Le développement des approches robustes et non paramétriques pour l’analyse et le traitement statistique de gros volumes de données présentant une forte variabilité,comme dans les domaines de l’environnement et de la génétique, est fondamental.Nous modélisons ici des données complexes de biologie appliquées à l’étude du comportement de bivalves et à l’analyse de liaison génétique. L’application des mathématiques à l’analyse du comportement de mollusques bivalves nous a permis d’aller vers une quantification et une traduction mathématique de comportements d’animaux in-situ, en milieu proche ou lointain. Nous avons proposé un modèle de régression non paramétrique et comparé 3 estimateurs non paramétriques, récursifs ou non,de la fonction de régression pour optimiser le meilleur estimateur. Nous avons ensuite caractérisé des rythmes biologiques, formalisé l’évolution d’états d’ouvertures,proposé des méthodes de discrimination de comportements, utilisé la méthode des shot-noises pour caractériser différents états d’ouverture-fermetures transitoires et développé une méthode originale de mesure de croissance en ligne.En génétique, nous avons abordé un cadre plus général de statistiques robustes pour l’analyse de liaison génétique. Nous avons développé des estimateurs robustes aux hypothèses de normalités et à la présence de valeurs aberrantes, nous avons aussi utilisé une approche statistique, où nous avons abordé la dépendance entre variables aléatoires via la théorie des copules. Nos principaux résultats ont montré l’intérêt pratique de ces estimateurs sur des données réelles de QTL et eQTL. / The development of robust and nonparametric approaches for the analysis and statistical treatment of high-dimensional data sets exhibiting high variability, as seen in the environmental and genetic fields, is instrumental. Here, we model complex biological data with application to the analysis of bivalves’ behavior and to linkage analysis. The application of mathematics to the analysis of mollusk bivalves’behavior gave us the possibility to quantify and translate mathematically the animals’behavior in situ, in close or far field. We proposed a nonparametric regression model and compared three nonparametric estimators (recursive or not) of the regressionfunction to optimize the best estimator. We then characterized the biological rhythms, formalized the states of opening, proposed methods able to discriminate the behaviors, used shot-noise analysis to characterize various opening/closing transitory states and developed an original approach for measuring online growth.In genetics, we proposed a more general framework of robust statistics for linkage analysis. We developed estimators robust to distribution assumptions and the presence of outlier observations. We also used a statistical approach where the dependence between random variables is specified through copula theory. Our main results showed the practical interest of these estimators on real data for QTL and eQTL analysis.

La spondyloarthrite (SpA) est un rhumatisme inflammatoire chronique fréquent et invalidant. Plus d’une vingtaine de locus de susceptibilité à la maladie ont été identifiés à ce jour, dont HLA-B27 situé dans le complexe majeur d’histocompatibilité (CMH). L’objectif de ce travail était d’identifier de nouveaux facteurs génétiques de susceptibilité à la SpA grâce à une double approche d’études familiales et de génomique fonctionnelle. Dans la première partie, nous avons génotypé des familles multiplex de SpA. L’analyse de liaison non paramétrique a révélé la présence, en plus du CMH, d’un nouveau locus significativement lié à la SpA en 13q13. L’étude de ce locus nous a permis de restreindre la région d’intérêt à un intervalle de 1,3 Mb, dont le séquençage est en cours. Par ailleurs, l’étude d’association intra-familiale a identifié un SNP intronique de MAPK14 significativement associé à la SpA. Enfin, nous avons montré que l’un des SNPs du gène IL23R connu pour être associé à la spondylarthrite ankylosante était en fait associé à la présence d’une sacro-iliite radiologique dans la SpA. Parallèlement aux études familiales, nous avons comparé le transcriptome de cellules dendritiques de neuf patients atteints de SpA à celui de dix témoins sains. Nous avons ainsi identifié 81 gènes différentiellement exprimés. Nous avons aussi montré que l’expression génique d’ERAP1 (et à un moindre degré son expression protéique et son niveau d’activité enzymatique) étaient sous le contrôle de polymorphismes de ce gène associés à la SpA. / Spondyloarthritis (SpA) is a frequent and disabling chronic rheumatic disease. To date, more than 20 susceptibility loci have been identified, including HLA-B27 in the major histocompatibility complex (MHC). Most of the disease heritability remains to be elucidated. The aim of the study was to identify new genetic factors of susceptibility to SpA using an approach combining genetics and functional genomics. In the first part of this work, we genotyped SpA multiplex families with microarrays of 250,000 SNPs. Non parametric linkage analysis revealed a new locus significantly linked to SpA outside the MHC, in 13q13. Further studies on this locus allowed us to map the disease interval to a 1.3 Mb region, which will be soon sequenced. Moreover, family-based association study identified a significant association between one intronic SNP in MAPK14 and SpA. We also showed that one of the known ankylosing spondylitis-associated SNP in IL23R was indeed associated with sacroiliitis in SpA. We have also compared dendritic cells gene expression between nine SpA patients and ten controls and identified 81 genes differentially expressed. Moreover, we showed that ERAP1 gene expression (and at a less extent protein expression and enzymatic activity) is under the control of several polymorphisms in the gene which has previously been associated with SpA.

