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The genetic basis of the different cancer phenotypes has been a continuous and accelerating subject of investigation. Data accumulated thanks to recently introduced genome-wide scanning technologies have revealed that human diversity and diseases susceptibility is also greatly influenced by structural alterations in the human genome, such as DNA copy number variants (CNVs) and copy number alterations (CNAs), which influence gene expression in both healthy and pathological cells. Our research aims to investigate the influence of structural alterations on gene expression in cancer cells using SNP microarray data. Specifically, we focus on analyzing DNA copy number alternations (CNAs), which can significantly influence gene expression in cancer cells. Several cancer-predisposing mutations affect genes that are responsible for maintaining the integrity of the chromosomes during cell division, which can result in translocations, gains or losses of large parts of chromosome. To our knowledge, there have been no publications that link whole-genome copy number alterations in cancer to gene expression variations using the full range of possibilities offered by SNP arrays. The accurate use of SNP arrays in the analysis of cancer has been difficult due to tumour purity, tumour heterogeneity, aneuploidy/polyploidy and complex patterns of CNA and loss-of-heterozygosity (LOH). In our work, we use and further extend a recently developed novel tool for tumour genome profiling called OncoSNP (Yau, Mouradov et al. 2010), in order to resolve some of those problems and accurately estimate copy number alterations (CNA) and loss-of-heterozygosity (LOH) from SNP array data in cancer cell samples. The methods developed in this thesis tackle the problem of cancer genomic investigation by developing and validating an extension (DPS smoothing) of a new method (OncoSNP). This approach is used in the analysis of global expression versus CNA patterns in experimental systems and large clinical datasets. We analyse various cancer SNP and gene expression arrays of increasing complexity and heterogeneity, starting with a dataset of head and neck squamous cell carcinoma (HNSCC) cell lines, followed by leukaemia samples and finally a large breast cancer dataset. The central findings of our research are multifold. In the HNSCC dataset we find that the level of genetic instability is not indicative of the pathological state; i.e. there are premalignant lesions displaying extensive mutations. However some genetic features are typical of certain lesion type; e.g. we consistently observe copy loss in the short arm of chromosome 3 in carcinoma. The pattern of homozygous deletion in the dataset reveals common deletion of cancer related genes, especially CDK4 (pI6). Furthermore we notice a significant positive correlation between the copy number and the expression on a systematic level. In Leukaemia, we do not observe extended uniparental disomy as previously published (Akagi, Shih et al. 2009) and expected. However large alterations (whole arm amplification) are observed in individual patients: copy loss in chromosome 7 (2 patients), copy gain in chromosome 8 (3 patients) as well as common alterations around the centromeres and telomeres. In the breast cancer dataset significantly different level of mutations were observed in the different subtypes in the cohort. Furthermore 499 genes were identified with significant correlation between their gene expression (GE) and underlying genomic alterations (either copy number (CN) or loss-of-heterozygosity (LOH)). Performing hierarchical clustering on the cohort using the 499 correlated genes enabled us to recover the subtypes' separation previously based on gene expression alone.

