No description available.

Seleção balanceadora é definida como aquela que aumenta a variabilidade genética de populações em relação ao esperado sob neutralidade. Uma expectativa sobre seus efeitos é a redução da diferenciação populacional nos genes onde atua. Contudo, regimes que mantêm conjuntos distintos de alelos em diferentes populações poderiam resultar em aumento de diferenciação populacional. Com o objetivo de compreender melhor os efeitos da seleção balanceadora sobre a distribuição da variação genética entre populações, investigamos a diferenciação populacional em genes dos Antígenos Leucocitários Humanos (HLA, do inglês, Human Leukocyte Antigen), que são os genes mais polimórficos do genoma humano e o exemplo mais clássico de seleção balanceadora em humanos. As proteínas HLA são responsáveis pela apresentação de peptídeos aos linfócitos T, mediando uma etapa crítica da resposta imune. A vantagem da manutenção de variação nesses genes está possivelmente associada à capacidade de resposta a uma maior diversidade de patógenos. Neste estudo, analisamos dados do projeto 1000 Genomas (1000G), que sequenciou indivíduos de diferentes populações usando sequenciamento de nova geração (NGS, do inglês, Next Generation Sequencing). Essa técnica de sequenciamento é conhecidamente problemática quando aplicada a regiões altamente polimórficas, como os genes HLA. Por isso, avaliamos a confiabilidade dos genótipos e frequências alélicas estimados a partir dos dados do 1000G nos genes HLA, utilizando como padrão ouro dados de sequenciamento Sanger de 930 das 1092 amostras do 1000G. Encontramos um viés de superestimativa da frequência do alelo referência em alguns polimorfismos de nucleotídeo único (SNPs, do inglês, Single Nucleotide Polimorphisms), indicando que viés de mapeamento é uma causa importante de erros nos dados do 1000G. Esses resultados são relevantes para a compreensão dos desafios do uso de dados de NGS em outras regiões de alta diversidade. Usando os resultados dessa análise, excluímos de nosso estudo de diferenciação populacional sítios com estimativas de frequências alélicas pouco confiáveis nos dados do 1000G. Em uma segunda etapa de controle metodológico, demonstramos o efeito do uso de dados ricos em variantes raras em estudos de diferenciação populacional. Controlando para esse efeito, e usando apenas sítios que demonstramos ser confiáveis em nossos dados, descobrimos que a diferenciação populacional de SNPs nos genes HLA é menor que a diferenciação de SNPs em outras regiões do genoma. Esse resultado aponta para um papel predominante de pressões seletivas globais na distribuição da variação genética de HLA entre populações. Contudo, apresentamos também evidências de que a diferenciação populacional de haplótipos nos genes HLA pode ser maior do que a observada no nível dos SNPs, sugerindo que pressões locais podem influenciar a distribuição de haplótipos entre populações. Nossos achados indicam que é possível reconciliar baixa diferenciação populacional em SNPs com maior diferenciação em haplótipos, possivelmente sujeitos a pressões seletivas locais. / Balancing selection is defined as any kind of selective regime that increases genetic variability in populations relative to what is expected under neutrality. Theory predicts that balancing selection reduces population differentiation. However, balancing selection regimes in which different sets of alleles are maintained in different populations could increase population differentiation. To better understand the effects of balancing selection on the distribution of genetic variation among populations, we investigated population differentiation at the Human Leukocyte Antigen (HLA) genes, which are the most polymorphic genes in the human genome, and constitute the most striking example of balancing selection in humans. The HLA molecules are responsible for the presentation of peptides to T cells, thus mediating a critical step of the immune response. The advantage of maintaining variation in those genes through balancing selection is possibly related to the increased ability of the immune system to respond to a wider variety of pathogens. In this study, we analysed the public dataset of the 1000 Genomes project (1000G), which sequenced 1092 individuals from different populations using Next Generation Sequencing (NGS) technologies. These sequencing techniques are known to be problematic when applied to highly polymorphic genomic regions, such as the HLA genes. Therefore, we evaluated the reliability of genotype calls and allele frequency estimates of the SNPs reported by 1000G at HLA genes, using Sanger sequencing data of 930 of the 1092 1000G samples as a gold standard. We found a bias towards overestimation of reference allele frequency for some single nucleotide polymorphisms (SNPs), indicating mapping bias is an important cause of error in frequency estimation in the 1000G data. These results provide insights into the challenges of using of NGS data at other genomic regions of high diversity. Using the results of this analysis, we selected a list of sites that have reliable allele frequency estimates in the 1000G data to be used in our population differentiation study. In another methodological control, we demonstrate the effect of using a dataset rich in rare variants in population differentiation studies. Controlling for this effect, and using only the sites which we demonstrated that were reliable, we found that population differentiation of single nucleotide polymorphisms (SNPs) at the HLA genes is lower than that of SNPs in other genomic regions. This suggests a predominant role of global selective pressures in shaping the distribution of variation at the HLA genes among populations. However, we also show evidence that population differentiation of HLA haplotypes may be higher than what we observe at the SNP level, suggesting that local selective pressures may influence the distribution of haplotypes among populations. Altogether, our results indicate that it is possible to reconcile low population differentiation at the SNP level - as predicted by theory - to higher differentiation at haplotypes, which are possibly under local selective pressures.

