecteur et les facteurs environnementaux. Commensalisme : interaction symbiotique où le symbiote retire un bénéfice de l'association sans répercussion sur l'hôte. Compétence vectorielle : capacité du vecteur à s'infecter par le pathogène et à le transmettre. C'est une composante de la capacité vectorielle. Immunité innée : le système immunitaire inné comprend les cellules et mécanismes qui participent à l'élimination du non-soi d'une manière non spécifique. C'est la seule composante de l'immunité chez les invertébrés, alors qu'elle est complétée par l'immunité adaptative chez les vertébrés. Manipulateurs de la reproduction : symbiotes dont l'effet phénotypique se traduit par une modification de la reproduction de ses hôtes. Ces manipulations incluent différents effets comme la féminisation des mâles génétiques, l'induction de la parthénogenèse thélytoque, le male-killing ou l'incompatibilité cytoplasmique. Ces effets permettent aux symbiotes d'envahir les populations à partir de faibles fréquences. Mutualisme : interaction symbiotique entre deux organismes où chacun des partenaires tire profit de l'interaction. Ces associations peuvent être obligatoires pour les deux partenaires. Parasitisme : interaction symbiotique avec un effet négatif sur l'un des partenaires (l'hôte) et un effet positif sur l'autre (le parasite), ce dernier étant physiquement associé à son hôte. Parasitoïdes : insectes se développant aux dépens d'autres insectes et entraînant la mort des hôtes. Ils sont notamment utilisés dans les programmes de lutte biologique. Paratransgenèse : technique où l'introduction d'un transgène est réalisée non pas chez l'organisme cible directement, mais chez ses symbiotes. Symbiose : interaction durable entre deux organismes spécifiquement distincts. Cette définition large inclut le parasitisme, le commensalisme et le mutualisme. Vection : transmission d'un pathogène par un vecteur.

Figure 1 .

 1 Figure 1. Effets phénotypiques et utilisation des endosymbiotes à des fins appliquées. Les individus infectés par le symbiote sont grisés, les individus non infectés en blanc. Les effets des symbiotes sont indiqués en rouge.

Figure 2 .

 2 Figure 2. Co-infection Wolbachia (rouge) et virus Chikungunya (vert) dans le cytoplasme de cellules Aedes albopictus Aa23.Noyaux colorés en bleu (ANR SEST 06 Chikvendom).

La maladie de Chagas est due au parasite Trypanosoma cruzi ; elle est transmise par un insecte et sévit principalement sur le continent américain où plus de 100 millions de personnes sont à risque, et 10 millions de personnes infectées dans les zones endémiques de 21 pays d'Amérique Latine. La phase chronique apparaît après 10 à 20 ans d'infection silencieuse, et des lésions irréversibles peuvent toucher le coeur, l'oesophage, le côlon, et le système nerveux périphérique.

m/s n° 11, vol.27, novembre 2011

(➜) Voir la Brève de Julien Martinez, page 947 de ce numéro


J J A Q U I E ´r

S S To E C K E

P N O U H A U D

L M I E U Z E T

E ´o

F L E G E A I

† N B E R N A R D

A B O N V O I S I N

J -C S I M O N

Jean-Christophe Simon
email: jean-christophe.simon@rennes.inra.fr

Genome scans reveal candidate regions involved in the adaptation to host plant in the pea aphid complex

Keywords: ecological speciation, gene flow, genomic divergence, host plant adaptation, insect-plant interactions, outlier loci

A major goal in evolutionary biology is to uncover the genetic basis of adaptation. Divergent selection exerted on ecological traits may result in adaptive population differentiation and reproductive isolation and affect differentially the level of genetic divergence along the genome. Genome-wide scan of large sets of individuals from multiple populations is a powerful approach to identify loci or genomic regions under ecologically divergent selection. Here, we focused on the pea aphid, a species complex of divergent host races, to explore the organization of the genomic divergence associated with host plant adaptation and ecological speciation. We analysed 390 microsatellite markers located at variable distances from predicted genes in replicate samples of sympatric populations of the pea aphid collected on alfalfa, red clover and pea, which correspond to three common host-adapted races reported in this species complex. Using a method that accounts for the hierarchical structure of our data set, we found a set of 11 outlier loci that show higher genetic differentiation between host races than expected under the null hypothesis of neutral evolution. Two of the outliers are close to olfactory receptor genes and three other nearby genes encoding salivary proteins. The remaining outliers are located in regions with genes of unknown functions, or which functions are unlikely to be involved in interactions with the host plant. This study reveals genetic signatures of divergent selection across the genome and provides an inventory of candidate genes responsible for plant specialization in the pea aphid, thereby setting the stage for future functional studies.

Introduction

Divergent selection targeting ecologically important traits may result in adaptive population differentiation and eventually lead to reproductive isolation, a process referred to as ecological speciation [START_REF] Schluter | Ecology and the origin of species[END_REF][START_REF] Rundle | Ecological speciation[END_REF]. A fundamental question in speciation studies concerns the underlying genetic mechanisms favouring linkage disequilibrium between the loci under divergent natural selection and those controlling reproductive isolation, in the face of gene flow [START_REF] Via | Sympatric speciation in animals: the ugly duckling grows up[END_REF][START_REF] Bolnick | Sympatric speciation: models and empirical evidence[END_REF]. Deciphering the genomic architecture of ecological specialization and reproductive isolation is therefore essential to address this issue. The outstanding diversity of herbivorous insects, which probably results from their specialization to different host plants, offers a good opportunity to evaluate how natural selection promotes divergence and contributes to species diversification [START_REF] Berlocher | Sympatric speciation in phytophagous insects: moving beyond controversy[END_REF][START_REF] Dres | Host races in plant-feeding insects and their importance in sympatric speciation[END_REF]Peccoud et al. 2010). Partial reproductive isolation is crucial in studying ecological speciation, as the influence of ecological factors on genetic divergence is generally masked by the accumulation of further differences once the speciation is completed [START_REF] Via | Natural selection in action during speciation[END_REF]). However, genetically and ecologically differentiated populations that are still connected by substantial gene flow have been clearly identified in only few taxa [START_REF] Dres | Host races in plant-feeding insects and their importance in sympatric speciation[END_REF][START_REF] Mallet | Mayr's view of Darwin: was Darwin wrong about speciation[END_REF]. This occurs for the pea aphid, Acyrthosiphon pisum, which represents a strong case for ecological speciation by divergent selection [START_REF] Via | Reproductive isolation between sympatric races of pea aphids. I. Gene flow restriction and habitat choice[END_REF][START_REF] Ferrari | Population differentiation and genetic variation in performance on eight hosts in the pea aphid complex[END_REF]Peccoud et al. 2009a;Peccoud & Simon 2010;[START_REF] Smadja | Large-scale candidate gene scan reveals the role of chemoreceptor genes in host plant specialisation and speciation in the pea aphid[END_REF].

