The regulation of gene expression at the right time, place, and degree is crucial for many cellular processes such as proliferation and development. In addition, in order to maintain cellular life, cells must rapidly and appropriately respond to various environmental stimuli. Sequence-specific transcription factors (TFs) can recognize functional regulatory DNA elements in a sequence-specific manner so that they can regulate only a specific group of genes, a process which enables cells to cope with diverse internal and external stimuli. Human has approximately 1,400 sequence-specific TFs whose aberrant expression causes a wide range of detrimental consequences including developmental disorders, diseases, and cancers; therefore, it is pivotal to identify the binding sites of each sequence-specific TF in order to unravel its roles in and mechanisms of gene regulation. Even though some TFs have been intensively studied, the majority of TFs still remain to be studied, particularly the tasks of identifying their genome-wide target genes and deciphering their biological roles in specific cellular contexts. Many questions remain unanswered: how many sites on the human genome a sequence-specific TF can bind; whether all TF-bound sites are functional; how a TF achieves binding specificity onto its targets; how and to what extent a TF is involved in gene regulation. Comprehensive identification of the binding sites of sequence-specific TFs and follow-up molecular studies including gene expression microarrays will provide close answers to these questions. Chromatin Immunoprecipitation coupled with recently developed high-throughput sequencing (ChIP-seq) allows us to perform genome-scale unbiased identification of the binding sites of sequence-specific TFs. Here, to gain insight into gene regulatory functions of TFs as well as their influences on gene expression, we conducted, in diverse cell lines, genome-wide identification of the binding sites of several sequence-specific TFs (CTCF, E2F4, MYC, Pol II) that are involved in a wide range of biological functions, including cell proliferation, development, apoptosis, genome stability, and DNA repair. Analysis of ChIP-seq data provided not only comprehensive binding profiles of those TF across the genome in diverse cell lines, but also revealed tissue-specific binding of CTCF, MYC, and Pol II as well as combinatorial usage among these three factors. Analyses also showed that some CTCF binding sites were inherited from parents to children and regulated in an individual-specific as well as allele-specific manner. Finally, genome-wide target identification of several TFs will broaden our understanding of the gene regulatory roles of these sequence-specific TFs. / text