Dans le cadre de cette thèse nous nous sommes intéressés à l'étude de l'évolution et de la variabilité génétique de la famille des butyrophilines (BTN), des récepteurs de la superfamille des immunoglobulines impliqués dans la régulation de la réponse immunitaire. Par une étude phylogénétique approfondie nous avons caractérisé chez les mammifères 14 groupes phylogénétiques résultant d'une série de duplications à partir de huit gènes ancestraux à la base des thériens. Par la suite, nous avons étudié l'évolution des BTN de la région CMH chez les primates et leur variabilité génétique dans les populations humaines par une analyse minutieuse des données de séquençage générées du projet 1000 Genomes pour plus de 1600 individus à travers le monde. Nous avons montré que l'évolution du gène BTNL2 est marquée par une pression de sélection positive diversifiante chez les mammifères qui est accompagnée chez les hominoïdes d'un niveau de polymorphisme élevé induisant la formation de variants tronqués de BTNL2. Chez l'homme, quatre lignages d'allèles ont été identifiés. Ils ont été maintenus à des fréquences intermédiaires par une forte sélection balancée. D'autre part, l'analyse phylogénétique détaillée du groupe BTN3 (BTN3A1, 3A2 et 3A3) a montré la présence d'une évolution concertée, caractérisée par une homogénéisation forte et récurrente de la région codant pour le peptide signale et le domaine IgV chez les hominoïdes, au cours de laquelle les séquences de 3A1 et 3A3 sont remplacées par la séquence de 3A2. Chez l'homme, ces gènes sont polymorphismes important avec plus de 46 allèles chacun, mais avec la présence d'une homogénéisation extrême des séquences du domaine IgV / In this thesis we were interested in studying the evolution and the genetic variability of the butyrophilin family (BTN), a family of immune receptors belonging to the immunoglobulin superfamily implicated in the regulation of immune response. Through a thorough phylogenetic study of the family we characterized 14 phylogenetic groups in mammals resulting from a series of duplications from eight ancestral genes at the base of therian. Thereafter, we studied the evolution of the BTN of the MHC region and their genetic variability in human populations by a careful analysis of sequencing data generated by the consortium 1000 Genomes for more than 1,600 individuals representing 26 populations worldwide. We have shown that the evolution of BTNL2 gene is marked by a positive diversifying selection in placental mammals. This selection pressure is accompanied in hominoids of a high level of polymorphism inducing the formation of truncated BTNL2 variants. In humans this high level of polymorphism results in the presence of four ancient allele lineages that are maintained at intermediate frequencies by a strong balancing selection. On the other hand, a detailed phylogenetic analysis of BTN3 group (BTN3A1, 3A2 and 3A3) showed that these genes evolve in hominoids in a concerted manner characterized by a strong and recurrent homogenization of the regions encoding for the peptide signal and the IgV domain in which the 3A1 and 3A3 sequences are replaced by the 3A2 sequence. In humans these genes are polymorphic with over 46 alleles each, but with the presence of extreme homogenization of IgV domain sequences