The pea aphid forms a worldwide complex of hostassociated sympatric populations (or host races) that feeds on more than 20 legume genera (Peccoud & Simon 2010). Each host race is specialized on one or a few legume species and is genetically differentiated from other races [START_REF] Via | The genetic structure of host plant adaptation in a spatial patchwork -demographic variability among reciprocally transplanted pea aphid clones[END_REF][START_REF] Ferrari | Population differentiation and genetic variation in host choice among pea aphids from eight host plant genera[END_REF][START_REF] Ferrari | Population differentiation and genetic variation in performance on eight hosts in the pea aphid complex[END_REF][START_REF] Ferrari | Population genetic structure and secondary symbionts in host-associated populations of the pea aphid complex[END_REF]. Peccoud et al. (2009a) recently showed that the pea aphid complex encompasses at least eight partially isolated host races and three presumable species, thereby forming a continuum of population divergence towards virtually complete speciation. The age of the most recent maternal ancestor of pea aphid biotypes was estimated, by means of sequence data from the aphid endosymbiont Buchnera, to lay between 8000 and 16 000 years, which suggests a recent and rapid adaptive radiation (Peccoud et al. 2009b). In pea aphids, the correlation between preference and performance on the same host plant species suggests a relation between divergent selection and premating isolation, which is likely to be favoured by a specific genetic architecture [START_REF] Hawthorne | Genetic linkage of ecological specialization and reproductive isolation in pea aphids[END_REF]. Quantitative trait locus (QTL) mapping analyses of host acceptance and performance in two North American A. pisum host races, one specialized on alfalfa and the other on clover, indeed suggested that pleiotropic or closely linked loci control both traits [START_REF] Hawthorne | Genetic linkage of ecological specialization and reproductive isolation in pea aphids[END_REF]. However, the precise localization of these QTLs on the pea aphid genome and the identity and function of genes underlying these traits remain largely unknown.

Genome-wide scan of large sets of individuals from multiple populations is a powerful approach to explore the genetic architecture underlying adaptive divergence and to identify loci or genomic regions under ecologically divergent selection (e.g. [START_REF] Storz | Natural selection on protein polymorphism in the rodent genus Peromyscus: evidence from interlocus contrasts[END_REF][START_REF] Vasemagi | Expressed sequence tag-linked microsatellites as a source of gene-associated polymorphisms for detecting signatures of divergent selection in Atlantic salmon (Salmo salar L.)[END_REF][START_REF] Bonin | Explorative genome scan to detect candidate loci for adaptation along a gradient of altitude in the common frog (Rana temporaria)[END_REF]. Genome scans generally rely on the assumption that loci involved in adaptation to local environmental conditions (either directly or indirectly through genetic hitchhiking) exhibit stronger differentiation among populations and lower diversity within population, as compared to selectively neutral regions of the genome [START_REF] Ll | Population structure and human evolution[END_REF][START_REF] Lewontin | Distribution of gene frequency as a test of theory of selective neutrality of polymorphisms[END_REF][START_REF] Wu | The genic view of the process of speciation[END_REF][START_REF] Storz | Using genome scans of DNA polymorphism to infer adaptive population divergence[END_REF]. Although there are some conceptual and technical limitations in their use that must be kept in mind (see [START_REF] Bierne | The distinctive footprints of local hitchhiking in a varied environment and global hitchhiking in a subdivided population[END_REF][START_REF] Bierne | The coupling hypothesis: why genome scans may fail to map local adaptation genes[END_REF][START_REF] Michel | Widespread genomic divergence during sympatric speciation[END_REF][START_REF] Roesti | Genome divergence during evolutionary diversification as revealed in replicate lake-stream stickelback population pairs[END_REF], genome scans have successfully identified genomic regions responsible for adaptation to specific environments in a wide range of organisms [START_REF] Nadeau | A golden age for evolutionary genetics? Genomic studies of adaptation in natural populations[END_REF][START_REF] Stapley | Adaptation genomics: the next generation[END_REF][START_REF] Ellegren | Genetic basis of fitness differences in natural populations[END_REF].

Here, we scanned the genome of host-adapted populations of the pea aphid to explore the organization of the genomic divergence associated with ecological specialization and speciation and to identify candidate loci involved in the adaptation to the host plant. To achieve this aim, we developed 390 microsatellite markers located at variable distances from predicted genes in the pea aphid reference genome (IAGC 2010) and analysed their variation in replicate samples of sympatric populations of A. pisum from Medicago sativa (alfalfa), Trifolium pratense (red clover) and Pisum sativum (pea), which are three host races commonly reported in A. pisum [START_REF] Frantz | Ecological specialization correlates with genotypic differentiation in sympatric host-populations of the pea aphid[END_REF]Peccoud et al. 2009a,b;[START_REF] Ferrari | Population genetic structure and secondary symbionts in host-associated populations of the pea aphid complex[END_REF]. We used a hierarchical method to identify loci showing enhanced genetic differentiation between host races, as compared to the rest of the genome. Finally, we explored the genic environment of outlier loci and assessed the putative functions of neighbouring genes based on the annotated sequence of the pea aphid genome.

Methods

Aphid sampling

Pea aphid individuals were collected on three different host plants (alfalfa, red clover and pea) (Table S1, Supporting information). These samples represent three different host races, each adapted to a specific host range and genetically differentiated from the other biotypes [START_REF] Frantz | Ecological specialization correlates with genotypic differentiation in sympatric host-populations of the pea aphid[END_REF]Peccoud et al. 2009a). Although there is little genetic structure within each host race at small and large geographic scales [START_REF] Frantz | Ecological specialization correlates with genotypic differentiation in sympatric host-populations of the pea aphid[END_REF][START_REF] Peccoud | Host range expansion of an introduced insect pest through multiple colonizations of specialized clones[END_REF][START_REF] Via | The genetic mosaic suggests a new role for hitchhiking in ecological speciation[END_REF]Peccoud et al. 2009a;[START_REF] Ferrari | Population genetic structure and secondary symbionts in host-associated populations of the pea aphid complex[END_REF], we used a hierarchical sampling strategy to avoid the potential confounding effect of geography: for each of the three host plants, we sampled populations from three different regions, separated by 100-200 km, in Western Europe (Table S1, Supporting information). Approximately 900 parthenogenetic females were collected from the nine populations (see Fig. S1, Supporting information, for further details). To obtain sufficient amounts of DNA, field-collected aphids were grown individually in controlled conditions ensuring continuous clonal reproduction (16 h light per day, 18 °C). A total of 566 (of ~900) individuals survived parasitism (e.g. fungi and parasitoids).

We then discarded from the sample all presumable copies of the same clone, the migrant individuals coming from other host races and the hybrids between host races. To do so, we genotyped the sampled individuals at seven microsatellite loci (AlA09M, AlB07M, AlB08M, AlB12M, ApF08M, ApH08M and ApH10M, see [START_REF] Caillaud | Microsatellite DNA markers for the pea aphid Acyrthosiphon pisum[END_REF]), following the conditions described in [START_REF] Peccoud | Host range expansion of an introduced insect pest through multiple colonizations of specialized clones[END_REF]. Given the high polymorphism of this set of loci [START_REF] Frantz | Ecological specialization correlates with genotypic differentiation in sympatric host-populations of the pea aphid[END_REF], individuals bearing the same multilocus genotype were considered as copies of the same clone (see Fig. S1, Supporting information, for information on the clonal composition of each population). A single copy of each clone per population was then kept for further analyses, which resulted in a total of 426 unique multilocus genotypes. To discard presumable migrants and/or hybrids in our data set, we ran the Bayesian clustering method implemented in STRUCTURE [START_REF] Pritchard | Inference of population structure using multilocus genotype data[END_REF] on the multilocus genotypes at the seven microsatellite markers, setting the hypothetical number of clusters to K = 3, which corresponds to the number of host plants. Each STRUCTURE analysis was run for 100 000 steps, after a 100 000-step burn-in period, using the admixture model that assigns individual proportions of genotypes to each cluster and discarding prior information on the collection site or the host plant. About 80% of the individuals had a large genotype membership (>90%) in a single cluster, corresponding to the host plant (and not the geographical region) from which they were collected (see Fig. S1, Supporting information).

