The seed size and shape of lentil are important traits because they determine the market class, cooking time, and can influence quality and yield of milled lentils. Understanding the genetic control of seed size and shape can help breeders develop varieties with improved seed size and shape characteristics such as seed diameter, seed thickness and seed plumpness. The objectives were to determine the heritability of seed size and shape and identify the genomic regions controlling these traits. This involved i) developing a linkage map for the LR-18 population (CDC Robin x 964a-46) using a recently developed single nucleotide polymorphism (SNP) assay; ii) analyzing the LR-18 population for seed size and shape QTLs; iii) analyzing an association mapping panel for seed size and shape QTLs. Phenotyping trials were grown at two different locations in Saskatchewan, Canada. The mapping population was grown in two different years while the association panel was only grown in one. Seed diameter and thickness were measured using sieves and this data were used to calculate seed plumpness. Days to flowering was also recorded to determine if it had any effect on seed size or shape. A linkage map consisting of 537 SNPs, 10 SSRs and 4 morphological markers on seven linkage groups was constructed and used for the QTL analysis. The heritability estimates were high for seed diameter and seed plumpness (0.92 and 0.94, respectively) while for seed thickness and days to flowering they were more moderate (0.60 and 0.45, respectively). QTL analysis revealed QTLs on five of the seven linkage groups. The association mapping study revealed similar heritability estimates of 0.97, 0.62, 0.94, and 0.62 for seed diameter, seed thickness, seed plumpness and flowering time, respectively. There were 31 different significant marker trait associations, however only 5 of those were significant for both locations. Four of those five markers did not map in the LR-18 linkage map so their genomic locations are still to be determined. Results showed that there are key regions in the genome that control seed size and shape and flowering time in lentil. These markers could be used for marker-assisted selection or for further candidate gene analysis.

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L’avènement du génotypage à haut débit permet aujourd’hui de mieux exploiter le phénomène d’association, appelé déséquilibre de liaison (LD), qui existe entre les allèles de différents loci sur le génome. Dans ce contexte, l’utilité de certains modèles utilisés en cartographie de locus à effets quantitatifs (QTL) est remise en question. Les objectifs de ce travail étaient de discriminer entre des modèles utilisés en routine en cartographie et d’apporter des éclaircissements sur la meilleure façon d’exploiter le LD, par l’utilisation d’haplotypes, afin d’optimiser les modèles basés sur ce concept. On montre que les modèles uni-marqueur de liaison, développés en génétique il y a vingtaine d’années, comportent peu d’intérêts aujourd’hui avec le génotypage à haut débit. Dans ce contexte, on montre que les modèles uni-marqueur d’association comportent plus d’avantages que les modèles uni-marqueur de liaison, surtout pour des QTL ayant un effet petit ou modéré sur le phénotype, à condition de bien maîtriser la structure génétique entre individus. Les puissances et les robustesses statistiques de ces modèles ont été étudiées, à la fois sur le plan théorique et par simulations, afin de valider les résultats obtenus pour la comparaison de l’association avec la liaison. Toutefois, les modèles uni-marqueur ne sont pas aussi efficaces que les modèles utilisant des haplotypes dans la prise en compte du LD pour une cartographie fine de QTL. Des propriétés mathématiques reliées à la cartographie de QTL par l’exploitation du LD multiallélique capté par les modèles haplotypiques ont été explicitées et étudiées à l’aide d’une distance matricielle définie entre deux positions sur le génome. Cette distance a été exprimée algébriquement comme une fonction des coefficients du LD multiallélique. Les propriétés mathématiques liées à cette fonction montrent qu’il est difficile de bien exploiter le LD multiallélique, pour un génotypage à haut débit, si l’on ne tient pas compte uniquement de la similarité totale entre des haplotypes. Des études sur données réelles et simulées ont illustré ces propriétés et montrent une corrélation supérieure à 0.9 entre une statistique basée sur la distance matricielle et des résultats de cartographie. Cette forte corrélation a donné lieu à la proposition d’une méthode, basée sur la distance matricielle, qui aide à discriminer entre les modèles utilisés en cartographie. / The advent of high-throughput genotyping nowadays allows better exploitation of the association phenomenon, called linkage disequilibrium (LD), between alleles of different loci on the genome. In this context, the usefulness of some models to fine map quantitative trait locus (QTL) is questioned. The aims of this work were to discriminate between models routinely used for QTL mapping and to provide enlightenment on the best way to exploit LD, when using haplotypes, in order to optimize haplotype-based models. We show that single-marker linkage models, developed twenty years ago, have little interest today with the advent of high-throughput genotyping. In this context, we show that single-marker association models are more advantageous than single-marker linkage models, especially for QTL with a small or moderate effect on the phenotype. The statistical powers and robustness of these models have been studied both theoretically and by simulations, in order to validate the comparison of single-marker association models with single-marker linkage models. However, single-marker models are less efficient than haplotype-based models for making better use of LD in fine mapping of QTL. Mathematical properties related to the multiallelic LD captured by haplotype-based models have been shown, and studied, by the use of a matrix distance defined between two loci on the genome. This distance has been expressed algebraically as a function of the multiallelic LD coefficients. The mathematical properties related to this function show that it is difficult to exploit well multiallelic LD, for a high-throughput genotyping, if one takes into account the partial and total similarity between haplotypes instead of the total similarity only. Studies on real and simulated data illustrate these properties and show a correlation above 0.9 between a statistic based on the matrix distance and mapping results. Hence a new method, based on the matrix distance, which helps to discriminate between models used for mapping is proposed.

El treball presentat en aquesta tesi és un estudi de la diversitat genètica en un conjunt de gens implicats en funcions neurològiques ("Gens cerebrals"). Hom ha examinat vint-i-dos gens implicats en els sistemes de neurotransmissió dopaminèrgic, serotoninèrgic i glutamatèrgic. L'objectiu de l'estudi té dos vessants: per una banda l'anàlisi de la diversitat genètica en un conjunt de gens implicats en malaltia humana, en aquest cas en malaltia psiquiàtrica, en poblacions humanes mundials, amb la intenció d'assentar les bases per propers esforços de mapatge genètic; i per altra banda analitzar la diversitat genètica en aquest conjunt de gens per tal de descobrir evidències d'esdeveniments històrics, incloent possibles evidències de selecció. / The work presented in this thesis is a study of the genetic variation in a set of genes related to neurological function ('Brain genes'). Twenty two genes are examined, all of which are involved in either the Dopaminergic, Serotonergic or the Glutamatergic systems of neurotransmission.The objective of the study has two aspects: on the one hand the analysis of genetic variation in a set of genes which are implicated in human disease, in this case psychiatric disease, across global human populations, towards the end of providing some new insight for gene mapping efforts, and on the other hand the study of genetic variation in this set of genes may reveal traces of the population history events undergone, including possible evidence for selection.