Thesis advisor: Gabor T. Marth / During the last few years, numerous new sequencing technologies have emerged that require tools that can process large amounts of read data quickly and accurately. Regardless of the downstream methods used, reference-guided aligners are at the heart of all next-generation analysis studies. I have developed a general reference-guided aligner, MOSAIK, to support all current sequencing technologies (Roche 454, Illumina, Applied Biosystems SOLiD, Helicos, and Sanger capillary). The calibrated alignment qualities calculated by MOSAIK allow the user to fine-tune the alignment accuracy for a given study. MOSAIK is a highly configurable and easy-to-use suite of alignment tools that is used in hundreds of labs worldwide. MOSAIK is an integral part of our genetic variant discovery pipeline. From SNP and short-INDEL discovery to structural variation discovery, alignment accuracy is an essential requirement and enables our downstream analyses to provide accurate calls. In this thesis, I present three major studies that were formative during the development of MOSAIK and our analysis pipeline. In addition, I present a novel algorithm that identifies mobile element insertions (non-LTR retrotransposons) in the human genome using split-read alignments in MOSAIK. This algorithm has a low false discovery rate (4.4 %) and enabled our group to be the first to determine the number of mobile elements that differentially occur between any two individuals. / Thesis (PhD) — Boston College, 2010. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Biology.

No description available.

No description available.

Tous les individus ne répondent pas de la même façon à un même traitement médicamenteux, tant sur le plan pharmacologique (efficacité) que sur le plan toxicologique (effets indésirables). Des facteurs génétiques affectant la pharmacocinétique et la pharmacodynamie des médicaments jouent un rôle déterminant dans cette variabilité interindividuelle de réponse. Certains de ces facteurs sont distribués de manière hétérogène entre les populations humaines. Ces différences s’expliquent en partie par des phénomènes d’adaptation locale des populations à leur environnement. Au cours de son histoire, l’homme a dû en effet faire face à des changements de son environnement chimique, qui ont entraîné des pressions de sélection naturelle sur les gènes intervenant dans la réponse de l’organisme aux xénobiotiques. Ce sont ces mêmes gènes qui, aujourd’hui, influencent la réponse aux médicaments.La formidable accélération des progrès de la génétique donne accès aujourd’hui à la variabilité génétique des populations humaines sur l’ensemble du génome, facilitant la découverte et la compréhension des mécanismes génétiques à l’origine des traits complexes comme la réponse aux médicaments. Les outils de la génétique des populations permettent notamment d’identifier des variants affichant un niveau de différenciation génétique inhabituel entre les populations humaines et de déterminer dans quelle mesure la sélection naturelle a joué un rôle dans les profils atypiques observés.Dans cette thèse, nous avons appliqué ces outils à des données de génotypage et de séquençage pour analyser les profils de différenciation génétique des populations humaines pour les gènes de la réponse aux médicaments. Nous avons ainsi démontré qu’une sélection positive récente en Asie de l’Est dans la région génomique du gène VKORC1 était responsable d’une hétérogénéité de distribution du variant fonctionnel de VKORC1, à l’origine des différences de sensibilité génétique aux anticoagulant oraux de type antivitamine K entre les populations humaines. Puis, en étendant notre analyse à l’ensemble des pharmacogènes majeurs, nous avons identifié de nouveaux variants potentiellement intéressants en pharmacogénétique pour expliquer les différences de réponse aux médicaments entre les populations humaines et les individus. Enfin, l’étude approfondie du gène NAT2 nous a permis de révéler un processus de sélection homogénéisante ciblant un variant fonctionnel associé à un phénotype d’acétylation très lent. Ces résultats soulignent l’influence déterminante de la sélection naturelle dans la variabilité de réponse aux médicaments entre les populations et les individus. Ils montrent l’apport de la génétique des populations pour une meilleure compréhension de la composante génétique de la réponse aux médicaments et des traits complexes. / Response to drug treatment can be highly variable between individuals, both in terms of therapeutic effect (efficacy) and of adverse reactions (toxicity).Genetic factors affecting drug pharmacodynamics and pharmacokinetics play a major role in this inter-individual variability. Some of these factors are heterogeneously distributed among human populations. Local adaptation of populations to their environment partly explained those differences. Indeed,during human evolution, populations had to cope with changes in their chemical environment that triggered selective pressures on genes involved in xenobiotic response. Those genes are the same ones that influence drug response today.The tremendous recent advances in genotyping and sequencing technologies now provide access to the genome-wide patterns of genetic variation in a growing number of human populations, facilitating our understanding of the genetic mechanisms underlying complex traits such as drug response. Population genetic tools allow the identification of variants showing an unusual pattern of genetic differentiation among human populations and the determination of the role played by natural selection in shaping the atypical patterns observed.In this thesis, we have applied these tools on both SNP-chip genotyping data and Next Generation Sequencing data to analyze the genetic differentiation patterns of human populations for genes involved in drug response. We show that a nearly complete selective sweep in East Asia in the genomic region of the VKORC1 gene is responsible for an heterogeneous distribution of theVKORC1 functional variant and can explain the inter-population genetic differences in response to oral anti-vitamin K anticoagulants. Extending the analysis to all major pharmacogenes, we have identified new variants of potential relevance to pharmacogenetics which could explain inter-population and inter-individual differences in drug response. Finally, by a comprehensive analysis of the NAT2 gene, we evidence a homogenizing selection process targeting a functional variant associated with a very slow acetylation phenotype. These results emphasize the crucial role of natural selection in the inter-population and inter-individual drug response variability.They also illustrate the relevance of population genetics studies for a better understanding of the genetic component underlying drug response and complex traits.