In each population, we then selected 20 individuals among those assigned to their host plant with a probability larger than or equal to 90%. This condition was not met in two populations from pea where we had to include seven individuals that were assigned to their host plant with an 80% probability on average. All further analyses were conducted on this subset of 180 individuals (three host races 9 three geographic populations 9 20 individuals). The different steps allowing the selection of individuals for the genome-scan analysis are summarized in Fig. S1 (Supporting information).

Large-scale genotyping

The 180 selected individuals were genotyped at 390 microsatellite loci (see Table S2, Supporting information, for loci used and primer sequences) as described in Jaquie ´ry et al. (2012). These loci were picked among a larger set of 952 loci genotyped on a subsample of eight individuals from the three host races, based on the reliability of amplification, their polymorphism and the ease of scoring. The vast majority of these 390 loci was chosen to locate on different scaffolds in the V1 genome assembly of the pea aphid (IAGC 2010) to cover a wide genomic area. These loci were also selected based on their distances from genes predicted in the reference pea aphid genome. Although there is no available data on the extent of recombination and linkage disequilibrium in the pea aphid genome, we showed in a recent study that microsatellites standing at <30 kb from predicted genes displayed a reduced genetic diversity as compared to microsatellites located at more than 30 kb [START_REF] Jaquie ´ry | Accelerated evolution of sex chromosomes in aphids, an X0 system[END_REF]. This suggests that 30 kb may be considered as a relevant threshold below which neutral loci might be influenced by hitchhiking. This 30-kb threshold was, therefore, used in all analyses presented hereafter, although we insist that this particular choice shall be considered as somewhat arbitrary until confirmed by dedicated studies. Seventy-two loci were located within EST contigs [START_REF] Sabater-Munoz | Large-scale gene discovery in the pea aphid Acyrthosiphon pisum (Hemiptera)[END_REF]) and 235 loci were located at less than 30 kb from a predicted gene. Among the latter markers, 25 were located at less than 14 kb (average distance: 3.4 kb, median: 1.8 kb) from genes coding for chemosensory proteins, gustative receptors, odorant-binding proteins or odorant receptors previously annotated and potentially involved in A. pisum plant specialization [START_REF] Zhou | Genome annotation and comparative analyses of the odorant-binding proteins and chemosensory proteins in the pea aphid Acyrthosiphon pisum[END_REF][START_REF] Smadja | Large gene family expansions and adaptive evolution for odorant and gustatory receptors in the pea aphid, Acyrthosiphon pisum[END_REF][START_REF] Smadja | Large-scale candidate gene scan reveals the role of chemoreceptor genes in host plant specialisation and speciation in the pea aphid[END_REF]. The 83 remaining loci were chosen because they were located at more than 30 kb from any predicted genes in the V1 genome assembly. After genotyping, all individuals with more than 10% of missing data were eliminated, resulting in a final data set of 166 individuals genotyped at 390 loci (Table 1).

Because a new genome assembly (V2) was released after our selection of microsatellite markers, we checked for possible differences in the genomic environment of the 390 loci between the V1 and the V2 assemblies. Seven loci (of 390) could not be unambiguously located

Whole-genome genetic structure

Expected heterozygosity [START_REF] Nei | Molecular Evolutionary Genetics[END_REF]) and allelic richness (assuming a minimal sample size of eight individuals) were calculated per population for each locus with FSTAT 2.9.4 [START_REF] Goudet | FSTAT, A Program to Estimate and Test Gene Diversities and Fixation Indices[END_REF]. F IS was estimated for each locus in each population using FSTAT 2.9.4, and 95% confidence intervals (CI) of median F IS estimates were computed by bootstrapping over loci using R (R Development Core Team 2012). F IS was considered as significant if the 95% CI did not contain zero. Pairwise F ST estimates [START_REF] Weir | Estimating F-statistics for the analysis of population structure[END_REF] were computed between populations using ARLEQUIN 3.5 [START_REF] Excoffier | Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows[END_REF], and their significance was estimated by 16 000 random permutations of individuals among populations. We investigated the genetic structure of our data with STRUCTURE [START_REF] Pritchard | Inference of population structure using multilocus genotype data[END_REF], using the admixture model and varying the number of putative clusters from K = 1 to K = 9. Each analysis was replicated 10 times and consisted in 100 000 steps following a 25 000-step burn-in period. Then, to test for hidden hierarchical structure, we performed independent STRUCTURE analyses on each of the three different subgroups that were identified, as recommended by [START_REF] Evanno | Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study[END_REF].

Effect of the genomic environment on genetic structure

Natural selection is predicted to affect polymorphism not only at the targeted genes, but also at linked markers [START_REF] Maynard-Smith | Hitch-hiking effect of a favorable gene[END_REF]. We thus tested for a potential effect of the genomic environment of the microsatellite loci on allelic richness, using the following linear mixed effect model (R package Lme4, Bates & Sarkar 2007) fitted with REML (restricted maximum likelihood) and implemented in R (R Development Core Team 2012):

Allelic richness $ Number of Microsatellite Repeats þ Genomic environment þ 1jfactorðpopulationÞ þ 1jfactorðHost PlantÞ þ 1jfactorðLociÞ
The Number of Microsatellite Repeats was measured on the V2 genome assembly of the pea aphid [START_REF] Iagc | Genome sequence of the pea aphid Acyrthosiphon pisum[END_REF] as the maximal number of consecutive di-, tri-or tetranucleotide repeats found between the two primers. This provides a rough estimate of the number of repeats for each locus (as the number of repeats measured on the reference genome is used as a surrogate for the average number of repeats found in a population), but this still allows capturing essential information as the number of microsatellite repeats explains a large proportion of variance in allelic richness (see the Results section). The Genomic environment was either measured as (i) the number of RefSeq genes located in 60-kb window centred on the focal microsatellite loci or as (ii) the distance (in kb) to the first exon of the closest RefSeq gene. Two distinct models were therefore constructed using either measure, to test for the effect of the Genomic environment. The Number of Microsatellite Repeats and Genomic environment were considered as fixed effects, and Population, Host Plant and Loci were considered as random effects. The Number of Microsatellite Repeats and Genomic environment effects were tested by likelihood ratio tests based on the drop in Akaike's information criterion following the inclusion of the focal variable into the partial model comprising all other variables.