Contrairement aux maladies génétiques mendéliennes, qui dépendent d’un seul gène causal, les traits quantitatifs complexes sont des caractéristiques mesurables d’organismes vivants, qui résultent de l’interaction entre plusieurs gènes et les facteurs environnementaux. La génomique fonctionnelle nous a permis d’identifier de nombreux locus génétiques liés aux caractères complexes, qui sont appelés «locus de traits quantitatifs» (QTL). Cependant, de telles études ne permettent pas une caractérisation précise de l'architecture génétique des traits complexes. Plus récemment, il est devenu possible d’identifier des locus génétiques associés aux niveaux d'expression de gènes, appelés«locus de traits quantitatifs d’expression» (eQTLs). Dans de tels cas, les variants génétiques peuvent affecter l'expression soit des gènes qui se situent dans leur voisinage (cis-eQTLs), soit de ceux qui résident plus loin (trans-eQTLs). Dans des cas particuliers, un même locus peut affecter l’expression de plusieurs gènes situés dans différents chromosomes, formant ce qu’on appelle des ‘trans-eQTLs hotspots’. Ceux-ci peuvent avoir d’importants intérêts biologiques, car ils sont généralement enrichis en gènes fonctionnellement apparentés qui peuvent influencer le même trait phénotypique. Dans cette thèse, en analysant l'expression des gènes dans des échantillons de cœurs obtenus à partir d'un panel de souches consanguines recombinantes de souris AxB / BxA, nous avons détecté un QTL lié en trans- à l'expression de 190 transcrits, dont la majorité est connue pour être sensible aux interférons de type I. Le même locus correspondait également à celui d'un cis-eQTL pour le gène Ypel5, ce qui suggère que ce dernier peut être un régulateur commun des gènes trans-eQTL. Donc, le but principale de cette thèse fut de valider biologiquement le rôle du gène cis-eQTL dans la régulation du ‘trans-eQTLs hotspots’. Les travaux présentés dans cette thèse ont montrés que la réduction de l'expression de Ypel5 dans des macrophages de souris a stimulée l'expression de plusieurs gènes qui appartiennent au ‘trans-eQTL hotspot’, et ce d’une manière dépendante d’IFNB1. Le knockdown de YPEL5 a également augmenté l’induction d’IFNB1 dans les cellules humaines HEK293T. Lorsque ces dernières ont été soumis à des stimuli qui activent les kinases TBK1 / IKBKE, nous avons détecté des interactions fonctionnelles de YPEL5 avec l'activité de ces kinases, ainsi que des interactions physiques avec IKBKE. Nos résultats préliminaires (présentés dans le chapitre3) suggèrent aussi l’implication de YPEL5 dans la régulation du cycle cellulaire et /ou de la sénescence. En conclusion, nous sommes parmi les premiers groupes à fournir des preuves biologiques montrant le rôle d'un gène cis-eQTL en tant que régulateur commun de gènes appartenant à un ‘hotspot de trans-eQTL’. La validation biologique des analyses génomiques a ainsi permis de découvrir Ypel5 comme un nouveau régulateur négatif de la réponse antivirale innée qui agit (au moins en partie) au niveau des kinases TBK1 / IKBKE. / Unlike Mendelian genetic diseases, which depend on a single causal gene, complex quantitative traits are measurable characteristics of living organisms, which result from the interaction between several genes and environmental factors. Functional genomics has allowed us to identify many genetic loci linked to complex traits, which are called "quantitative trait loci" (QTL). However, such studies do not allow an accurate characterization of the genetic architecture of complex traits. More recently, it has become possible to identify genetic loci associated with gene expression levels, called "expression quantitative trait locus" (eQTLs). In such cases, the genetic variants can affect the expression of genes that are either located in their vicinity (cis-eQTLs) or that reside further away (trans-eQTLs). In particular cases, the same locus can affect the expression of several genes located on different chromosomes, forming so-called ‘trans-eQTLs hotspots’. These may have important biological interests, as they are generally enriched in functionally related genes, which may influence the same phenotypic trait. In this thesis, by analyzing the expression of genes in hearts from a panel of