Mieux comprendre les mécanismes de la résistance aux antibiotique est un enjeu important dans la lutte contre les maladies infectieuses, qui fait face à la propagation de bactéries multi-résistantes. Les études d'association à l'échelle des génomes sont des outils puissants pour explorer les polymorphismes liés aux variations phénotypiques dans une population. Leur cadre méthodologique est très documenté pour les eucaryotes, mais leur application aux bactéries est très récente. Durant cette thèse, j'ai cherché à rendre ces outils mieux adaptés aux génomes plastiques des bactéries, principalement en travaillant sur la représentation des variations génétiques. En effet, parce que les bactéries ont la capacité à échanger du matériel génétique avec leur environnement, leurs génomes peuvent être trop différents au sein d'une espèce pour être alignés contre une référence. La description des variations par des fragments de séquence de longueur k, les k-mers, offre la flexibilité nécessaire mais ne permet pas une interprétation directe des résultats obtenus. La méthode mise au point teste l'association de ces k-mers avec le phénotype, et s'appuie sur un graphe de De Bruijn pour permettre la visualisation du contexte génomique des k-mers identifiés par le test, sous forme de graphes. Cette vue synthétique renseigne sur la nature de la séquence identifiée: il peut par exemple s'agir de polymorphisme local dans un gène ou de l'acquisition d'un gène dans un plasmide. Le type de variant représenté dans un graphe peut être prédit avec une bonne performance à partir de descripteurs du graphe, rendant plus opérationnelles les approches par k-mers pour l'étude des génomes bactériens / The emergence and spread of multi-drug resistance has become a major worldwide public health concern, calling for better understanding of the underlying resistance mechanisms. Genome-wide association studies are powerful tools to finely map the genetic polymorphism linked to the phenotypic variability observed in a population. However well documented for eukaryotic genome analysis, these studies were only recently applied to prokaryota.Through this PhD project, I searched how to better adapt these tools to the highly plastic bacterial genomes, mainly by working on the representation of the genetic variations in these genomes. Indeed, because the bacteria have the faculty to acquire genetic material by a means other than direct inheritance from a parent cell, their genomes can differ too much within a species to be aligned against a reference. A representation using sequence fragments of length k - the so-called k-mers - offers the required flexibility but generates redundancy and does not allow for a direct interpretation of the identified associations. The method we set up tests the association of these k-mers with the phenotype, and takes advantage of a De Bruijn graph (DBG) built over all genomes to remove the local redundancy of k-mers, and offer a visualisation of the genomic context of the k-mers identified by the test. This synthetic view as DBG subgraphs informs on the nature of the identified sequence: e.g. local polymorphism in a gene or gene acquired through a plasmid. The type of variant can be predicted correctly in 96% of the cases from descriptors of the subgraphs, providing a tractable framework for k-mer-based association studies

We have investigated genetic variation in microRNA-mediated regulation as a susceptibility factor for anxiety disorders following two different approaches. We first studied two isoforms of the candidate gene NTRK3 by re-sequencing its different 3'UTRs in patients with Panic (PD) and Obsessive Compulsive disorders (OCD) as well as controls. Two rare variants that altered microRNA-mediated regulation were identified in PD. Conversely, association of a common SNP with OCD hoarding subtype was found. Moreover, we have also studied a possible involvement of microRNAs in anxiety disorders. Consequently, we have analysed the genomic organisation and genetic variation of miRNA-containing regions to construct a panel of SNPs for association analysis. Case-control studies revealed several associations. However, it is worth remarking the associations of miR-22 and miR-488 with PD; two microRNAs for which functional assays and transcriptome analysis after microRNA overexpression showed significant repression of a subset of genes involved in physiological pathways linked to PD development. / Hem investigat la variació genètica a la regulació mediada per microRNAs com a factors de susceptibilitat pels trastorns d'ansietat seguint dues aproximacions diferents. Primer vam estudiar dues isoformes del gen candidat NTRK3 mitjançant la reseqüenciació dels seus diferents 3'UTRs a pacients de pànic (TP), a pacients amb trastorn obsessiu compulsiu (TOC) i a controls. Dues variants rares que alteren la regulació mediada per microRNAs foren identificades per TP. D'altra banda, es trobà associació d'un SNP comú amb el subtipus acumulador de TOC. A més, també hem estudiat la possible implicació dels microRNAs als trastorns d'ansietat. Conseqüentment, hem analitzat l'organització genòmica i la variació genètica a regions que contenen microRNAs per construir un panell d'SNPs per fer anàlisis d'associació. Els estudis cas-control van revelar algunes associacions. Tanmateix, val la pena destacar les associacions del miR-22 i el miR-488 amb TP; dos microRNAs pels quals assajos funcionals i anàlisis de transcriptoma després de la seva sobreexpressió han mostrat una repressió significativa d'un grup de gens implicats en vies fisiològiques lligades al desenvolupament del TP.