As divergent selection acting across different environments not only affect genetic differentiation at the targeted genes but also at linked markers through hitchhiking [START_REF] Ll | Population structure and human evolution[END_REF][START_REF] Lewontin | Distribution of gene frequency as a test of theory of selective neutrality of polymorphisms[END_REF][START_REF] Maynard-Smith | Hitch-hiking effect of a favorable gene[END_REF], we tested for an effect of the presence of genes in the genomic environment of the microsatellite loci on the genetic structure (F ST ) measured at these loci. To that end, we estimated the Pearson's correlation coefficient between F ST and either the number of RefSeq genes located within a 60-kb window centred on the focal microsatellite locus, or the distance between the microsatellite and the closest exon from a RefSeq gene. We also verified that the number of microsatellite repeats did not affect F ST . Finally, we also tested for a difference in genetic differentiation (F ST ) between the 25 microsatellite loci located in the vicinity of chemosensory genes and the remaining 358 loci (Mann-Whitney two-sided test).

Detection of loci influenced by selection

To detect those loci that depart from neutral expectation, and which are therefore potentially involved in the adaptation to the host plant, we used the hierarchical method developed by [START_REF] Excoffier | Detecting loci under selection in a hierarchically structured population[END_REF] and implemented in ARLEQUIN 3.5 [START_REF] Excoffier | Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows[END_REF]. This method is an extension to [START_REF] Beaumont | Evaluating loci for use in the genetic analysis of population structure[END_REF] approach, which assumes a hierarchical island model of migration between structured populations. It is therefore particularly adapted to the pea aphid complex where populations from the same host plant exchange migrants at a higher rate than populations from different host races. The distribution of the genetic differentiation among host races expected under neutrality was estimated by means of coalescent simulations. The among-race differentiation was characterized by the parameter F CT , which accounts for the geographical structure within host races. 100 000 coalescent simulations were performed conditionally on the multilocus estimate of F CT at the 390 microsatellite loci, assuming 50 groups and 100 demes per group. The observed data from each locus were compared with the simulated distribution, and a particular locus was classified as a significant outlier if it lay outside the 99% confidence envelope. For the purpose of this study, we focused on loci putatively involved in divergence between host races and therefore considered only the loci falling above the upper confidence limit, because such genome scan methods are not well adapted to detect balancing selection [START_REF] Beaumont | Identifying adaptive genetic divergence among populations from genome scans[END_REF]). As we were mostly interested in identifying outlier loci involved in host plant specialization, rather than in adaptation to local environmental conditions, we checked whether the outliers identified from this global analysis (in which all three host races were included simultaneously) were not classified as outliers within host races. To that end, we ran three independent analyses for the detection of outliers within each host race. In that case, there was only one hierarchical level, that of the populations. To identify the host race(s) in which selection targeted outlier loci, we performed three additional hierarchical analyses between each pair of host races: clover vs. alfalfa, alfalfa vs. pea and pea vs. clover.

Note that in this study, individuals were sampled using a hierarchical design to avoid confounding geographical effects or sample-related specificities. Currently, only one method (i.e. [START_REF] Excoffier | Detecting loci under selection in a hierarchically structured population[END_REF]) can account for hierarchical structure and therefore make use of all the information contained in hierarchical data sets. In a recent simulation study, [START_REF] Narum | Comparison of F ST outlier tests for SNP loci under selection[END_REF] showed that this hierarchical method had higher type I and II error rates than island-based methods (e.g. Bayescan, Fdist2). There is, however, no evidence that this conclusion applies to our case. Indeed, these authors compared bi-allelic markers (at which heterozygosity cannot exceed 0.5 by definition) with an envelope made of multi-allelic markers (at which heterozygosity lies in the [0,1] range). Additionally, they simulated genetic data under a stepping-stone migration model, while [START_REF] Excoffier | Detecting loci under selection in a hierarchically structured population[END_REF] method assumes a hierarchical migration model. As an alternative to ARLEQUIN 3.5, nonhierarchical methods such as BAYESCAN [START_REF] Foll | A genome scan method to identify selected loci appropriate for both dominant and codominant markers: a Bayesian perspective[END_REF]) can be used to analyse hierarchical data set, but this causes several difficulties.

(i) If a single analysis is performed in which the hierarchical structure is neglected, this increases the number of false positives [START_REF] Excoffier | Detecting loci under selection in a hierarchically structured population[END_REF]). (ii) Alternatively, several pairwise analyses between populations with contrasted phenotypes can be performed. This, however, raises the problem of multiple testing and of loss of power (as the whole data set cannot be used in a unique analysis). For these reasons, we chose to use the method implemented in ARLEQUIN 3.5 because it is the most adapted to analyse our hierarchical data set.

We also performed STRUCTURE and AMOVA (Analysis of MOlecular VAriance, [START_REF] Excoffier | Analysis of molecular variance inferred from metric distances among DNA haplotypes -application to human mitochondrial-DNA restriction data[END_REF] analyses on the set of outlier loci and on the set of nonoutlier loci, to test whether the two groups of loci showed similar patterns of genetic structure. For the AMOVAs, populations were nested within host races, and the significance was estimated by 16 000 random permutations.

Then, all the predicted genes located at <30 kb from the outlier loci in the V2 genome assembly of the pea aphid (IAGC 2010; [START_REF] Legeai | AphidBase: a centralized bioinformatic resource for annotation of the pea aphid genome[END_REF] were collected and blasted against nonredundant (NR) peptide database (NCBI, June 2011 version) to assess their putative functions. The NCBI NR protein database is a collection of all protein data from all species for which such information is available. Protein domains were identified with Interproscan against the Interpro database (September 2011 version) [START_REF] Hunter | InterPro: the integrative protein signature database[END_REF]). Gene ontology associations were performed with Blast2Go [START_REF] Conesa | Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research[END_REF] using Interpro and NR databases. These analyses assume similar genome organization between the reference genome (i.e. LSR1 that belongs to the alfalfa race) and the populations studied here. We cannot exclude, though, that some genomic rearrangements may have occurred in some host races.

Finally, as we specifically designed some microsatellite loci in the vicinity of the chemosensory genes described by [START_REF] Smadja | Large gene family expansions and adaptive evolution for odorant and gustatory receptors in the pea aphid, Acyrthosiphon pisum[END_REF][START_REF] Smadja | Large-scale candidate gene scan reveals the role of chemoreceptor genes in host plant specialisation and speciation in the pea aphid[END_REF] for their potential role in the adaptation to the host plant, we also tested whether the chemosensory function was overrepresented in the outlier category (test of proportion).

Genomic architecture of host plant adaptation

We investigated whether the among-host-race differentiation measured at the microsatellite loci located on the same scaffolds as the 11 ARLEQUIN 3.5 outliers (based on the V2 genome assembly) was higher than the average. The pattern of linkage disequilibrium between the loci that were physically linked with outliers was also investigated. The correlations (R 2 ) between allele frequencies between the outlier loci and those located on the same scaffold were calculated within each population using © 2012 Blackwell Publishing Ltd FSTAT 2.9.4. An overall estimate, combining R 2 values calculated within each population, was provided by FSTAT 2.9.4. P-values for linkage disequilibrium were calculated by 1000 randomizations of genotypes at each locus within populations.

