La Polyarthrite Rhumatoïde (PR) est une maladie auto-immune inflammatoire complexe qui touche près de 0,3% de la population française. A ce jour, malgré l'identification d'un facteur génétique majeur (HLA-DRB1), et d'une centaine de facteurs de susceptibilité d'effet faible à modéré (majoritairement identifiés par des études d'associations pangénomiques - GWAS), on ne peut expliquer au plus que 50% de la composante génétique de la maladie. Les GWAS se focalisant sur les variants fréquents (fréquence de l'allèle mineure (MAF) ≥ 1%) et considérant l'effet de ces variants comme indépendants, nous avons cherché dans ces travaux à identifier de nouveaux facteurs génétiques de la PR via l'analyse de variants rares (variants d'un seul nucléotide (SNVs) ou petites insertions et délétions (InDels)) pour lesquels peu d'études sont référencées dans la littérature. Nous avons ensuite étudié les interactions gène/gène (GxG) dans des voies biologiques enrichies par les variants rares identifiés.Pour cela, nous avons travaillé sur deux jeux de données obtenus par séquençage d'exomes. Dans le premier échantillon (data1), nous avons cherché à évaluer la contribution des variants rares dans 1080 gènes candidats séquencés chez 240 cas et 240 témoins français. Dans le second échantillon (data2), notre objectif était d'identifier de nouveaux facteurs génétiques par l'analyse de variants rares chez 30 individus (dont 19 atteints) appartenant à 9 familles françaises à cas multiples de PR. Nous avons mis en place un workflow afin de réaliser toutes les étapes de traitement des séquences obtenues jusqu'à l'identification des variants (alignement des lectures sur la séquence de référence du génome humain GRCh37, nettoyage de l'alignement, identification des variants (SNV et Indels) et filtre qualité des variants identifiés).Avec data1, nous avons répliqué l'association entre la PR et le gène BTNL2 (p-value = 3,0E-6) et identifié trois nouveaux gènes à risque (p-value ≤ 4,0E-3), impliqués dans la différentiation et l'activation des cellules du système immunitaire, en combinant les multiples variants de fréquences faibles à modérées identifiés dans ces gènes (analyses d'association de type burden). Dans data2, nous avons effectué une étude d'association-liaison, par laquelle nous avons identifié 3 gènes - SUSD5, MNS1 et SMYD5 - présentant une agrégation de variants (rares et fréquents) associée à la PR (p-value < 0,04 après 10E6 permutations), et un gène nommé SUPT20H dont le signal d'association était porté par un seul variant rare à pénétrance complète dans une famille et sans phénocopie. Nous avons aussi mis en évidence, via une étude d'enrichissement, une agrégation de variants rares dans plusieurs voies biologiques dont l'adhésion focale. Dans cette voie, nous avons identifié 9 interactions candidates pour lesquelles plusieurs combinaisons génotypiques semblent conférer un risque supplémentaire de développer la PR (p-value ≤ 5,0E-5). / Rheumatoid arthritis (RA) is a complex inflammatory autoimmune disease affecting about 0.3% of French population. Today, despite the identification of a major genetic factor (HLA-DRB1), and more than one hundred susceptibility factors with low to moderate effect (mainly identified by Genome-Wide association studies - GWAS), we cannot explain more than 50% of RA genetic component. Knowing that GWAS only study frequent variants (minor allele frequency (MAF) ≥ 1%) and consider that all of them are independent, we tried to identify new RA genetic factors by focusing on rare variants (single nucleotide variants (SNVs) or small insertions and deletions (InDels)) for which, to date, only few studies has been conducted. In addition, we studied gene/gene interactions (GxG) in biological pathways enriched for rare susceptible variants.To this end, we worked on two datasets obtained by exome sequencing. With the first dataset (data1), we wanted to evaluate the contribution of rare variants to RA risk into 1080 candidate genes sequenced in 240 cases et 240 controls from French population. With the second dataset (data2), our aim was to identify new genetic factors by focusing on rare variants selected from 30 individuals (including 19 affected) belonging to 9 French multiplex families. We set up in the laboratory a workflow to process the produced sequences up to the identification of variants (read alignment on human reference genome GRCh37, alignment refinement, variant identification (SNV et Indels) and quality filters).In data1, we replicated the association between RA and BTNL2 gene (p-value = 3,0E-6) and identified 3 new RA risk genes (p-value ≤ 4,0E-3), involved in the differentiation and activation of immune system cells, by combining rare to low frequency variants (burden association analysis). In data2, with a linkage – association study, we identified 3 genes - SUSD5, MNS1 and SMYD5 – presenting an aggregation of rare and frequent variants associated with RA (p-value < 0.04 with 10E6 permutations), and another gene SUPT20H in which we identified one rare variant with complete penetrance in one of the family and without phenocopy. Finally, we identified, by enrichment analysis, several biological pathways presenting an aggregation of rare variants. In one of them (focal adhesion), we extracted 9 candidate GxG interactions for which multiple genotype combinations seem to increase RA risk (p-value ≤ 5,0E-5).

