The rare disease pulmonary arterial hypertension (PAH) results in high blood pressure in the lung caused by narrowing of lung arteries. Genes causative in PAH were discovered through family studies and very often harbour rare variants. However, the genetic cause in heritable (31%) and idiopathic (79%) PAH cases is not yet known but are speculated to be caused by rare variants. Advances in high-throughput sequencing (HTS) technologies made it possible to detect variants in 98% of the human genome. A drop in sequencing costs made it feasible to sequence 10,000 individuals including 1,250 subjects diagnosed with PAH and relatives as part of the NIHR Bioresource - Rare (BR-RD) disease study. This large cohort allows the genome-wide identification of rare variants to discover novel causative genes associated with PAH in a case-control study to advance our understanding of the underlying aetiology. In the first part of my thesis, I establish a phenotype capture system that allows research nurses to record clinical measurements and other patient related information of PAH patients recruited to the NIHR BR-RD study. The implemented extensions provide a programmatic data transfer and an automated data release pipeline for analysis ready data. The second part is dedicated to the discovery of novel disease genes in PAH. I focus on one well characterised PAH disease gene to establish variant filter strategies to enrich for rare disease causing variants. I apply these filter strategies to all known PAH disease genes and describe the phenotypic differences based on clinically relevant values. Genome-wide results from different filter strategies are tested for association with PAH. I describe the findings of the rare variant association tests and provide a detailed interrogation of two novel disease genes. The last part describes the data characteristics of variant information, available non SQL (NoSQL) implementations and evaluates the suitability and scalability of distributed compute frameworks to store and analyse population scale variation data. Based on the evaluation, I implement a variant analysis platform that incrementally merges samples, annotates variants and enables the analysis of 10,000 individuals in minutes. An incremental design for variant merging and annotation has not been described before. Using the framework, I develop a quality score to reduce technical variation and other biases. The result from the rare variant association test is compared with traditional methods.

Mitochondria are essential cellular organelles and the location of the electron transport chain, the site of the majority of energy production in the cell. Mitochondria contain their own circular genome approximately 16,000 base pairs in length. The mitochondrial genome (mtDNA) encodes 11 protein-coding genes essential for the electron transport chain, 22 tRNA genes, and two rRNA genes. Mitochondrial malfunction occurs in many diseases, and changes in the mitochondrial genome lead to numerous disorders. Multiple mitochondrial haplotypes and sequence features are associated with Alzheimer's disease. In this dissertation we utilized TreeScanning, an evolutionary-based haplotype approach to identify haplotypes and sequence variation associated with specific phenotypes: Alzheimer's disease case-control status, mitochondrial copy number, and 16 neuroimaging phenotypes related to Alzheimer's disease neurodegeneration. In the first two studies we utilized 1007 complete mitochondrial genomes from participants in the Cache County Study on Memory Health and Aging. First, individuals with mitochondrial haplotypes H6A1A and H6A1B showed a reduced risk of AD. Our study is the largest to date and the only study with complete mtDNA genome sequence data. Next, each cell contains multiple mitochondria, and each mitochondrion contains multiple copies of its own circular genome. The ratio of mitochondrial genomes to nuclear genomes is referred to as mitochondrial copy number. Decreases in mitochondrial copy number are known to occur in many tissues as people age, and in certain diseases. Three variants belonging to mitochondrial haplogroups U5A1 and T2 were significantly associated with higher mitochondrial copy number in our dataset. Each of these three variants was associated with higher mitochondrial copy number and we suggest several hypotheses for how these variants influence mitochondrial copy number by interacting with known regulators of mitochondrial copy number. Our results are the first to report sequence variation in the mitochondrial genome that lead to changes in mitochondrial copy number. The identification of these variants that increase mtDNA copy number has important implications in understanding the pathological processes that underlie these phenotypes. Lastly, we used an endophenotype-based approach to further characterize mitochondrial genetic variation and its relationship to risk markers for Alzheimer's disease. We analyzed longitudinal data from non-demented, mild cognitive impairment, and late onset Alzheimer's disease participants in the Alzheimer's Disease Neuroimaging Initiative with genetic, brain imaging, and behavioral data. Four clades were associated with three different endophenotypes: whole brain volume, percent change in temporal pole thickness, and left hippocampal atrophy over two years. This was the first study of its kind to identify mitochondrial variation associated with brain imaging endophenotypes of Alzheimer's disease. Together, these projects provide evidence of mtDNA involvement in the risk and physiological changes of Alzheimer's disease.