Results

Genomic structure of pea aphid populations

Allelic richness ranged from 3.00 to 3.90 per population, the expected heterozygosity from 0.52 to 0.64, and F IS varied from À0.029 to 0.029 (Table 1). Populations of the pea race stood out from the two other host races, being characterized by a reduced genetic diversity at the scale of the population and by an excess of heterozygotes at the individual level, as denoted by negative F IS (significant for two of the three pea populations, see Table 1). The red clover race showed higher F IS than the other races, with two populations having significantly positive values.

Analyses with STRUCTURE revealed that the most likely number of clusters was K = 2 (based on Evanno et al.'s 2005 method), with one cluster composed of individuals collected on red clover and alfalfa and the second of those collected on pea. Nevertheless, for K = 3 the three clusters corresponded exactly to the host plant on which individuals had been sampled (Fig. 1A). For K = 3, each individual had a proportion of genome that originated from the cluster corresponding to its host plant >0.71 (average was 0.96). When analyses were run separately on each of the three clusters, the most likely number of clusters was K = 2 for pea and red clover and K = 3 for alfalfa. The membership coefficients indicated some geographical structure for populations collected on alfalfa and red clover but not for those collected on pea (Fig. 1B).

Pairwise F ST comparisons between host races confirmed a strong effect of the host plant on genetic structure: the pea race was highly differentiated from red clover and alfalfa races, with an average F ST between the two host races of 17%. Red clover and alfalfa races were less divergent (F ST = 6.9%) (Fig. S2, Supporting information). Contrastingly, there was little differentiation among populations within host races: populations collected on pea were not genetically differentiated (F ST < 0.006, NS), whereas most red clover and alfalfa populations were slightly differentiated within each host race (Fig. S2, Supporting information).

Effect of the genomic environment on the genetic structure

The number of microsatellite repeats was positively correlated with allelic richness (linear mixed effect model [LMEM], P < 10 À16 , R 2 = 41%, Fig. S3A, Supporting information). The genomic environment of the loci also influenced allelic richness: allelic richness was negatively correlated with the number of genes in a 60-kb window (LMEM, P < 0.0001, R 2 = 11%, Fig. S3B, Supporting information) and positively correlated with the distance to the closest gene (LMEM, P < 0.001, R 2 = 7%, Fig. S3C, Supporting information). Contrastingly, genetic structure (F ST ) was affected neither by the number of microsatellite repeats (Pearson correlation, P = 0.86, r = À0.009, Fig. 2A) nor by the distance to the closest gene (P = 0.12, r = À0.08, Fig. 2C), but slightly increased with the number of genes within a 60-kb window centred on each locus (P = 0.0024, r = 0.15, Fig. 2B). We found no significant difference between F ST measured at microsatellite loci located near a chemosensory gene (F ST = 0.102, n = 25) and F ST measured at the remaining loci (F ST = 0.100; n = 358) (Mann-Whitney test: w = 4601, P = 0.81).

Detection of outlier loci

We found 11 outlier loci at the a = 0.01 threshold from the global analysis with ARLEQUIN 3.5 (Table 2, Fig. 3). The hierarchical analyses run between pairs of host races also supported these outliers: all these loci but one were identified as significant outliers (at a = 0.01) in at least one pairwise comparison (and often in two © 2012 Blackwell Publishing Ltd comparisons) from the hierarchical analyses run between pairs of host races (Table 2). The only exception concerned the marker D_115338_1 (P = 0.013 in pea vs. red clover comparison). The results for all loci are provided in Table S3 (Supporting information). On the basis of their F CT values, ranking and significance as outlier in pairwise analyses, it appeared that the pea race largely contributed to the outlier status of several of these 11 loci. When ARLEQUIN 3.5 was run within each of the three host races, we detected four loci (of 390) departing from the neutral expectation (at a = 0.01) in the alfalfa race, five in the clover race and nine in the pea race (see Table S3, Supporting information). There was only one locus in common between this set of 18 within-host races outliers and the set of 11 between-host races outliers. This locus (EQ118272_44) departed from neutrality within the clover race, with F ST = 0.12 (P = 0.007). Nevertheless, this locus remained a significant outlier between host races when the analyses were performed between alfalfa and pea races (i.e. when clover populations were excluded, Table 2). AMOVA analyses performed separately on the set of 11 outliers and that of nonoutlier loci showed that in both cases, populations were significantly (P < 0.01) more structured by the host plant (F CT outliers = 0.40, F CT nonoutliers = 0.12) than by the geography (F SC out- liers = 0.02, F SC nonoutliers = 0.01). Similar results emerged from STRUCTURE analyses (see Fig. S4, Supporting information).

Alfalfa Pea Red clover M R S M R S M R S (

Genic environment of outlier loci

More than 55% of the 73 genes near outlier loci corresponded to genes with unknown functions, owing to the absence of homology with any other genes in public databases (Table S4, Supporting information). Two of the outliers (D_115338_1 and T_110814_1) were close to the genes corresponding to the olfactory receptors Or12 and Or22, respectively [START_REF] Smadja | Large gene family expansions and adaptive evolution for odorant and gustatory receptors in the pea aphid, Acyrthosiphon pisum[END_REF][START_REF] Smadja | Large-scale candidate gene scan reveals the role of chemoreceptor genes in host plant specialisation and speciation in the pea aphid[END_REF]. As we specifically developed some microsatellite loci close to chemosensory genes, it might be that this gene function is overrepresented in the outlier category just by chance. Indeed, this proportion (2 of 11) was not significantly different from that measured for nonoutlier loci (23 of 372; test of proportion: P = 0.33). Interestingly, two other outlier loci (D_121300_2, Q_116274_17) were located in the vicinity of three genes encoding salivary proteins [START_REF] Bos | A functional genomics approach identifies candidate effectors from the aphid species Myzus persicae (green peach aphid)[END_REF][START_REF] Carolan | Predicted effector molecules in the salivary secretome of the pea aphid (Acyrthosiphon pisum): a dual transcriptomic/proteomic approach[END_REF]. D_121300_2 is, indeed, located at 27 kb of gene ACYPI089376 (gene name on gene prediction 2.1), which corresponds to part of the gene ACYPI002172 (previous gene name on gene prediction 1.2) identified in the salivary secretome of the pea aphid [START_REF] Carolan | Predicted effector molecules in the salivary secretome of the pea aphid (Acyrthosiphon pisum): a dual transcriptomic/proteomic approach[END_REF]. Another gene, ACYPI54712, distant from 4.5 kb from D_121300_2 is homolog to a protein found in the salivary glands of the green peach aphid Myzus persicae [START_REF] Bos | A functional genomics approach identifies candidate effectors from the aphid species Myzus persicae (green peach aphid)[END_REF]. The outlier locus Q_116274_17 was also found to be at 12 kb from the salivary protein ACYPI000472 (that conserved the same gene ID on the 1.2 and 2.1 gene predictions). The putative function of these three genes (ACYPI089376, ACYPI54712 and ACYPI000472) is unknown. Another outlier (AlB08M) was close to a cadherin gene (ACYPI073870), a gene involved in calcium binding, a function expressed in salivary glands too [START_REF] Will | Molecular sabotage of plant defense by aphid saliva[END_REF][START_REF] Carolan | Predicted effector molecules in the salivary secretome of the pea aphid (Acyrthosiphon pisum): a dual transcriptomic/proteomic approach[END_REF][START_REF] Hogenhout | Effector proteins that modulate plant-insect interactions[END_REF]). We also found three genes interacting with ubiquitin (ACYPI086543 and ACYPI005897 near outlier T_110814_1, and ACYPI47822 near outlier D_114374_2), a function often found in salivary proteins (e.g. [START_REF] Bos | A functional genomics approach identifies candidate effectors from the aphid species Myzus persicae (green peach aphid)[END_REF][START_REF] Carolan | Predicted effector molecules in the salivary secretome of the pea aphid (Acyrthosiphon pisum): a dual transcriptomic/proteomic approach[END_REF]. Hypothetical functions of other genes located at less than 30 kb from outliers include protein binding, regulator of transcription, oxydo-reduction process amongst other functions, with no obvious role in host plant adaptation (Table S4, Supporting information).