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Craniosynostosis is a disorder characterized by the premature fusing of cranial sutures in an infant. Premature closure of these sutures can lead to detrimental consequences on the development of a child. The two broad categories of craniosynostosis are classified as syndromic and nonsyndromic. Nonsyndromic craniosynostosis involves only the fusion of one or more sutures, whereas syndromic craniosynostosis involves other abnormalities throughout the body of the affected individual. Two of the families analyzed in this study were of the syndromic nature, and known FGFR mutations were discovered. However, phenotypical features documented in association with these mutations differed from our individuals. Two families affected with nonsyndromic sagittal synostosis were also analyzed. Within one of these families, three candidate mutations were identified as possible disease causing mutations. These mutations were found in the genes ITGAV, SLC30A9, and BAMBI. Here we analyze the function of these proteins and determine the significance of the role they may play in nonsyndromic craniosynostosis.

<p>The advent of next-generation sequencing, now nearing a decade in age, has enabled, among other capabilities, measurement of genome-wide sequence features at unprecedented scale and resolution. </p><p>In this dissertation, I describe work to understand the genetic underpinnings of non-Hodgkin’s lymphoma through exploration of the epigenetics of its cell of origin, initial characterization and interpretation of driver mutations, and finally, a larger-scale, population-level study that incorporates mutation interpretation with clinical outcome. </p><p>In the first research chapter, I describe genomic characteristics of lymphomas through the lens of their cells of origin. Just as many other cancers, such as breast cancer or lung cancer, are categorized based on their cell of origin, lymphoma subtypes can be examined through the context of their normal B Cells of origin, Naïve, Germinal Center, and post-Germinal Center. By applying integrative analysis of the epigenetics of normal B Cells of origin through chromatin-immunoprecipitation sequencing, we find that differences in normal B Cell subtypes are reflected in the mutational landscapes of the cancers that arise from them, namely Mantle Cell, Burkitt, and Diffuse Large B-Cell Lymphoma. </p><p>In the next research chapter, I describe our first endeavor into understanding the genetic heterogeneity of Diffuse Large B Cell Lymphoma, the most common form of non-Hodgkin’s lymphoma, which affects 100,000 patients in the world. Through whole-genome sequencing of 1 case as well as whole-exome sequencing of 94 cases, we characterize the most recurrent genetic features of DLBCL and lay the groundwork for a larger study. </p><p>In the last research chapter, I describe work to characterize and interpret the whole exomes of 1001 cases of DLBCL in the largest single-cancer study to date. This highly-powered study enabled sub-gene, gene-level, and gene-network level understanding of driver mutations within DLBCL. Moreover, matched genomic and clinical data enabled the connection of these driver mutations to clinical features such as treatment response or overall survival. As sequencing costs continue to drop, whole-exome sequencing will become a routine clinical assay, and another diagnostic dimension in addition to existing methods such as histology. However, to unlock the full utility of sequencing data, we must be able to interpret it. This study undertakes a first step in developing the understanding necessary to uncover the genomic signals of DLBCL hidden within its exomes. However, beyond the scope of this one disease, the experimental and analytical methods can be readily applied to other cancer sequencing studies.</p><p>Thus, this dissertation leverages next-generation sequencing analysis to understand the genetic underpinnings of lymphoma, both by examining its normal cells of origin as well as through a large-scale study to sensitively identify recurrently mutated genes and their relationship to clinical outcome.</p> / Dissertation

Skeletal dysplasias and dysostoses are a genotypically and phenotypically diverse group of disorders that affect the growth, development and maintenance of cartilage and bone. General disorders of bone affecting bones and cartilage throughout the body have been referred to as skeletal dysplasias, whereas defects that selectively affect certain bones or bone groups are called skeletal dysostoses. Despite this distinction, modern molecular techniques are showing that this division is somewhat superficial, given the similarity in their underlying causes. Although the rate of disease gene discovery has grown substantially since the advent of next-generation sequencing technologies, most of the disorders have unknown molecular defects. Skeletal dysostoses are rarely observed, occurring at such low incidence levels that no comprehensive study has ascertained their frequency. The effects range from mild growth inhibition to