The population level bias towards right-handedness in humans implies left-hemisphere dominance for fine motor control. Left-handedness and reduced cerebral asymmetry have been linked to neurodevelopmental disorders such as dyslexia. Understanding the biology of these traits at a genetic level is crucial for understanding the relationship between handedness and neurodevelopmental disorders. Here I present genome-wide association study (GWAS) meta-analyses for both relative hand skill (handedness, n = 728) and reading-related traits (n = 548) in individuals with dyslexia. I uncovered a genome-wide significant association in an intron of PCSK6 associated with relative hand skill. PCSK6 is a protease that cleaves NODAL proprotein into an active form, and NODAL determines the development of left/right (LR) asymmetry in bilaterians. I performed pathway analyses of the GWAS data that revealed handedness is determined in part by the mechanisms that establish left/right (LR) asymmetry early in development, such as NODAL signalling and ciliogenesis. This finding replicated in a general population cohort unaffected with neurodevelopmental disorders (n = 2,666). A key stage in LR asymmetry development is the rotation of cilia that creates a leftward flow of NODAL. Candidate genes for dyslexia are involved in both neuronal migration and ciliogenesis. Ciliopathies can cause not only LR body asymmetry phenotypes, but also cerebral midline phenotypes such as an absent corpus callosum. Furthermore, I identified a genome-wide significant association with non-word reading located in an intron of MAP1B, a gene involved in neuronal migration that causes an absent corpus callosum when disrupted in mice. However, this finding did not replicate in two independent cohorts with dyslexia (n = 156 & 199), or in the general population cohort (n = 2,359). Though these cohorts had inadequate reading measures and poorly matched ascertainment for dyslexia. I also performed copy number variation (CNV) pathway and burden analyses of 920 individuals with dyslexia and 1,366 unselected controls, but did not find that rare CNVs play a major role in the etiology of dyslexia. Based on these results I propose that common variants in genes responsible for ciliogenesis and corpus callosum development influence traits such as handedness and reading ability.

The post human genome sequence era has begun to explore various aspects of the functional genome in relation to disease including gene expression, genetic variation and epigenetics. The genetic determinants of common and complex phenotypes are difficult to resolve even though their heritability is recognised. Recent genome-wide association studies (GWAS) for common diseases has identified many new disease susceptibility associated loci. These loci often lie in non-coding regions of the genome and disease associated genetic variants are proposed to act by modulating gene expression. This thesis investigated genetic variation as determinants of gene expression in the context of the immune system especially focused on the innate immune and inflammatory responses. Different primary human immune cell types were collected from healthy volunteers of European ancestry to achieve this. In order to identify genetic variants associating with gene expression, expression quantitative trait loci (eQTL) mapping was conducted in a cell type specific manner. The primary dataset (n=288) consists of CD19⁺ B-cells from the adaptive immune system and CD14⁺ monocytes from the innate immune system. 78% of the total cis eQTL were found to be cell type specific and include genes relating to their roles in the immune response. Trans eQTL showed greater cell type specificity and include master regulatory eQTL on the LYZ locus at chromosome 12q15 in monocytes and the KLF4 (9p31) in B-cells. The identified eQTL are implicated in association with autoimmune disease susceptibility including inflammatory bowel disease, diabetes and rheumatoid arthritis. The second analysed dataset (n=64) consists of CD14+ monocytes and macrophages differentiated ex vivo. Macrophages are involved in many inflammatory diseases as well as in the innate immune response. The differential gene expression and eQTL mapping analyses were conducted to investigate macrophages specific gene expression signatures and associations to genetic variants. Macrophage eQTL are involved in signal transduction for the inflammatory response (IL1RN and STAT4) and lipid metabolism (PPARG) with implication for metabolic disease association. The eQTL analyses using primary immune cell types provide insights into genetic variation in association to gene expression which is involved in autoimmunity and disease susceptibility.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterised clinically by rapidly progressive paralysis leading ultimately to death from respiratory failure. There is no cure for ALS and no definitive explanation for the onset and rapid progression of motor neuron degeneration. Genetics is a known risk factor for a portion of familial cases. However, the role of genetics in the commoner sporadic form of the disease is poorly understood, although numerous genes have been implicated. The primary aim of this thesis project is to uncover the genetic causes that underlie ALS. To accomplish this goal, the main focus of this thesis is to perform genome-wide association analysis of sporadic ALS using high density SNP arrays. This thesis describes the first and the largest genome-wide association studies of ALS to date. Results demonstrate that there is no single large effect susceptibility variant underlying a large proportion of ALS, such as ApoE in Alzheimer’s disease. However, the genotyping data has been made publically available and the digital nature of this data means that it is a resource that can grow with future studies. Beyond genome-wide association, this thesis describes work using linkage, haplotype and sequence analysis to investigate the genetic overlap between ALS and frontotemporal dementia. Lastly, this thesis presents a novel method for linkage analysis using high throughput SNP arrays. Ultimately, it is hoped that by uncovering the genes that cause ALS, such knowledge will shed light on the pathogenic mechanisms underlying motor neuron degeneration and potentially lead to new rational therapies effective in slowing or even halting disease progression.