Genomic architecture of host plant adaptation

The 11 outlier loci were located on 11 distinct scaffolds, five of which also containing some nonoutlier microsatellite loci (Table 3). The physical distance between outliers and these neighbouring markers ranged from 49 to 1067 kb. Only one locus, located at 49.8 kb from the outlier locus T_112827_1, showed high genetic divergence between host races (F CT = 0.30) and was identified as an outlier at the a = 0.05 significance threshold in our analyses with ARLEQUIN 3.5. By contrast, two loci located at approximately 170 kb from outliers showed extremely low F CT values (Table 3). In spite of the physical proximity between these loci based on the V2 genome assembly, we found no significant linkage disequilibrium between outlier loci and the neighbouring markers, except for outlier D_121300_2 and one of its neighbour (D_126141_4) distant from 1067 kb (Table 3).

Discussion

Genomic structure of pea aphid populations

Our population genetic analyses based on an extensive set of microsatellite loci revealed a strong genetic structure by the host plant all along the nuclear genome of the pea aphid. Contrastingly, the impact of geography within a host race was negligible although the sampled populations were separated by 100-200 km. Among the three host races studied here, the pea host race was the most differentiated, as already shown with a much smaller set of loci [START_REF] Frantz | Ecological specialization correlates with genotypic differentiation in sympatric host-populations of the pea aphid[END_REF]Peccoud et al. 2009a).

The red clover and alfalfa host races were less divergent from each other. The pea adapted race might have diverged before the two other races started to, although this is not supported by sequence data of the maternally inherited aphid endosymbiont Buchnera aphidicola (Peccoud et al. 2009b). This pattern of differentiation could also be due to a stronger reproductive isolation, whether pre-and/or postzygotic, in the pea race. Migrants from other races are, indeed, very rare on pea, and this race shows very few hybrids in field populations (~3%), against 4 to 9% for other races within the A. pisum complex (Peccoud et al. 2009a). The pea race also differed from the other two by a lower genetic diversity, an absence of within-race genetic structure and an excess of heterozygotes. The pea-adapted race uses annual pea and annual vetches as alternative hosts, which are both unstable resources that might cause strong fluctuations in aphid population sizes. This may explain the reduced genetic diversity and the negative F IS (possibly because of low founding numbers of males and females) within the pea race populations. Instable resources might favour greater dispersal abilities compared to clover and alfalfa races as these two feed on perennial plants [START_REF] Frantz | Complex trait differentiation between host-populations of the pea aphid Acyrthosiphon pisum (Harris): implications for the evolution of ecological specialisation[END_REF][START_REF] Frantz | Host races of the pea aphid Acyrthosiphon pisum differ in male wing phenotypes[END_REF]. Lower constraints on dispersal in clover and alfalfa host plants would account for the greater geographical differentiation between populations adapted to these plants and might favour local inbreeding, resulting in the observed homozygote excess observed in some populations of the clover race. Interestingly, the genomic environment of our microsatellite loci affected both genetic diversity and structure of pea aphid populations. After correcting for the number of repeats, which is known to influence diversity (e.g. Ellegren 2000), we found a lower diversity and an increased genetic differentiation for microsatellite loci located in genomic regions with high gene density than for those located in regions with low gene density. These patterns are expected under genetic hitchhiking, with a reduction of diversity in the vicinity of the genomic regions targeted by selection, along with an increased divergence between environments selecting for different optima [START_REF] Maynard-Smith | Hitch-hiking effect of a favorable gene[END_REF][START_REF] Barton | Genetic hitchhiking[END_REF].

Genomic regions under divergent selection

Our genome scan approach identified 11 outlier loci (at the a = 0.01 threshold) when the hierarchical analysis was performed on the three races simultaneously. Hierarchical analyses performed between pairs of host races also supported these outliers. Whether the outlier locus EQ118272_44 is influenced by the host plant or local (geographical) effects remains unclear, a fortiori as this locus is far from any predicted gene. All 11 outliers were characterized by a high heterozygosity, and there are two reasons for this pattern. First, heterozygozity is estimated overall populations in ARLE-QUIN analyses, so the larger the divergence among populations, the higher overall heterozygosity can reach. Second, the power to detect outliers increases with increasing variance in allelic frequencies. Note that similar results have been reported in earlier works (e.g. Fig. 1 in [START_REF] Beaumont | Evaluating loci for use in the genetic analysis of population structure[END_REF][START_REF] Smadja | Large-scale candidate gene scan reveals the role of chemoreceptor genes in host plant specialisation and speciation in the pea aphid[END_REF].

We showed that both outlier loci and nonoutlier loci were more structured by the host plant (outliers: F CT = 0.40, nonoutliers: F CT = 0.12) than by the geography (outliers: F SC = 0.02, nonoutliers: F SC = 0.01, Fig. S4, Supporting information). If the populations sampled from the same host plant derived from the same specialization event, we would then expect these populations to cluster together in analyses based on nonoutlier loci. Conversely, if the populations sampled from the same host plant derived from independent and/or recurrent specialization events (i.e. parallel adaptation), we would then expect some populations at least to cluster into geographic groups (see, for example, [START_REF] Colosimo | Widespread parallel evolution in sticklebacks by repeated fixation of ectodysplasin alleles[END_REF]. Our results support the hypothesis that adaptation to each host plant occurred once in the populations studied here, as A. pisum populations cluster together into host plant groups and not into geographic groups. Similar results were previously documented at larger geographical scales [START_REF] Peccoud | Host range expansion of an introduced insect pest through multiple colonizations of specialized clones[END_REF](Peccoud et al. , 2009a;;[START_REF] Ferrari | Population genetic structure and secondary symbionts in host-associated populations of the pea aphid complex[END_REF]. The pea aphid complex, thus, differs from the well-documented case of parallel adaptation in sticklebacks [START_REF] Colosimo | Widespread parallel evolution in sticklebacks by repeated fixation of ectodysplasin alleles[END_REF][START_REF] Hohenlohe | Population genomics of parallel adaptation in threespine stickleback using sequenced RAD tags[END_REF], presumably because aphids have strong dispersal abilities [START_REF] Loxdale | The relative importance of short-range and longrange movement of flying aphids[END_REF][START_REF] Margaritopoulos | Tracking the global dispersal of a cosmopolitan insect pest, the peach potato aphid[END_REF].