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La maladie de Crohn (MC) et la colite ulcéreuse (CU) sont des maladies inflammatoires chroniques du tube digestif qu’on regroupe sous le terme maladies inflammatoires de l’intestin (MII). Les mécanismes moléculaires menant au développement des MII ne sont pas entièrement connus, mais des études génétiques et fonctionnelles ont permis de mettre en évidence des interactions entre des prédispositions génétiques et des facteurs environnementaux - notamment la flore intestinale – qui contribuent au développement d’une dérégulation de la réponse immunitaire menant à l’inflammation de la muqueuse intestinale. Des études d’association pangénomiques et ciblées ont permis d’identifier plusieurs gènes de susceptibilité aux MII mais les estimations de la contribution de ces gènes à l’héritabilité suggèrent que plusieurs gènes restent à découvrir. Certains d’entre eux peuvent se trouver dans les régions identifiées par des études de liaison génétique. L’objectif de mon projet de doctorat était d’identifier un ou des facteurs de risque génétique dans la région chromosomale 19p (identifiée comme région de liaison IBD6) et de le/les caractériser au niveau fonctionnel. Nous avons d’abord entrepris une cartographie d’association de la région 19p. À la suite du génotypage successif de deux cohortes indépendantes, nous avons identifié un SNP intronique et quatre SNP codants dont un non-synonyme, rs8108738, tous localisés dans le gène microtubule associated serine threonine kinase gene-3 (MAST3) et associés aux MII. Peu d’information fonctionnelle sur MAST3 était disponible. Par contre MAST2, une protéine encodée par un gène de la même famille, régule l’activité du facteur de transcription inflammatoire NF-kappaB. Nous avons confirmé l’implication de MAST3 dans l’activité de NF-kappaB via un knockdown de MAST3 et des essais gène-rapporteur. Pour poursuivre la caractérisation fonctionnelle de MAST3, nous avons choisi une approche non ciblée pour étudier les effets de la variation des niveaux d’expression de MAST3 sur la cellule. C’est-à-dire que nous avons créé un 1er modèle cellulaire de surexpression du gène MAST3 dans les cellules HEK293 et analysé l’expression pangénomique endogène. La validation de l’expression génique dans un 2e modèle cellulaire de knockdown et de type cellulaire différent (THP1), nous a permis d’identifier et de contrer les effets non-spécifiques dus aux niveaux non-physiologiques. Notre étude d’expression a mené à l’identification d’un groupe de gènes dont l’expression est régulée par MAST3. Ces gènes sont majoritairement impliqués dans des fonctions immunitaires (cytokines pro-inflammatoires, régulateurs de NF-kappaB, migration cellulaire, etc.) et une forte proportion est régulée par NF-kappaB. Nous avons évalué l’importance du groupe de gènes régulés par MAST3 dans la présentation clinique des MII à travers des études d’expression dans des biopsies intestinales de patients atteints de CU. Nous avons constaté que l’expression de ces gènes est significativement supérieure dans les régions enflammées par rapport aux régions saines de la muqueuse intestinale des patients atteints de CU. Globalement, les résultats de nos études suggèrent que le facteur de risque aux MII MAST3 agit via la voie du facteur de transcription NF-kappaB pour influencer l’expression d’un groupe de gènes impliqués dans l’inflammation intestinale typique des MII. Chaque étude génétique sur les MII a le potentiel d’orienter les recherches fonctionnelles vers de nouvelles voies biologiques causales. Le dévoilement des mécanismes moléculaires sous-jacents à ces voies permet d’augmenter les connaissances sur le développement de ces maladies vers une compréhension plus complète de la pathogenèse qui permettra d’optimiser le diagnostic et le traitement de ces maladies. / Inflammatory bowel diseases (IBD) refer to different chronic inflammatory diseases of the digestive tract mainly Crohn’s disease (CD) and ulcerative colitis (UC). Mechanisms leading to the pathogenesis of IBD are not completely understood, but genetic and functional studies have highlighted interactions between genetic predispositions and environmental factors, such as the intestinal microbiota, as contributors to the deregulation of the immune response that leads to inflammation of the intestinal mucosa. Genome-wide and targeted association studies have identified several IBD susceptibility genes. However, estimations of the contribution of these genes to heritability of the disease suggest that more are to be discovered. Some of these genes may be in previously identified IBD linkage regions. The objective of my doctoral project was first, to identify risk factors in the 19p chromosomal region (IBD6), previously identified following a genome-wide linkage study, then to characterise them functionally. We first performed a comprehensive association mapping study of the 19p region. Our two-stage genotyping strategy led to the identification of one intronic SNP and four coding SNP –including one non-synonymous SNP, rs8108738 – all located in the microtubule associated serine threonine kinase gene 3 (MAST3) and associated to IBD. Very limited functional information on MAST3 was available at that time. However MAST2 (a gene in the same family as MAST3), is involved in the regulation of inflammation master switch, transcription factor NF-B. We confirmed the involvement of MAST3 in the modulation of NF-B via a knockdown of MAST3 and gene reporter assays. In order to further characterize the function of MAST3, we chose a non-targeted approach to study the effects of the modulation of MAST3 levels on the cell. More specifically, we created a 1st cell model of MAST3 overexpression in HEK293 cells and analysed the resulting genome-wide endogenous gene expression. Validation in a 2nd cell model consisting of a knockdown of MAST3 in THP1 cells, allowed to identify non-specific gene expression due to non-physiological MAST3 levels. Our expression study led to the identification of a group of genes whose expression is modulated by MAST3. These genes are mainly involved in immune functions (pro-inflammatory cytokines, NF-B regulation, cellular migration, etc) and a majority is regulated by transcription factor NF-B. We evaluated the importance of this MAST3-regulated gene set in the clinical manifestation of IBD through an expression study on biopsies of UC patients. We found that the expression the MAST3-regulated gene set was significantly enriched in inflamed region of the intestinal mucosa of UC patients compared to healthy region. Taken together, the results of our study suggest that IBD risk factor MAST3 acts on the NF-B pathway to influence the expression of a group of genes involved in intestinal inflammation typical of IBD. Every genetic study on IBD has the potential to lead functional research towards new causal biological pathways. The unravelling of the molecular mechanisms underlying these pathways aims to improve the comprehension of the pathogenesis of IBD and hopefully will allow for optimization of diagnostic and treatment of these diseases.