The fundamental theme my thesis explores is the relationship between genetic variation and phenotypic variation. It addresses three main questions. What is the genetic architecture of traits in the HS? How can sequence information help identifying the sequence variants and genes responsible for phenotypic variation? Are the genetic factors contributing to phenotypic variation in the rat homologous to those contributing to variation in the same phenotype in the mouse? To address these questions, I analysed data collected by the EURATRANS consortium on 1,407 Heterogeneous Stock (HS) rats descended from eight inbred strains through sixty generations of outbreeding. The HS rats were genotyped at 803,485 SNPs and 160 measures relevant to a number of models of disease (e.g. anxiety, type 2 diabetes, multiple sclerosis) were collected. The eight founders of the Stock were genotyped and sequenced. I identified loci in the genome that contribute to phenotypic variation (Quantitative Trait Loci, QTLs), and integrated sequence information with the mapping results to identify the genetic variants underlying the QTLs. I made some important observations about the nature of genetic architecture in rats, and how this compares to mice and humans. I also showed how sequence information can be used to improve mapping resolution, and in some cases to identify causal variants. However, I report an unexpected observation: at the majority of QTLs, the genetic effect cannot be accounted for by a single variant. This finding suggests that genetic variation cannot be reduced to sequence variation. This complexity will need to be taken into account by studies that aim at unravelling the genetic basis of complex traits.

Obesity is a serious public health crisis and recent estimates of its incidence are the highest in United States history, with 35% and 17% of American adults and children affected, respectively. The clinical definition of adult obesity is operationalized as a body mass index (BMI) greater than 30 kg/m2. Although the prevalence of common obesity has increased dramatically over the past 30 years–largely thought to be due to changes in the environment, such as high calorie diets and sedentary lifestyles—twin and family studies have shown consistently that relative body weight is under considerable genetic influence in both children and adults, with heritability estimates ranging from 40% to 90%. Elucidating the genetic and environmental liability to relative body weight is an important public health endeavor. To further our understanding of the genetics of BMI and common complex obesity, several studies are described that integrate clinical, twin, and genome-wide association (GWAS) methodology in the context of genetic risk scores, clinical risk prediction, development across adolescence into adulthood, and comorbidity with depression symptoms and smoking behavior. First, in two cross-sectional genetic association studies, the utility of genetic risk sum scores (GRSS) were assessed, which summarize the total number of risk alleles, as an alternative form of replication and for potential clinical utility for obesity risk prediction. Next, since there has been only limited research on when during development BMI-associated variants begin influencing BMI, a longitudinal twin study was utilized to assess the effects of adult-validated BMI-SNPs across adolescence into adulthood. In addition, obesity is comorbid with numerous medical conditions including cardiovascular disease, insulin-resistance and some forms of cancer, as well as, various psychiatric disorders including eating disorders, mood disorders, and substance use. The next series of studies aimed to understand phenotypic and genetic associations between BMI/obesity and binge eating disorder (BED), depression symptoms and smoking behavior. Using a clinical sample of overweight and obese women with and without BED, the relationship of BED, food intake and internalizing symptoms of depression and anxiety was examined. Next, twin study methodology was used to investigate if shared genetic and/or environmental liability was responsible for phenotypic associations found between BMI, depression symptoms, and impulsivity. Finally, a genetic association study aimed at investigating whether genetic variants were associated with multiple behaviors, body composition and smoking behavior, or were trait-specific is presented. By utilizing several samples and methodologies and by pursuing methods development, a comprehensive approach is presented that is hoped to represent a more powerful evidence-based strategy to understanding the genetic and environmental determinants of BMI and common complex obesity, along with associated depression symptoms and smoking behavior.