The large genetic differentiation found here between the three host races of A. pisum at both outlier and nonoutlier loci contrasts with the results of [START_REF] Via | The genetic mosaic suggests a new role for hitchhiking in ecological speciation[END_REF], showing that American pea aphid populations adapted to red clover and alfalfa were not structured (neither geographically nor by their hosts) at nonoutlier loci. The most probable explanation for these opposing results relies on how outlier and nonoutlier loci were defined here and in [START_REF] Via | The genetic mosaic suggests a new role for hitchhiking in ecological speciation[END_REF]. The latter authors combined a QTL map for plant specialization [START_REF] Hawthorne | Genetic linkage of ecological specialization and reproductive isolation in pea aphids[END_REF] with data on genetic structure between two host races on mapped loci. They showed that the QTLs affected genetic markers located up to 20-30 cM far (as differentiation was on average higher at these loci). They identified only five AFLP markers (of 45) that did not hitchhike with the QTLs and estimated genetic structure between host races with these five markers. Contrastingly, here, we identified loci as outlier only if they were highly significant with ARLEQUIN 3.5 (a = 0.01), and all remaining loci were grouped in the nonoutlier class. If, as suggested by [START_REF] Via | The genetic mosaic suggests a new role for hitchhiking in ecological speciation[END_REF], most markers are affected by QTLs controlling host plant specialization, this could explain why we observe an important genetic structure even on the loci that we classified as nonoutliers (see STRUCTURE and AMOVA's results). Thus, we are currently unable to resolve whether the large effect of the host plant on A. pisum genetic structure on both the outlier and the nonoutlier groups of loci results from drift at neutral loci as a consequence of adaptive divergence, or from hitchhiking of large genomic portions with selected genes because of low recombination in some genomic regions. Having a high-quality genetic map in the pea aphid would certainly help discriminating between these hypotheses, as they predict different distributions of F ST values for nonoutlier loci across the chromosomes. Under drift at neutral loci resulting from adaptive divergence, we expect a random distribution of F ST values from the nonoutlier group of loci across chromosomes, while the latter hypothesis predicts an aggregated distribution of markers according to their F ST values, with only a few genomic areas (those far from any QTL) showing low differentiation between host races. Whether the outliers we identified (that each belongs to a different scaffold) map to the genomic regions identified through the QTL analysis of host acceptance and performance by [START_REF] Hawthorne | Genetic linkage of ecological specialization and reproductive isolation in pea aphids[END_REF] remains an open question, as basic information about the molecular markers used in their study was not provided.

Here, we chose many markers close to expressed genes and focused on outliers detected using a stringent threshold to increase the probability to target genomic regions of adaptive significance. Hence, the frequency of outliers (11 of 390) might not reflect the frequency of randomly drawn markers. Furthermore, if there are large differences in the rate of recombination in different regions of the aphid genome, in particular if strong hitchhiking effects occur in some genomic areas, this could lead to a biased estimation of the frequency of outliers. We also acknowledge that the number of markers used here is still low compared with the genome size of the pea aphid (530 Mb, IAGC 2010) and that we have probably only picked out a small part of the genomic regions (or genes) involved in host plant specialization.

Candidate genes involved in plant adaptation

The majority of the genes located at less than 30 kb of the outlier loci have unknown functions and showed no homology with genes from other model organisms. However, a few genes with functions likely to be involved in plant specialization were at 30 kb or less from several of the 11 outlier microsatellites, suggesting that this arbitrarily chosen threshold was reasonable. In particular, two outliers were located in the vicinity of three genes recently identified as encoding secreted proteins from the salivary glands of the pea aphid and the green peach aphid [START_REF] Carolan | Predicted effector molecules in the salivary secretome of the pea aphid (Acyrthosiphon pisum): a dual transcriptomic/proteomic approach[END_REF]. A third outlier was close to a cadherin gene, which encodes calciumbinding proteins and which has a copy encoding secreted salivary proteins in the pea aphid [START_REF] Carolan | Predicted effector molecules in the salivary secretome of the pea aphid (Acyrthosiphon pisum): a dual transcriptomic/proteomic approach[END_REF]. Salivary proteins are important effectors of aphid-plant interactions, which can suppress actively plant defences [START_REF] Will | Molecular sabotage of plant defense by aphid saliva[END_REF][START_REF] Bos | A functional genomics approach identifies candidate effectors from the aphid species Myzus persicae (green peach aphid)[END_REF][START_REF] Hogenhout | Effector proteins that modulate plant-insect interactions[END_REF]. In particular, calcium-binding proteins secreted by salivary glands, and which are injected into the sieve tube following insertion of aphid stylets, can counteract plant defences by clogging of sieve elements and callose formation [START_REF] Will | Molecular sabotage of plant defense by aphid saliva[END_REF]). The fact that three of the genes previously identified by [START_REF] Carolan | Predicted effector molecules in the salivary secretome of the pea aphid (Acyrthosiphon pisum): a dual transcriptomic/proteomic approach[END_REF] and [START_REF] Bos | A functional genomics approach identifies candidate effectors from the aphid species Myzus persicae (green peach aphid)[END_REF] locate close to two of our outliers and that we also identified a cadherin gene close to a third outlier strongly suggests that these salivary proteins play a role in plant use by the different host races.

We identified two other outliers close to chemosensory genes Or12 and Or22 (at 6.7 kb and 0.7 kb, respectively) and showed that this gene function was not significantly enriched in the outlier category. Our results differ from a recent study by [START_REF] Smadja | Large-scale candidate gene scan reveals the role of chemoreceptor genes in host plant specialisation and speciation in the pea aphid[END_REF], based on sequence data from populations of eight individuals each, which suggested that Or12 and Or22 did not evolve under divergent selection in A. pisum host races collected in UK on red clover, alfalfa and lotus (Lotus pedunculatus). Conversely, seven of our microsatellite loci were located in the vicinity (<14 kb) of four of the 19 chemosensory genes identified as outliers by [START_REF] Smadja | Large-scale candidate gene scan reveals the role of chemoreceptor genes in host plant specialisation and speciation in the pea aphid[END_REF] (d_127119_2 and T_127119_1: 0.5kb and 11.5 kb from Gr8, D_119783_3: 10.5 kb from Or15, t_125317_2 and D_112775_1: 9.5 kb and 13.6kb from Or29, D_128051_6 and 10114: 2.5 kb and 3.1kb from Or36), but none of these microsatellite loci were identified as outlier in the present study. The differences between our results and those in [START_REF] Smadja | Large-scale candidate gene scan reveals the role of chemoreceptor genes in host plant specialisation and speciation in the pea aphid[END_REF] may have several causes. First, the two studies compared different sets of host races, and it is possible that different chemosensory genes are involved in host plant specialization in the different host races. Second, genomic differentiation along chromosomes is noisy (e.g. [START_REF] Weir | Measures of human population structure show heterogeneity among genomic regions[END_REF][START_REF] Cao | Whole-genome sequencing of multiple Arabidopsis thaliana populations[END_REF][START_REF] Nadeau | Genomic islands of divergence in hybridizing Heliconius butterflies identified by large-scale targeted sequencing[END_REF], so that differentiation observed at a particular locus might not reflect that of neighbouring loci. Third, our microsatellite loci are possibly too far from chemosensory genes identified as under divergent selection by [START_REF] Smadja | Large-scale candidate gene scan reveals the role of chemoreceptor genes in host plant specialisation and speciation in the pea aphid[END_REF] to be influenced by hitchhiking effect. This hypothesis nevertheless contradicts results of [START_REF] Via | The genetic mosaic suggests a new role for hitchhiking in ecological speciation[END_REF], suggesting that neutral markers are influenced by host-specialization QTL over large distance. Furthermore, two of our microsatellite loci were close from Gr8 and Or36 (0.5 and 2.5 kb), so they would have hitchhiked if these genes had undergone strong directional selection. Fourth, [START_REF] Smadja | Large-scale candidate gene scan reveals the role of chemoreceptor genes in host plant specialisation and speciation in the pea aphid[END_REF] analysed eight individuals from a single population. Estimating genetic structure with less than 15 diploid individuals is not recommended, as allelic frequencies might be poorly estimated [START_REF] Kalinowski | Do polymorphic loci require large sample sizes to estimate genetic distances?[END_REF].