Les progrès technologiques récents nous permettent d'accéder à la variation des génomes complets ce qui nous ouvre la porte d'une meilleure compréhension de leur diversification via des approches de génomique des populations et de génomique du paysage. Ce travail de thèse se base sur l'analyse des données de génomes complets (WGS) pour caractériser la diversité génétique des petits ruminants (chèvre et moutons) et rechercher les bases génétiques d'adaptations locales.Dans un premier temps, ce travail appréhende un aspect méthodologique et examine la précision et le biais de différentes approches d'échantillonnage des génomes pour caractériser la variabilité génétique, en les comparant aux données WGS. Nous mettons en évidence un fort biais des approches classiques (i.e. puces à ADN, capture de l'exome) ainsi que des séquençages de génomes à faibles taux de couverture (1X et 2X), et nous suggérons des alternatives basées sur un échantillonnage aléatoire de marqueurs dont la densité est variable selon les objectifs d'étude (évaluation de la diversité neutre, déséquilibre de liaison, signatures de sélection). Le jeu de données produit a permis d'évaluer l'état des ressources génétiques de différentes populations domestiques (races locales marocaines, iraniennes, races industrielles) et sauvages (aegagre, mouflon asiatique). Nous relevons une très forte diversité génétique dans les populations indigènes et sauvages qui constituent des réservoirs d'allèles et peuvent jouer un rôle important pour préserver le potentiel adaptatif des petits ruminants domestiques dans un contexte de changement climatique. L'étude plus approfondie des populations de chèvres du Maroc montre une forte diversité génétique faiblement structurée géographiquement, et met en évidence des portions de génome présentant des signaux de sélection. Leur étude montre l'existence de mécanismes adaptatifs potentiellement différents selon les populations (e.g. transpiration/halètement dans l'adaptation probable à la chaleur).Enfin, nous explorons les bases génétiques de l'adaptation locale à l'environnement chez les moutons et chèvres via une approche de génomique de paysage. En scannant les génomes de 160 moutons et 161 chèvres représentant la diversité éco-climatique du Maroc, nous identifions de nombreux variants et gènes candidats qui permettent d'identifier les voies physiologiques potentiellement sous-jacentes à l'adaptation locale. En particulier, il apparait que les mécanismes respiratoires et les processus cardiaques joueraient un rôle clé dans l'adaptation à l'altitude. Les résultats suggèrent que les chèvres et moutons ont probablement développé différents mécanismes adaptatifs pour répondre aux mêmes variations environnementales. Cependant, nous identifions plusieurs cas probables de voies adaptatives communes à plusieurs espèces. Par ailleurs, nous avons caractérisé les patrons de variations du niveau de différenciation de régions chromosomiques sous sélection en fonction de l'altitude. Cela nous permet de visualiser la diversité des réponses adaptatives selon les gènes (par exemple, sélection de variants à faible et/ou haute altitude). Ainsi, ce travail pose les bases de la compréhension de certains mécanismes d'adaptation locale. / Recent technological developments allow an unprecedented access to the whole genome variation and would increase our knowledge on genome diversification using population and landscape genomics. This work is based on the analysis of Whole Genome Sequence data (WGS) with the purpose of characterising genetic diversity in small ruminants (sheep and goats) and exploring genetic bases of local adaptation.First, we addressed a methodological aspect by investigating the accuracy and possible bias in the widely used genotyping approaches to characterize genetic variation in comparison with WGS data. We highlighted strong bias in conventional approaches (SNP chips and exome capture) and also in low-coverage whole genome re-sequencing (1X and 2X), and we suggested effective solutions based on sampling panels of random markers over the genome depending the purpose of the study (assessing neutral diversity, linkage disequilibrium, selection signatures). The various datasets produced allowed assessing genetic resources in various domestic (Moroccan and Iranian indigenous breeds and industrials) and wild populations (bezoars and Asiatic mouflons). We identified a very high diversity in indigenous and wild populations. They constitute a reservoir of alleles allowing them to play a possible key role in the preservation of these species in the context of global changes. The deep study of Moroccan goats showed a high diversity that is weakly structured in geography and populations, and highlighted numerous genomic regions showing signatures of selection. These regions identified different putative adaptive mechanisms according to the population (e.g. panting/sweating to adapt to warm/desert environment).Then, we explored genetic bases of local adaptation to the environment in sheep and goats using a landscape genomics framework. We scanned genomes of 160 sheep and 161 goats representing the eco-climatic Moroccan-wide diversity. We identified numerous candidate variants and genes, which allowed for identifying physiological pathways possibly underlying local adaptation. Especially, it seems that respiration and cardiac process have key roles in the adaptation to altitude. Our results suggest dissimilar adaptive mechanisms for the same environment in sheep and goats. However, we highlighted several cases of common metabolic pathways in different species. Moreover, we characterized some patterns for the variation of genetic differentiation in some candidate genomic regions over environmental gradients. This allowed us to visualise different adaptive reaction depending genes. This work points the way towards a better understanding of some mechanisms underlying local adaptation.