Diverses lésions ostéochondrales peuvent affecter les articulations des jeunes chevaux et réduire leurs futures performances en course. L’objectif de cette thèse est d’identifier les régions du génome, appelées locus à caractère quantitatif (QTL), associées avec des caractères mesurant l’ostéochondrose (OC) enregistrés dans le programme GENEQUIN sur une population de Trotteurs Français. Le génotypage a été réalisé à l’aide de la puce SNP Illumina BeadChip EquineSNP50, qui est dense et permet d’exploiter le déséquilibre de liaison par des analyses d’association. Ces analyses sont sujettes à certains problèmes en présence d’une structure familiale des données. Dans la première partie de la thèse, une comparaison de la puissance et de la robustesse d’un choix restreint de méthodes d’analyses est effectuée. L’originalité de ce travail réside dans la dérivation algébrique des moments des distributions des statistiques de test comparées, donnant ainsi plus de généralité à nos résultats et permettant une meilleure compréhension des différences. Les résultats peuvent notamment servir à l’optimisation du dispositif expérimental. La deuxième partie est consacrée à la cartographie des régions QTL des caractères mesurant l’OC en différents sites articulaires dans une population de 583 Trotteurs Français. Cette étude a permis de mettre en évidence plusieurs régions QTL d’effets moyens et faibles à un niveau significatif mais pas hautement significatif. Nous montrons que l’OC est un caractère polygénique et qu’aucun QTL, ayant un effet à la fois sur l’OC du jarret et l’OC du boulet, n’est détectable dans ce protocole QTL, ce qui infirme l’hypothèse simple d’une cause génétique commune de la sensibilité à cette maladie sur les différents sites anatomiques. Suite à ces travaux, l’identification des gènes candidats et des mutations causales devrait clarifier la physiopathologie moléculaire de l’OC et ainsi permettre de développer des stratégies efficaces pour l’évaluation des risques. Pendant ce temps, les marqueurs peuvent être utilisés dans un contexte de sélection assistée par marqueurs afin d’améliorer la santé et le bien-être du cheval. / Osteochondral lesions are commonly observed in young horses and may be responsible for reduced performances in racing. The purpose of the PhD thesis was to identify genome regions, called quantitative trait loci (QTL), associated with various traits measuring osteochondrosis (OC) and recorded in the GENEQUIN program in a population of French Trotters horses. Genotyping was performed using the EquineSNP50 Illumina high density chip, which allows to exploit the linkage disequilibrium with genome-wide association studies. These analyses are subject to several problems in presence of family structure. We hence first proposed a comparison of power and robustness of a limited choice of models for this type of analysis. The originality of this work lies in the algebraic derivation of the distribution moments of the test statistics compared, making the outcome of this comparison more general and allowing a better understanding of differences. The results can be used to establish an experimental design. The second part was devoted to the QTL fine mapping of traits that measure OC in different joint sites. This study highlighted several significant QTL with low and medium effects but none of them were highly significant. We showed that OC is a polygenic trait and we were not able to identify QTL affecting both OC on the hock and the fetlock, rejecting the hypothesis of a single genetic determinism of susceptibility to this desease accross anatomical sites. Further studies will now focus on the identification of candidate genes and screening for mutation in an attempt to clarify the molecular physiopathology of OC and develop efficient strategies for risk assessment. Meanwhile, markers could be used in a marker-assisted selection context to improve horse health and welfare.

We developed a pipeline to identify the copy number polymorphisms (CNPs) in the Northern Swedish population using whole genome sequencing (WGS) data. Two different methodologies were applied to discover CNPs in more than 1,000 individuals. We also studied the association between the identified CNPs with the expression level of 438 plasma proteins collected in the same population. The identified CNPs were summarized and filtered as a population copy number matrix for 1,021 individuals in 243,987 non-overlapping CNP loci. For the 872 individuals with both WGS and plasma protein biomarkers data, we conducted linear regression analyses with age and sex as covariance. From the analyses, we detected 382 CNP loci, clustered in 30 collapsed copy number variable regions (CNVRs) that were significantly associated with the levels of 17 plasma protein biomarkers (p < 4.68×10-10).