Conclusion

By scanning the genome of multiple pea aphids adapted to distinct host plants, we confirmed the primary influence of plant specialization on overall genetic differentiation. Considering that the adaptive radiation in the pea aphid complex is recent (Peccoud et al. 2009b), our results suggest a rapid genome-wide divergence promoted by ecological factors and reproductive barriers between host-adapted races. Our approach also allowed identifying with a strong statistical support a handful of loci under divergent selection. Whether differentiation among host races at nonoutlier loci results from drift as a consequence of adaptive divergence or from extensive genetic hitchhiking remains to be investigated. Nearly half of the outliers we identified were close to the genes of biological relevance in the context of molecular plantaphid interactions. This is an encouraging result for further studies on population and functional genomics of plant adaptation and ecological speciation in the pea aphid complex, but more generally for the discovery of candidate genes controlling adaptive traits.

There is now a need to improve our knowledge about the physical organization of the pea aphid genome to localize the outlier loci as well as to characterize the extent of genomic hitchhiking, in particular in relation to the recombination rate of different genomic regions. Investigating the occurrence of chromosomal rearrangements among host races is also highly relevant, as this could account for the high diversification rate observed in the pea aphid complex. Finally, functional studies on the candidate genes identified here and in the related work of [START_REF] Smadja | Large-scale candidate gene scan reveals the role of chemoreceptor genes in host plant specialisation and speciation in the pea aphid[END_REF] are required to determine their role in plant use by pea aphid races.

This works represents a contribution to the understanding of trophic adaptation in herbivores from an evolutionary and genetic perspective. J.J., S.S. and R.V. are population geneticists interested in evolutionary biology. P.N. participated to different steps of this study and is currently doing a PhD thesis on the genetics of plant adaptation in the pea aphid under the supervision of J.C.S. and S.S. N.B. and A. B. contributed to data acquisition and analysis. L. M. and F.M. are experts in highthroughput genotyping technologies. F. L. is a bioinformatician focusing on insect genomics, genome assembly and genomic analyses. J.C.S. is a scientist with long-standing interest in the evolution of complex life-history traits, using aphids as model systems.

Data accessibility

Microsatellite genotypes and sampling information are deposited in DRYAD along with input files for running Arlequin and Structure softwares (doi:10.5061/dryad. pf5cg).

Supporting information

Additional Supporting Information may be found in the online version of this article. Table S1 Origin of populations used (M. sativa: alfalfa, T. pratense: red clover, P. sativum: pea). S = Switzerland, M = Mirecourt, R = Ranspach.

Table S2 Microsatellite loci used.

Table S3 Identification of outlier loci with the hierarchical method implemented in ARLEQUIN 3.5 [START_REF] Excoffier | Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows[END_REF].

Table S4 Putative functions of the predicted genes located in a 60-kb windows centered on the outlier microsatellite loci (detected with ARLEQUIN 3.5) on the V2 genome assembly (IAGC 2010; [START_REF] Legeai | AphidBase: a centralized bioinformatic resource for annotation of the pea aphid genome[END_REF].

Please note: Wiley-Blackwell are not responsible for the content or functionality of any supporting materials supplied by the authors. Any queries (other than missing material) should be directed to the corresponding author for the article.

© 2012 Blackwell Publishing Ltd

Fig. 1

 1 Fig. 1 Clustering of pea aphids by STRUCTURE analyses for K = 3 clusters (panel A). Each individual is represented by a vertical line, divided into up to K = 3 coloured segments representing the individual's ancestry to each cluster. Panel B: genetic substructure of each of the three clusters identified in A) (with K = 3 for each). Host plants and localities are respectively labelled on the top and bottom of the figure (M = Mirecourt, R = Ranspach, S = Switzerland).

  Fig.2Effects of the number of microsatellite repeats (panel A) and of the genomic environment of the microsatellite loci (panels B and C) on the genetic differentiation (F ST ) tested with Pearson's correlations. Loci identified as significant outliers at a < 0.01 with ARLEQUIN 3.5 are shown in black.

  Microsatellite loci physically linked to outlier loci from the V2 genome assembly of the pea aphid. Genetic differentiation between host races (F CT , estimated with ARLE-QUIN 3.5 in a hierarchical model where geographical populations are nested within the three host races), the ranking of the loci based on this value (1 = most differentiated locus, 390 = less differentiated locus) and the significance level as outlier are shown. Correlations between allelic frequencies between focal outliers and linked loci (and significance)

Fig. S1

 S1 Fig. S1 Description of the different steps for selecting the individuals used for extensive genotyping in each of the nine populations sampled.

Fig. S2

 S2 Fig. S2 Pairwise F ST estimates for populations and host races of the pea aphid and computed across 390 microsatellite markers.

Fig. S3

 S3 Fig.S3Effects of the number of microsatellite repeats (panel A) and of the genomic environment of the microsatellite loci (panels B and C) on residuals of allelic richness from linear-mixed effects models.

Fig. S4

 S4 Fig.S4Clustering of pea aphids by STRUCTURE analyses for K = 3 clusters.

Table 1 Genetic diversity at 390 microsatellite loci calculated within populations of the pea aphid Acyrthosiphon pisum collected on alfalfa, pea and red clover. N, sample size; H e

 1

	,

Table 3

 3

© 2012 Blackwell Publishing Ltd

Acknowledgements

We thank L. Buechi, A. Juilland, G. Evanno, Y. Outreman, the Jaquie ´ry and Evanno families for help with sampling and J. Bonhomme for rearing aphids. J. Peccoud, L. Orsini, and three anonymous referees contributed constructive comments on a previous draft of this manuscript. This work was supported by INRA-AIP BioRessources, the De ´partement INRA Sante ´des Plantes et Environnement, the Fondation pour la Recherche sur la Biodiversite ´, the ANR GW-Aphid, the ANR Speciaphid and the Swiss National Science Foundation (grants number PBLAA-122658 and PA00P3_139720 to J.J).