AxB / BxA mouse recombinant inbred strains, we detected a QTL linked in trans- to the expression of 190 transcripts, the majority of which are known to be sensitive to type I interferon. The same locus also corresponded to that of a cis-eQTL for the Ypel5 gene, suggesting that it could be a common regulator of the trans-eQTL genes. Therefore, the main purpose of this thesis was to biologically validate the role of the cis-eQTL gene in the regulation of the ‘trans-eQTL hotspot’. The work presented in this thesis showed that the silencing of Ypel5 expression in mouse macrophages stimulated the expression of several genes that belong to the ‘trans-eQTL hotspot’ in an IFNB1-dependent manner. YPEL5 knockdown also increased IFNB1 induction in human HEK293T cells. When the latter were subjected to stimuli that activate the TBK1/IKBKE kinases, we detected functional interactions of YPEL5 with the activity of these kinases and physical interactions with IKBKE. Our preliminary results (presented in Chapter 3) suggest also the involvement of YPEL5 in the regulation of cell cycle progression and / or senescence. In conclusion, we are among the first groups to provide biological evidence showing the role of a cis-eQTL gene as a common regulator of genes belonging to a ‘trans-eQTL hotspot’. The biological validation of genomic analysis thus revealed Ypel5 as a new negative regulator of the innate antiviral response that acts (at least in part) at the level of the TBK1 / IKBKE kinases.

The Major Histocompatibility Complex (MHC) is a highly polymorphic region of the genome located on chromosome 6p21 in which genetic diversity has been associated with susceptibility to many autoimmune, infectious and other common diseases. Despite strong associations between disease and variation in the MHC that have been identified initially from serological testing and more recently by genome-wide association studies, functional insights into how specific variants may be altering disease susceptibility remain poorly understood in most cases. It is predicted that gene expression will play a significant role in the modulation of disease susceptibility and so further understanding of allele specific gene expression in the MHC will be necessary to help define the function of disease associated variants in this region. This thesis aimed to define allele specific gene expression in the MHC by characterising specific candidate genes together locus-wide approaches in order to try and resolve functional variants. Gene expression was analysed in both lymphoblastoid cell lines (LCLs) and primary human peripheral blood mononuclear cells (PBMCs). Data is presented validating a novel haplotype-specific MHC microarray and fine mapping putative local, likely cis-acting, regulatory variants. This was done by expression quantitative trait mapping for two cohorts of healthy volunteers. A transcription factor ZFP57, encoded in the MHC, was found to show significant differential allelic expression relating to specific single nucleotide polymorphisms (SNPs) and possession of HLA-type. This provided new insights into reported disease associations, notably HIV-1 infection and cancer. The function of ZFP57 was further investigated in terms of genome-wide DNA binding sites by ChIP-seq together with its binding co-factor KAP1. Allele-specific gene expression was also demonstrated for several classical HLA genes including the HLA-C and HLA-DQ genes, fine mapping specific putative regulatory variants. This provided new insights into disease association, notably variants of HLA-DQB1 and susceptibility to leprosy. The applicability and sensitivity of the technique of RNA sequencing (mRNA-seq) for allele-specific quantification of gene expression was investigated for different allelic ratios of RNA from LCLs homozygous for sequence across the MHC. Significant challenges were identified in successful application of this technique to MHC genes while high levels of accuracy were observed dependent on read depth in non-MHC genes. This thesis provides new insights into the extent and nature of allele-specific gene expression in the MHC, experimental approaches that can be used and insights gained into disease susceptibility for this important genomic region.