complete absence of entire bone groups. The axial skeleton is most often involved in skeletal dysostoses with common symptoms including poorly formed cranial bones, mandible, ribs and vertebrae. Several important signaling pathways control the migration and formation of mesodermal cells, which eventually differentiate into many elements of the vertebral column. The importance of these pathways, namely the T-box transcription factors, Wnt, Notch, and Smad pathways are integrally involved in the very early stages of vertebral development. Currently, the most cost-effective method of pathogenic gene discovery for rare genetic diseases is exome sequencing. Utilizing this technology, as well as SNP arrays for identity-by-descent loci mapping, two independent skeletal dysostosis cases with similar phenotypes were studied to determine pathogenic candidate genes. Next-generation sequencing and identity-by-descent analysis revealed a possible candidate gene, PM20D2, in one proband. The gene includes peptidase dimerization, peptidase M20/M25/M40, and N-myristolylation domains based on predicted functional analysis. It is implicated in various metabolic activities, having hydrolase, protein binding, and metallopeptidase molecular functions. Further investigation into this gene, as well as further studies of these probands is needed to understand the role, if any, the defect plays in the disease.

Suicidal behavior represents the most severe, yet inherently preventable, outcome of psychiatric disease. Despite tremendous efforts to improve the awareness and treatment of psychiatric illness, suicidal behavior rates have been on the rise. The greatest challenge to confronting this crisis is the effective identification and treatment of those at risk for suicide. This challenge has been difficult to address due, in part, to the lack of a clear biological basis for suicidal behavior. Toward addressing this knowledge gap, evidence has been identified of a significant heritable component to suicidal behavior. Subsequent genetic research efforts have focused on the examination of common sites of genetic variation within candidate genes and throughout the genome. These efforts have identified many potentially important risk loci, but the majority of the risk expected to arise from genetic variation remains unexplained by current data. The primary objective of this dissertation was to examine the contribution of largely unexplored rare and potentially damaging genetic variation within suicidal behavior. To do this, targeted next-generation sequencing approaches were employed within a cohort of individuals diagnosed with bipolar disorder, a group particularly enriched for suicidal behavior. Sequence data was generated that examined essentially all protein-coding regions of the human genome (“exome”), with expanded sequencing around and within candidate genes hypothesized to play a role in suicidal behavior risk. The secondary objective of this dissertation focused on the assessment of rare variation within bipolar disorder through sequenced pedigrees and followup in a large collaborative bipolar disorder versus normal control sequencing dataset. These objectives were addressed through the thoughtful application of diverse and complimentary methods. These methods were selected to investigate individual variants, genes, and biological pathways. This approach offered examinations of the potential impact of rare genetic variation within focused regions and across complex biological process pathways that could be disrupted through damaging variation in many different genes. The presented efforts represent the largest examinations of rare functional variation with suicidal behavior and bipolar disorder performed, to date. No individual variant or gene survived correction for multiple testing for either phenotype. These results are consistent with other initial sequencing efforts in complex psychiatric phenotypes, offering conclusions that larger samples will likely be required to identify significant associations for single variants and genes. Within pathway analyses, however, we identified a significant enrichment of rare damaging variation that segregated within bipolar disorder pedigrees in genes that have been implicated in de novo studies of autism. This finding was further replicated within three large case/control sequencing samples, providing support to emerging evidence of a potential overlap of risk loci for autism and bipolar disorder. Many additional results approached significance that bear further consideration. These results offer potential candidate genes and pathways that could be utilized in future sequencing efforts for suicidal behavior and bipolar disorder. In addition, highly valuable resources in the form of datasets strongly enriched for novel rare loci were produced that can significantly contribute to ongoing efforts to investigate bipolar disorder and suicidal behavior. These data can be used in combination with other emerging datasets to generate more powerful meta- and mega-analyses to confidently identify risk loci for both phenotypes.