The selection on genetic values predicted from markers could substantially increase the rate of genetic gain in animals by increasing accuracy of prediction and reducing generation interval, especially for difficult to measure traits, such as feed efficiency. Feed efficiency is the most important trait in animal production due to its impacts on cost of production and environmental factors. Many metrics measure the feed efficiency, such as ratio of gain to feed (FER), the ratio of feed to gain (FCR) and residual feed intake (RFI). Nevertheless, in ovine, no study with the aim of understand the genetic variants or the accuracy of genomic estimated breeding value (GEBV) for feed efficiency traits was published yet. Moreover, before to apply the genomic information, it is necessary to understand and characterized the population structure, for instance, by linkage disequilibrium (LD). Both genome-wide association studies (GWAS) and genomic selection (GS) leverage LD between marker and causal mutation. Based on the above considerations, the aim of this study was to map LD in ovine, characterized by Brazilian Santa Inês sheep; to search genetic variants for feed efficiency traits (FER, FCR and RFI) through GWAS; and to verify the accuracy of GEBV for RFI. In total, 396 samples (animals) of Longissimus dorsi muscle were collect. A high-density panel of SNP (Illumina High-Density Ovine SNP BeadChip®) comprising 54,241 SNPs was used to obtain the genotyping data. The phenotype data was comprised of 387 animals. The average LD between adjacent markers for two LD metrics, r² and |D\'|, were 0.166 and 0.617, respectively. The degree of LD estimated was lower than reported in other species and it was characterized by short haplotype blocks. Consequently, for genomic analyses, high-density panels of marker are recommended. Many markers were associated to feed efficiency traits in GWAS, mainly to RFI trait. Few candidate genes were reported in this study, highlighting NRF-1 (nuclear respiratory factor 1), which controls mitochondrial biosynthesis, the most important process responsible by a great fraction of the produced energy. Finally, we verified the accuracy of GEBV for RFI using few Bayesian regression models, and we found low accuracy, ranging from 0.033 (BayesB with π=0.9912) to 0.036 (BayesA), which might be explained by the low relationship among animals and small training population. / A seleção com base nos valores genéticos genômicos preditos pode aumentar substancialmente a taxa de ganho genético em animais por meio do aumento da acurácia de predição e redução do intervalo de gerações, especialmente para características de difícil e/ou onerosa mensuração, como eficiência alimentar. A eficiência alimentar é uma das características mais importantes na produção animal devido principalmente aos seus impactos econômicos e ambientais. Muitas métricas representam a eficiência alimentar, por exemplo: a relação do ganho de peso e consumo alimentar (EA), a proporção do consumo alimentar e ganho de peso (CA) e o consumo alimentar residual (CAR). Em ovinos, nenhum estudo com o objetivo de buscar variantes genéticas ou verificar a acurácia do valor genético genômico estimado para eficiência alimentar foi publicado. Adicionalmente, antes de aplicar a informação genômica, é necessário compreender e caracterizar a estrutura da população, como por meio do desequilíbrio de ligação (LD). O estudo de associação genômica (GWAS) e seleção genômica (GS) consideram o LD entre marcador e a mutação causal. Com base nas considerações acima, o objetivo deste estudo foi mapear o LD em ovinos, caracterizado pela raça ovina Santa Inês; localizar variantes genéticas para as características de eficiência alimentar (EA, CA e CAR) utilizando a abordagem GWAS; e verificar a acurácia da estimação dos valores genéticos genômico para o CAR. No total, foram coletadas 396 amostras (animais) do músculo Longissimus dorsi, para posterior genotipagem utilizando o painel de alta densidade (Illumina High-Density Ovine SNP BeadChip®), compreendendo 54.241 SNPs. O banco fenotípico é composto por 387 animais. O LD médio entre marcadores adjacentes para duas métricas de LD, r² e |D\'|, foram 0,166 e 0,617, respectivamente. O grau de LD estimado foi menor que o relatado em outras espécies e foi caracterizado por blocos de haplótipos curtos. Consequentemente, para as análises genômicas são recomendados painéis de marcadores de alta densidade. No GWAS, foram encontrados muitos marcadores associados aos fenótipos, em especial, à característica CAR. Alguns genes candidatos foram relatados neste estudo, destacando-se o NRF-1 (fator respiratório nuclear 1), que controla a biossíntese mitocondrial, o processo mais importante responsável por grande parte da produção de energia. Finalmente, verificamos a acurácia do valor genético genômico estimado para o CAR usando modelos de regressão Bayesiana, e encontramos baixos valores para acurácia (0,033 a 0,036) o que pode ser explicado pelo baixo grau de relacionamento entre os indivíduos e tamanho reduzido da população de treinamento.