Epstein-Barr Virus (EBV), a ubiquitous herpesvirus that infects over 95% of the adult human population, has been implicated in the aetiology of a range of autoimmune diseases and tumours. In some of these disorders such as post-transplant B-cell lymphomas, EBV acts as a direct causal factor, in others, like Hodgkin's disease and nasopharyngeal carcinoma, it is an important co-factor. Additionally, EBV infection has been linked to several other diseases, most notably Multiple Sclerosis through positive correlation with the occurrence of Infectious Mononucleosis – a benign lymphoproliferative disease caused by primary EBV infection. The key feature of most EBV-disease associations is the ability of the virus to infect and transform human B- T- NK- and epithelial cells using a set of transcripts and proteins, some of which act as oncogenes. While it is evident that EBV viral load and gene expression may be correlated with the course of disease or even directly contributing to its pathology, the genetic determinants of EBV uptake, expression and its proliferative capacity remain unresolved. This project aimed to investigate the genetic determinants of EBV copy number and EBV latency gene expression for human B-cells immortalised by EBV in vitro and transformed into permanently growing lymphoblastoid cell lines (LCLs), as a model for early-stage EBV infection in naïve B-cells. LCL samples studied have been sourced from several different populations, the HapMap Project, the 1000 Genomes Project as well as British MRC-A family cohort. Methods used encompass quantification of viral expression and copy number using TaqMan and SybrGreen PCR techniques, followed by statistical association tests conducted using Plink, Merlin and MatrixEQTL. EBV QTLs identified by the assays were next subjected to a meta-analysis in GWAMA. Two most significant eQTLs were also selected for a replication experiment in an independent panel of newly generated LCLs and validated in peripheral blood B-cells sourced from the same donors. Multiple significant and suggestive expression and copy number QTLs were identified. However, most of these associations have not been replicated in more than a single cohort. The relatively small sample size of most cohorts tested as well as population structure posed a limitation. Some findings merit attention, particularly the presence of statistically significant viral eQTLs within or close to CSMD1 locus in two different cohorts, and finding of a significant EBV eQTL in a SNP associated with type 1 diabetes risk and located close to IL2RA, an immune-response gene harbouring multiple autoimmune disease risk loci. Suggestive associations were also identified in the 1000 Genomes Project samples by the copy number assay which resulted in the most robust test conducted. These encompassed an association to the PRDM9 locus as well as to a gene involved in TGF-β secretion. This is particularly interesting since TGF-β signal promotes lytic replication in EBV-infected B-cells and a consistent significant correlation between EBV lytic expression and increased viral copy number has been identified. In conclusion, although no significant association has been consistently replicated, the project provided several suggestive EBV QTL candidates with plausible biological links to EBV infection and replication, which could be studied further in independent experiments.