Novel technologies for genome analysis have provided almost unlimited opportunities to uncover structural gene variants behind human disorders. Whole exome sequencing (WES) is especially useful for understanding rare Mendelian conditions, because it reduces the requirements for a priori clinical data, and can be applied on a small number of patients. However, supporting functional data on the effect of specific gene variants are often required to power these findings. A variety of methods and biological model systems exists for this purpose. Among those, induced pluripotent stem cells (iPSCs), which are capable of self-renewal and differentiation, stand out as an alternative to animal models. In papers I and II we took advantage of WES to identify gene variants underlying autosomal recessive pure hair and nail ectodermal dysplasia (AR PHNED) as well as autosomal dominant familial visceral myopathy (FVM). We identified a homozygous variant c.821T&gt;C (p.Phe274Ser) in the KRT74 gene as the causative mutation in AR PHNED, supported by the fact that Keratin-74 was undetectable in hair follicles of an affected family member. In a family segregating FVM we found a heterozygous tandem base substitution c.806_807delinsAA (p.(Gly269Glu)) in the ACTG2 gene in the affected members. This novel variant is associated with a broad range of visceral symptoms and a variable age of onset. In Paper III we explored the similarity between clonally derived iPSC lines originating from a single parental fibroblast line and we highlighted the necessity to use lines originating from various donors in disease modeling because of biological variation. Paper IV focused on how the genomic integrity of iPSCs is affected by the choice of reprogramming methods. We described several novel cytogenetic rearrangements in iPSCs and we identified a chromosome 5q duplication as a candidate aberration for growth advantage. In summary, this doctoral thesis brings novel findings on unreported disease-causing variants, as supported by extensive genetic analysis and functional data. A novel molecular mechanism behind AR PHNED is presented and the phenotypic spectrum associated with FVM is expanded. In addition, the thesis brings novel understanding of benefits and limitations of the iPSC technology to be considered for disease modeling.

<p>Muscular dystrophy is a devastating disease for which no cures or preventative treatments are currently available. There has been great progress in the identification of genetic mutations that cause some forms of muscle disease; however, genetic heterogeneity is the rule rather than the exception. Molecular diagnosis of these disorders is challenging because the large number of known causative genes makes exhaustive clinical testing very expensive and the similarity of clinical presentation makes selection of likely candidate genes difficult. The Duke Limb-Girdle Muscular Dystrophy (LGMD) group strives to identify the mutations causing disease in affected members of families with molecularly undiagnosed, dominantly inherited forms of muscular dystrophy while potentially identifying and characterizing genes and mutations that have not been previously shown to be involved in muscle disease pathogenesis.</p><p>One strategy to identify disease-causing mutations in families with many affected individuals is to perform linkage analysis to identify a region of the genome that is likely to contain the disease-causing variant followed by candidate gene sequencing within the peak to isolate the mutation. Linkage analysis was performed for a family with a molecularly undiagnosed form of scapuloperoneal muscular dystrophy. Three suggestive linkage regions were identified on chromosomes 3, 4, and 14 respectively. Each affected individual in the family carried a heterozygous deletion of a lysine residue at position 1784 in exon 37 of MYH7, which maps to one of the linked loci. Other groups have also identified this variant in individuals with similar symptoms. The deletion of the lysine residue is likely the causative mutation in this family.</p><p>An alternate strategy for mutation identification is exome capture and sequencing. This approach may be used to screen genes that are known to be involved in muscle disease pathogenesis while potentially identifying candidate disease-causing variants in genes that have not previously been shown to be involved in the disease. This strategy was evaluated through the analysis of exome sequencing data obtained from multiple affected family members in two families with different muscle disease symptoms. Variant filtration and Sanger sequencing follow-up were performed to identify those variants located in genes known to be involved in skeletal and/or cardiac muscle disease that fit the expected inheritance patterns in each family and are rarely identified in the general population, and likely functional. The mutation, desmin IVS3+3 A>G, was identified in the first family, and the mutation, filamin C p.W2710X, was identified in the second family. These mutations segregated with affection status in the complete families. They have been identified in other individuals with similar phenotypes and were found to affect the proteins by functional analyses. Therefore, the mutations likely caused disease in affected members of these two families as well.