Patients with schizophrenia and their siblings typically show subtle changes of brain structures, such as a reduction of hippocampal volume. Hippocampal volume is heritable, may explain a variety of cognitive symptoms of schizophrenia and is thus considered an intermediate phenotype for this mental illness. The aim of our analyses was to identify single-nucleotide polymorphisms (SNP) related to hippocampal volume without making prior assumptions about possible candidate genes. In this study, we combined genetics, imaging and neuropsychological data obtained from the Mind Clinical Imaging Consortium study of schizophrenia (n = 328). A total of 743,591 SNPs were tested for association with hippocampal volume in a genome-wide association study. Gene expression profiles of human hippocampal tissue were investigated for gene regions of significantly associated SNPs. None of the genetic markers reached genome-wide significance. However, six highly correlated SNPs (rs4808611, rs35686037, rs12982178, rs1042178, rs10406920, rs8170) on chromosome 19p13.11, located within or in close proximity to the genes NR2F6, USHBP1, and BABAM1, as well as four SNPs in three other genomic regions (chromosome 1, 2 and 10) had p-values between 6.75×10−6 and 8.3×10−7. Using existing data of a very recently published GWAS of hippocampal volume and additional data of a multicentre study in a large cohort of adolescents of European ancestry, we found supporting evidence for our results. Furthermore, allelic differences in rs4808611 and rs8170 were highly associated with differential mRNA expression in the cis-acting region. Associations with memory functioning indicate a possible functional importance of the identified risk variants. Our findings provide new insights into the genetic architecture of a brain structure closely linked to schizophrenia. In silico replication, mRNA expression and cognitive data provide additional support for the relevance of our findings. Identification of causal variants and their functional effects may unveil yet unknown players in the neurodevelopment and the pathogenesis of neuropsychiatric disorders.

Proper development of skeletal muscle occurs through a highly complex process where activation and repression of genes are essential. Control of this process is regulated by timely and spatial expression of specific transcription factors (TFs). Six1 and Six4 are homeodomain TFs known to be essential for skeletal muscle development in mice. Using the C2C12 cell line, a model for skeletal muscle differentiation, I used a functional genomics approach, employing siRNA specific to both these TFs, to characterize their role in skeletal myogenesis. To identify the genes that are regulated by both these TFs, gene expression profiling by microarray of cells treated with siRNA against Six1 and/or Six4 was performed. The knock-down of these TFs caused lower expression of markers of terminal differentiation genes in addition to an impairment of myoblast fusion and differentiation. Interestingly, transcript profiling of cells treated with siRNA against myogenin revealed that several of the Six1 and Six4 target genes are also regulated by myogenin. Through a combination of bioinformatic analyses it was also found that specific knock-down of Six4 causes an up-regulation of genes involved in mitosis and the cell cycle. In summary, these results show that Six1 and Six4 can both independently regulate different genes, but can also cooperate together with other TFs where they play an important role in the proper regulation of skeletal myogenesis.