Sex biased expression characterizes ~1,000 genes in mammalian liver, and impart sex differences in metabolism and disease susceptibility. The sex-dependent temporal patterns of pituitary growth hormone (GH) secretion, pulsatile in males and more continuous in females, are known to sex-differentially activate transcriptional regulators (TFs), leading to widespread sex-differences in the mouse liver transcriptome. This thesis elucidates sex-biased gene expression patterns in the following studies. Gene structures, expression patterns and species conservation are characterized for ~15,000 liver-expressed intergenic long noncoding RNAs (lncRNAs), many of which are novel. Analysis of intergenic lncRNA promoters revealed unexpected high conservation and significant enrichment of TF binding compared to protein-coding promoters. A subset of intergenic lncRNAs showed strong sex-specific and GH-dependent gene expression, and whose transcription was tightly correlated with the surrounding chromatin environment and TF binding patterns. The pervasive role of genetic factors to regulate sex-biased genes was revealed by analyzing livers with matched genotype and gene expression data from Diversity Outbred (DO) mice, an outbred population with high natural allelic variance derived from eight inbred strains. Significant associations between genetic variants and gene expression (eQTLs) were identified, including many eQTLs with a strong sex-biased association. Remarkably, a large fraction of these sex-biased eQTLs were linked to either gain or loss of sex-specific gene expression in the DO founder strain predicted to be regulated by the eQTL. Thus, genetic factors are a major contributor to the variability of sex-biased genes, which has important consequences related to the individual variability of liver phenotypes with known sex-differences. Natural genetic perturbations in DO mice were leveraged to identify candidate lncRNAs that may regulate hypophysectomy (hypox) responsiveness. Co-regulated protein-coding gene clusters were discovered based on gene expression correlations across DO mouse livers, many of which are enriched for distinct hypox response classes. LncRNAs whose expression showed unexpected significant negative correlation with protein-coding gene clusters enriched for genes of the opposite-sex bias and inverse hypox class were hypothesized to play negative regulatory role. In sum, these studies expand the characterization of the sex-biased hepatic transcriptome and reveal contributions of genetic factors to the regulation of sex bias in mammalian liver. / 2020-11-27T00:00:00Z

Cette thèse a pour objet l'étude du lien génotype-transcriptome et de son influence sur le développement des maladies multifactorielles. Les apports de ce travail sont à la fois méthodologiques et appliqués. Nous étudions d'abord le lien génotype-transcriptome en établissant la liste des eQTL (expression Quantitative Trait Loci) dans le monocyte et nous évaluons l'apport de l'observation des eQTL pour l'interprétation des analyses d'association génome entier (GWAS). Nous proposons ensuite une méthode pour l'identification de variants génétiques affectant des modules de gènesco-régulés que nous appliquons à l'étude des données d'expression de monocytes issus d'une large étude populationnelle (GHS). Nous mettons ainsi en évidence plusieurs loci affectant l'expression de modules de gènes co-régulés, dont plusieurs sont impliqués dans la prédisposition au diabète de type I. Nous montrons également que le processus d'isolation des cellules monocytaires peut engendrer des biais liés à la contamination par des types cellulaires non désirés et nous proposons une approche pour contrôler ce type de biais dans les analyses.

<p>Pathologies of sexual development are common in humans and reflect the precarious processes of sex determination and sexual differentiation. The gonad forms as a bipotential organ, and recent results from the Capel lab revealed that it is initially balanced between testis and ovarian fates by opposing and antagonistic signaling networks. In XY embryos, this balance is disrupted by the transient expression of the Y-linked gene, Sry, which activates genes that promote the testis pathway and oppose the ovarian pathway. While the roles of a few genes have been defined by mutation, current evidence suggests that the interactions of many genes and signaling pathways are involved in the establishment of sexual fate. For example, most cases of disorders of sexual development (DSDs) are unexplained by mutations in known sex determination genes. In addition, recent microarray studies in the mouse revealed that nearly half the transcriptome is expressed in the gonad at the time of sex determination (Embryonic day 11.5, or E11.5), and as many as 1,500 genes are expressed in a sexually dimorphic pattern at this early stage. Thus the sexual fate decision in the developing gonad likely depends on a complex network of interacting factors that converge on a critical threshold. </p><p>To begin to elucidate the transcription network topology underlying sex determination, we exploited two inbred mouse strains with well-characterized differences in sex reversal. The common inbred strain C57BL/6J (B6) is uniquely sensitive to XY male-to-female sex reversal in response to a number of genetic perturbations, while other strains, including 129S1/SvImJ (129S1) and DBA/2J (D2) are resistant to sex reversal. We hypothesized that these strain differences in gonad phenotype likely result from underlying expression differences in the gonad at the critical timepoint of E11.5. Using microarrays, we identified significant, reproducible differences in the transcriptome of the E11.5 XY gonad between B6 and 129S1 indicating that the reported sensitivity of B6 to sex reversal is consistent with a higher expression of a female-like transcriptome in B6 XY gonads. Surprisingly, a well-characterized master regulator of the testis pathway, Sox9, was found to be upregulated in the sensitive B6 background, which may serve as a compensatory mechanism to counteract the female-leaning transcriptome and activate the testis pathway in wild type B6 XY gonads.