La génétique, et par extension le séquençage de l’ADN, sont des outils qui ont transformé la compréhension des mécanismes impliqués dans la survenue de nombreuses pathologies, dont l’obésité. Les technologies aujourd’hui à notre disposition nous permettent de déterminer rapidement si un patient est ou non porteur d’un évènement génétique pouvant expliquer sa pathologie. L’une des techniques les plus utilisées en diagnostic aujourd’hui est le séquençage d’exome, ou WES, qui permet une excellente détection des mutations ponctuelles dans les régions codantes du génome. Mais d’autres évènements comme les copy number variants, ou CNV, peuvent également expliquer certaines pathologies, dont l’obésité, via entre autres les CNV de la région 16p11.2. Actuellement, la technique de référence pour la détection de ces copy number variants est l’analyse de puces CGH (Comparative Genomic Hybridization), mais celles-ci ne permettent pas de détecter des mutations non répertoriées au préalable lors de la création de la puce. Sur le principe, le séquençage d’exome peut lui aussi être utilisé pour détecter les CNV, mais son absence de couverture des régions non codantes du génome ne permet pas une détection efficace de ces CNV, car ceux-ci peuvent survenir sur l’ensemble du génome, en englobant des régions codantes et non codantes au sein d’un seul évènement. Le séquençage génome complet peut détecter ces deux types d’évènement, mais son cout est encore élevé ce qui freine sa démocratisation, et l’analyse de données associées nécessite d’importantes ressources informatiques, et le rend difficilement utilisable en diagnostic de routine en l’état actuel des choses. Il est donc pour l’instant nécessaire d’avoir recours à deux techniques différentes pour couvrir ces deux types d’évènements génétiques. Cela implique d’utiliser des échantillons parfois très précieux à deux reprises, de supporter les couts liés à deux techniques diagnostiques (d’environ 450 euros pour le séquençage d’exome au laboratoire et un cout un peu plus élevé pour une puce à ADN dans un laboratoire clinique), et d’allonger les temps de rendu de résultats et donc la durée d’établissement du diagnostic du patient. Cet état de fait nous a conduit à développer une technique de séquençage, que nous avons nommé CoDE-seq (Copy number variation Detection and Exome sequencing), et qui permettra la détection simultanée de ces deux types d’évènements, pour diminuer les temps d’établissement de diagnostics, leurs couts, et la quantité d’échantillon nécessaire. Ce travail a nécessité deux aspects : la mise au point technique et la mise au point analytique. La mise au point technique est passée par la création d’une nouvelle « capture », permettant une détection correcte des mutations ponctuelles de l’exome et des CNV de tout le génome. La mise au point analytique a consisté à définir la méthode à employer, et à permettre d’arriver à une détection fiable, à la fois sensible et spécifique, des CNV sur l’ensemble du génome. Une fois ces CNV identifiés, la question de leur signification fonctionnelle se pose également, et une seconde partie de ma thèse porte sur l’étude de cette signification fonctionnelle, via l’étude de la conformation spaciale de la chromatine et de l’influence des CNV sur celle-ci. / Genetics, and by extention DNA sequencing, are tools that have modified the understanding of the mechanisms involved in genetic diseases, like obesity. Today’s technology has allowed us to rapidly find if a patient carries a genetic event that may explain his/her pathology. One of the most used technology for diagnostic is exome sequencing, or WES, which enables an excellent detection of point mutations in coding regions of the genome. However other events, such as copy number variations, or CNV, can also explain some pathologies, like a severe form of obesity due to CNV in the chr16p11.2 region. Actually, the gold standard method for an accurate detection of CNV is array CGH, but this technology cannot detect new point mutations. Exome sequencing can be used to detect CNV, but the lack of coverage in non-coding regions limits CNV detection sensitivity. Of note, whole genome sequencing can detect both CNVs and point mutations, but it is still very expensive and needs huge informatics capacities, which is an obvious limitation for a routine diagnostic use.For now, we have had to use two different methods in order to accurately detect both CNVs and point mutations. In other words, we have had to use precious samples two times, to assume the cost of two different methods (which is nearly 450 euros in the laboratory for exome sequencing, and a bit more for array CGH in a clinical laboratory), and to consider the time of the realization of two different methods in order to achieve a complete diagnostic.In this context, we aimed to develop an innovative sequencing method, named CoDE-seq (Copy number variation Detection and Exome sequencing), which would allow us to simultaneously detect both CNVs and point mutations, in order to reduce the time of diagnostic, the cost, and the needed quantity of sample.This work included the method conception, and the data analysis steps. The method conception has been done through the creation of a new capture enabling the detection of point mutations in the exome, and CNVs all along the genome. Furthermore, the data analysis step included the choice of the bioinformatics methods to be used, in order to get a specific and sensitive CNV detection, all along the genome.We were also interested in the fonctional significance of identified CNV, and tried to decipher it by the study of chromatine spacial conformation and the influence of these CNV.

Obesity prevalence continues to increase worldwide, yet few safe and effective treatment options are available suggesting there needs to be a greater emphasis on preventing rather than treating obesity. This research investigated the association of obesity predisposing SNPs and a gene score with nutrient consumption patterns including total energy intake and macronutrient distribution in a European ancestry population as well as discussing an evolutionary perspective on eating disorders using current epidemiological evidence to identify genes which may be involved. The association of two of the 14 obesity predisposing SNPs and the gene score with BMI was confirmed in the EpiDREAM population. Novel associations between two SNPs located in or near BDNF (rs6265 and rs1401635) were found with total fat, MUFA, and PUFA intake. Rs1401635 was also associated with total energy and trans fat intake. Novel associations of rs6235 (PCSK1) and the gene score were found with total energy intake. The novel associations found indicate that food related behaviours are one of the mechanisms of action through which obesity predisposing SNPs cause obesity and therefore warrant further investigation. The lack of association among all genes and the modest association of the gene score show that mechanisms other than food consumption are important. The investigation of the evolutionary history of eating disorders revealed that the adapted to flee famine hypothesis is a plausible theory explaining anorexia nervosa while the thrifty genotype hypothesis provides a possible explanation for bulimia nervosa and binge eating disorder. These evolutionary theories can be applied to identify new candidate genes as well as phenotypic traits to investigate to better understand the genetic architecture of eating disorders. Understanding genes associated with disordered eating patterns may highlight future areas for obesity prevention. / Thesis / Master of Science (MSc) / A large percentage of the risk of developing obesity or an eating disorder (anorexia nervosa, bulimia nervosa, and binge eating disorder) is determined by genetics. For obesity, many genes have been identified as influencing risk, but the mechanisms through which the genes work are largely unknown. For eating disorders, gene identification efforts have been mostly unsuccessful and no mechanisms of action have been determined. In the first component of this thesis we found an association between previously identified obesity risk genes and food intake, specifically the total number of calories consumed per day and the percentage of calories from total fat and fat subtypes. These results support that food related behaviours are possible mechanisms of action which need to be further investigated. In the second half of the thesis we viewed eating disorder behaviours from an evolutionary perspective. We concluded that there are theories that possibly explain eating disorder behaviours including being able to live off of small quantities of food as well as binging. These evolutionary theories can be applied to identify new genes to study in the context of eating disorders as well as different definitions of eating disorders.