Background: Imputation of partially missing or unobserved genotypes is an indispensable tool for SNP data analyses. However, research and understanding of the impact of initial SNP-data quality control on imputation results is still limited. In this paper, we aim to evaluate the effect of different strategies of pre-imputation quality filtering on the performance of the widely used imputation algorithms MaCH and IMPUTE. Results: We considered three scenarios: imputation of partially missing genotypes with usage of an external reference panel, without usage of an external reference panel, as well as imputation of ompletely un-typed SNPs using an external reference panel. We first created various datasets applying different SNP quality filters and masking certain percentages of randomly selected high-quality SNPs. We imputed these SNPs and compared the results between the different filtering scenarios by using established and newly proposed measures of imputation quality. While the established measures assess certainty of imputation results, our newly proposed measures focus on the agreement with true genotypes. These measures showed that pre-imputation SNP-filtering might be detrimental regarding imputation quality. Moreover, the strongest drivers of imputation quality were in general the burden of missingness and the number of SNPs used for imputation. We also found that using a reference panel always improves imputation quality of partially missing genotypes. MaCH performed slightly better than IMPUTE2 in most of our scenarios. Again, these results were more pronounced when using our newly defined measures of imputation quality. Conclusion: Even a moderate filtering has a detrimental effect on the imputation quality. Therefore little or no SNP filtering prior to imputation appears to be the best strategy for imputing small to moderately sized datasets. Our results also showed that for these datasets, MaCH performs slightly better than IMPUTE2 in most scenarios at the cost of increased computing time.

The genes that regulate pubertal timing in the general population are not well understood. Recently, genome-wide association studies have demonstrated that genetic variants near LIN28B associate with variation in pubertal timing in humans. To investigate where within the hypothalamic-pituitary-ovarian (HPO) axis Lin28b, and its homologue Lin28a, regulate pubertal timing, expression of these genes was assessed across the pubertal transition. The finding that Lin28a/b expression decreases only in the ovary suggests that the Lin28 pathway may exert its regulatory effects with respect to puberty in the ovary. Another aim of this thesis was to examine the effect of estrogen on Lin28b expression in immortalized GnRH neuronal cells, but the data remains equivocal and detailed future studies are needed to make definitive conclusions. The ovarian expression data lay the foundation for further studies using conditional knockout mice to verify the importance of the tissue and age specific developmental pattern that was identified.

The genes that regulate pubertal timing in the general population are not well understood. Recently, genome-wide association studies have demonstrated that genetic variants near LIN28B associate with variation in pubertal timing in humans. To investigate where within the hypothalamic-pituitary-ovarian (HPO) axis Lin28b, and its homologue Lin28a, regulate pubertal timing, expression of these genes was assessed across the pubertal transition. The finding that Lin28a/b expression decreases only in the ovary suggests that the Lin28 pathway may exert its regulatory effects with respect to puberty in the ovary. Another aim of this thesis was to examine the effect of estrogen on Lin28b expression in immortalized GnRH neuronal cells, but the data remains equivocal and detailed future studies are needed to make definitive conclusions. The ovarian expression data lay the foundation for further studies using conditional knockout mice to verify the importance of the tissue and age specific developmental pattern that was identified.

The existence of new technologies, implemented in efficient platforms and workflows has made massive genotyping available to all fields of biology and medicine. Genetic analyses are no longer dominated by experimental work in laboratories, but rather the interpretation of the resulting data. When billions of data points representing thousands of individuals are available, efficient computational tools are required. The focus of this thesis is on developing models, methods and implementations for such tools. The first theme of the thesis is multi-dimensional scans for quantitative trait loci (QTL) in experimental crosses. By mating individuals from different lines, it is possible to gather data that can be used to pinpoint the genetic variation that influences specific traits to specific genome loci. However, it is natural to expect multiple genes influencing a single trait to interact. The thesis discusses model structure and model selection, giving new insight regarding under what conditions orthogonal models can be devised. The thesis also presents a new optimization method for efficiently and accurately locating QTL, and performing the permuted data searches needed for significance testing. This method has been implemented in a software package that can seamlessly perform the searches on grid computing infrastructures. The other theme in the thesis is the development of adapted optimization schemes for using hidden Markov models in tracing allele inheritance pathways, and specifically inferring haplotypes. The advances presented form the basis for more accurate and non-biased line origin probabilities in experimental crosses, especially multi-generational ones. We show that the new tools are able to reconstruct haplotypes and even genotypes in founder individuals and offspring alike, based on only unordered offspring genotypes. The tools can also handle larger populations than competing methods, resolving inheritance pathways and phase in much larger and more complex populations. Finally, the methods presented are also applicable to datasets where individual relationships are not known, which is frequently the case in human genetics studies. One immediate application for this would be improved accuracy for imputation of SNP markers within genome-wide association studies (GWAS). / eSSENCE