Pour lutter contre les agents phytopathogènes, la sélection de plantes résistantes est la stratégie la plus rentable et la plus écologique. Les résistances quantitatives, basées sur des mécanismes de résistances complexes, sont connues pour être sujettes à l’érosion, en cas d’évolution de l’agressivité des agents pathogènes. L’objectif de ce travail basé sur le pathosystème peuplier – rouille du peuplier (Melampsora larici-populina) est d’évaluer le potentiel évolutif des caractères d’agressivité et morphologiques du parasite par des approches de génétique quantitative et d'identifier les bases génétiques par génétique d'association. Pour estimer la plasticité, l’héritabilité et les compromis évolutifs d’un ensemble de caractères quantitatifs, nous avons précisément mesuré leurs variations dans quatre populations contrastées du champignon. Nous avons montré que le volume des spores est un caractère héritable qui évolue rapidement. La quantité de mycélium in planta est aussi héritable mais très conservée car sous sélection stabilisante dans les populations étudiées. Le temps de latence, la taille des lésions et le taux de sporulation présentent une héritabilité faible, ce qui explique l’absence d’évolution observées au cours du temps pour ces trois caractères. Les caractères liés à la fonction de sporulation semblent être les plus plastiques le long d’un gradient de maturité foliaire. Cependant, l’absence de mise en évidence de compromis évolutifs ne nous a pas permis d’identifier des caractères d’agressivité qui seraient les meilleures cibles pour les résistances quantitatives chez le peuplier. Si aucune base génétique de ces caractères quantitatifs n’a été mise en évidence, nous avons localisé un locus d’avirulence potentiel (Avr7) sur lequel une caractérisation fonctionnelle est envisagée / To control plant pathogens, breeding resistant plants is the most cost-effective and ecological strategy. Quantitative resistances, which are based on complex plant mechanisms, are known to be exposed to erosion through an increase of pathogens aggressiveness. Through the study the poplar – poplar rust (Melampsora larici-populina) pathosystem, this work aims to estimate the evolutionary potential of aggressiveness and morphological traits using quantitative genetic approaches and to identify molecular bases through genome-wide association study. To estimate plasticity, heritability, and trade-offs for a set of quantitative traits, we precisely measured their variation in four contrasted pathogen populations. It appeared that spore volume is highly heritable and evolved rapidly. In planta mycelium quantity is also heritable but constant because of stabilizing selection occurring in the studied populations. Latent period, lesion size and sporulation rate exhibit low heritability, which explains the absence of evolution during the studied time period. Traits involved in the sporulating function seem to be the most plastic ones along a leaf maturity gradient. However, the lack of evidence of trade-offs did not allow us to identify aggressiveness traits that would be the best targets for the construction of durable resistance in poplar. No genetic underpinning has been found for quantitative traits, but we have identified a potential avirulence locus (Avr7), opening the way for its functional characterization

Advances in molecular marker technologies have led to the development of high throughput genotyping techniques such as Genotyping by Sequencing (GBS), driving the application of genomics in crop research and breeding. They have also supported the use of novel mapping approaches, including Multi-parent Advanced Generation Inter-Cross (MAGIC) populations which have increased precision in identifying markers to inform plant breeding practices. In the first part of this thesis, a high density physical map derived from GBS was used to identify QTLs controlling key agronomic traits of wheat in a genome-wide association study (GWAS) and to demonstrate the practicability of genomic selection for predicting the trait values. The results from GBS were compared to a previous study conducted on the same association mapping panel using a less dense physical map derived from diversity arrays technology (DArT) markers. GBS detected more QTLs than DArT markers although some of the QTLs were detected by DArT markers alone. Prediction accuracies from the two marker platforms were mostly similar and largely dependent on trait genetic architecture. The second part of this thesis focused on MAGIC populations, which incorporate diversity and novel allelic combinations from several generations of recombination. Pedigrees representing a wild rice MAGIC population were used to model MAGIC populations by simulation to assess the level of recombination and creation of novel haplotypes. The wild rice species are an important reservoir of beneficial genes that have been variously introgressed into rice varieties using bi-parental population approaches. The level of recombination was found to be highly dependent on the number of crosses made and on the resulting population size. Creation of MAGIC populations require adequate planning in order to make sufficient number of crosses that capture optimal haplotype diversity. The third part of the thesis considers models that have been proposed for genomic prediction. The ridge regression best linear unbiased prediction (RR-BLUP) is based on the assumption that all genotyped molecular markers make equal contributions to the variations of a phenotype. Information from underlying candidate molecular markers are however of greater significance and can be used to improve the accuracy of prediction. Here, an existing Differentially Penalized Regression (DiPR) model which uses modifications to a standard RR-BLUP package and allows two or more marker sets from different platforms to be independently weighted was used. The DiPR model performed better than single or combined marker sets for predicting most of the traits both in a MAGIC population and an association mapping panel. Overall the work presented in this thesis shows that while these techniques have great promise, they should be carefully evaluated before introduction into breeding programmes.