Ankylosing spondylitis (AS) is a common inflammatory arthritis of the spine and other affected joints, which is highly heritable, being strongly influenced by the HLA-B27 status, as well as hundreds of mostly unknown genetic variants of smaller effect. The aim of my research was to confirm some of the previously observed genetic associations and to identify new associations, many of which are in biological pathways relevant to AS pathogenesis, most notably the IL-23/T_H17 axis (IL23R) and antigen presentation (ERAP1 and ERAP2). Studies presented in this thesis include replication and refinement of several potential associations initially identified by earlier GWAS (WTCCC-TASC, 2007 and TASC, 2010). I conducted an extended study of IL23R association with AS and undertook a meta-analysis, confirming the association between AS and IL23R (non-synonymous SNP rs11209026, p=1.5 x 10-9, OR=0.61). An extensive re-sequencing and fine mapping project, including a meta-analysis, to replicate and refine the association of TNFRSF1A with AS was also undertaken; a novel variant in intron 6 was identified and a weak association with a low frequency variant, rs4149584 (p=0.01, OR=1.58), was detected. Somewhat stronger associations were seen with rs4149577 (p=0.002, OR=0.91) and rs4149578 (p=0.015, OR=1.14) in the meta-analysis. Associations at several additional loci had been identified by a more recent GWAS (WTCCC2-TASC, 2011). I used in silico techniques, including imputation using a denser panel of variants from the 1000 Genomes Project, conditional analysis and rare/low frequency variant analysis, to refine these associations. Imputation analysis (1782 cases/5167 controls) revealed novel associations with ERAP2 (rs4869313, p=7.3 x 10-8, OR=0.79) and several additional candidate loci including IL6R, UBE2L3 and 2p16.3. Ten SNPs were then directly typed in an independent sample (1804 cases/1848 controls) to replicate selected associations and to determine the imputation accuracy. I established that imputation using the 1000 Genomes Project pilot data was largely reliable, specifically for common variants (genotype concordence~97%). However, more accurate imputation of low frequency variants may require larger reference populations, like the most recent 1000 Genomes reference panels. The results of my research provide a better understanding of the complex genetics of AS, and help identify future targets for genetic and functional studies.