</p><p>For families in which initial analysis of exome sequencing data does not reveal a likely disease-causing variant in genes in which mutations are known to cause skeletal muscle disease, it is necessary to determine whether the exome sequencing data provided deep, high-quality coverage at each base in their coding and splicing regions. Coverage variability in genes known to be involved in skeletal and/or cardiac muscle disease was examined for eleven example exomes. After duplicate removal, the mean coverage per exome ranged from 42X to 84X, and 85.7%-92.8% of the expected capture region was covered at ¡Ý10X as calculated with the command GATK ¨CDepthOfCoverage. Depth and quality of coverage were examined in the coding and splicing regions of 102 genes that are known to be involved in skeletal and/or cardiac muscle disease; they were found to vary across different exome captures. Some regions were not well covered in any of the exomes sequenced. The results indicate that while many causative genes are well-covered, gaps exist which may interfere with the identification of some disease-causing mutations. In some cases, these gaps may be filled by increasing overall coverage.</p><p>The initial screen indicated that mutations in known disease genes may be frequent in the Duke LGMD families, so the use of a single exome in a family to screen genes that are known to be involved in muscle disease was attempted. Exome sequence analysis was performed for single affected individuals from seven families with multiple affected family members. For each exome, the candidate set was restricted to variants found within the coding and splicing regions of 102 skeletal and/or cardiac muscle disease genes. Strict filters were applied to identify extremely rare, high quality variants located within those genes, and Sanger sequencing follow-up was performed to determine which variants segregated with affection status in the complete family. In five of the seven families, potential disease-causing variants were found in a heterozygous state in all affected individuals. When possible, functional testing of these alleles, preferably in an in vivo model, would be beneficial to assist in determining whether each allele is likely to be pathogenic.</p><p>The described work utilized linkage analysis followed by candidate gene sequencing as well as exome capture and sequencing to attempt to isolate the mutations responsible for muscular dystrophy in affected family members. While linkage analysis may continue to be important to identify regions of the genome that are identical by descent in extended families, the use of next generation sequencing technologies to isolate mutations that cause rare, highly penetrant disorders in smaller families can be effective. However, it is necessary to examine the depth and quality of coverage within the consensus coding and splicing regions of genes in which mutations are known to cause a similar phenotype to that found in a family of interest. In the future, functional follow-up will be important to assist in the interpretation of variants of unknown significance.</p> / Dissertation

Body mass varies considerably between different mammals and this variation is largely accounted for by a difference in total cell number rather than individual cell size. Insights into mechanisms regulating growth can therefore be gained by understanding what governs total cell number at any one point. In addition, control of cell proliferation and programmed cell death is fundamental to other areas of research such as cancer and stem cell research. Microcephalic Primordial Dwarfism (MPD) is a group of rare Mendelian human disorders in which there is an extreme global failure of growth with affected individuals often only reaching a height of around one metre in adulthood. To date, all identified disease genes follow an autosomal recessive mode of inheritance and encode key regulators of the cell cycle, where mutations impact on overall cell number and result in a substantially reduced body size. MPD therefore provides a valuable model for examining genetic and cellular mechanisms that impact on growth. The overall aims of this thesis were to identify novel disease causing genes, as well as provide further characterisation of known disease causing genes, through the analysis of whole exome sequencing (WES) within a large cohort of MPD patients. Following the design and implementation of an analytical bioinformatics pipeline, deleterious mutations were identified in multiple disease genes including LIG4 and XRCC4. Both genes encode components of the non-homologous end joining machinery, a DNA repair mechanism not previously implicated in MPD. Additionally, the pathogenicity of novel mutations in subunits of a protein complex involved in chromosome segregation was assessed using patient-derived cells. These findings demonstrate WES can be successfully implemented to identify known and novel disease causing genes within a large heterogeneous cohort of patients, expanding the phenotype of known disorders and improving diagnosis as well as providing novel insights into intrinsic cellular mechanisms critical to growth.