</p><p>We extended our expression analysis to a large set of F2 XY gonads from B6 and 129S1 intercrosses. From each pair of gonads, we analyzed the expression of 56 sex-associated genes by nanoliter-scale quantitative RT-PCR (qRT-PCR). The expression levels of most genes were highly variable across the F2 population, yet strong correlations among genes emerged. We employed a First-Order Conditional Independence (FOCI) algorithm to estimate the F2 coexpression network. From this unbiased analysis of XY expression data, we uncovered two subnetworks consisting of primarily male and female genes. Furthermore, we predicted roles for genes of unknown function based on their connectivity and position within the network. </p><p>To identify the genes responsible for these strain expression differences, we genotyped each F2 embryo at 128 single nucleotide polymorphisms (SNPs) located evenly throughout the 19 autosomes and X chromosome. We then employed linkage analysis to detect autosomal regions that control the expression of one or more of the 56 genes in the F2 population. These regions are termed expression quantitative trait loci, or eQTLs. We identified eQTLs for many sex-related genes, including Sry and Sox9, the key regulators of male sex determination. In addition, we identified multiple prominent trans-band eQTLs that controlled the expression of many genes. My work represents the first eQTL analysis of a developing vertebrate organ, the mouse gonad. This systems-level approach revealed the complex transcription architecture underlying sex determination, and provides a mechanistic explanation for sensitivity to sex reversal seen in some individuals.</p> / Dissertation

The innate immune system is of central importance to the early containment of infection. When receptors of innate immunity recognize molecular patterns on pathogens, they initiate an immediate immune response by inducing the expression of cytokines and other host defense genes. Altered expression or function of the receptors, the molecules that mediate the signal transduction cascade, or the cytokines themselves can predispose individuals to infectious or autoimmune diseases. Here we used genomic approaches to uncover novel components underlying the innate immune response to cytosolic DNA and to characterize variation in the innate immune responses of human dendritic cells to bacterial and viral ligands. In order to identify novel genes involved in the cytosolic DNA sensing pathway, we first identified candidate proteins that interact with known signaling molecules or with dsDNA in the cytoplasm. We then knocked down 809 proteomic, genomic, or domain-based candidates in a high-throughput siRNA screen and measured cytokine production after DNA stimulation. We identified ABCF1 as a critical protein that associates with DNA and the known DNA-sensing components, HMGB2 and IFI16. We also found that CDC37 regulates stability of the signaling molecule, TBK1, and that chemical inhibition of CDC37 as well as of several other pathway regulators (HSP90, PPP6C, PTPN1, and TBK1) potently modulates the innate immune response to DNA and to retroviral infection. These proteins represent potential therapeutics targets for infectious and autoimmune diseases that are associated with the cytosolic DNA response. We also developed a high-throughput functional assay to assess variation in responses of human monocyte-derived dendritic cellsto LPS (receptor: TLR4) or influenza (receptors: RIG-I and TLR3), with the goal to ultimately map genetic variants that influence expression levels of pathogen-responsive genes. We compared the variation in expression between the dendritic cells of 30 different individuals, and within paired samples from 9 of these individuals collected several months later. We found genes that have significant inter- vs. intra-individual ariation in response to the stimuli, suggesting that there is a substantial genetic component underlying variation in these responses. Such variants may help to explain differences between individuals’ risk for infectious, autoimmune, or other inflammatory diseases.

Since the completion of the sequencing of the human genome at the turn of the century, genomics has revolutionized the study of biology and medicine by providing high-throughput and quantitative methods for measuring molecular activities. Microarray and next generation sequencing emerged as important inflection points where the rate of data generation skyrocketed. The high dimensionality nature and the rapid growth in the volume of data precipitated a unique computational challenge in massive data analysis and interpretation. Noise and signal structure in the data varies significantly across types of data and technologies; thus, the context of the data generation process itself plays an important role in detecting key and oftentimes subtle signals. In this dissertation, we discuss four areas where contextualizing the data aids discoveries of disease-causing variants, complex relationships in the human microecology, interplay between gene and environment, and genetic regulation of gene expression. These studies, each in its own unique way, have helped made possible discoveries and expanded the horizon of our understanding of the human body, in health and disease.