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L’approche GWAS est un outil essentiel pour la découverte de gènes associés aux maladies, mais elle pose des problèmes de puissance statistique quand il est impossible d’échantillonner génétiquement des dizaines de milliers de sujets. Les résultats présentés ici—ALDsuite, un programme en utilisant une correction nouvelle et efficace pour le déséquilibre de liaison (DL) ancestrale de la population locale, en permettant l'utilisation de marqueurs denses dans le MALD, et la démonstration que la méthode simpleM fournit une correction optimale pour les comparaisons multiples dans le GWAS—réaffirment la valeur de l'analyse en composantes principales (APC) pour capturer l’essence de la complexité des systèmes de grande dimension. L’APC est déjà la norme pour corriger la structure de la population dans le GWAS; mes résultats indiquent qu’elle est aussi une stratégie générale pour faire face à la forte dimensionnalité des données génomiques d'association. / GWAS is an essential tool for disease gene discovery, but has severe problems of statistical power when it is impractical to genetically sample tens of thousands of subjects. The results presented here—a novel, effective correction for local ancestral population LD allowing use of dense markers in MALD using the ALDsuite and the demonstration that the simpleM method provides an optimum Bonferroni correction for multiple comparisons in GWAS, reiterate the value of PCA for capturing the essential part of the complexity of high- dimensional systems. PCA is already standard for correcting for population substructure in GWAS; my results point to it’s broader applicability as a general strategy for dealing with the high dimensionality of genomic association data.

Meningitis is an infection of the meninges, a layer of tissue surrounding the brain. In cases of pneumococcal meningitis (where the bacterium Streptococcus pneumoniae is the causat- ive agent) this causes severe inflammation, requiring intensive care and rapid antibiotic treatment. The contribution of variation in host and pathogen genetics to pneumococcal meningitis is unknown. In this thesis I develop and apply statistical genetics techniques to identify genomic variation associated with the various stages of pneumococcal meningitis, including colonisation, invasion and severity. I start by describing the development of a method to perform genome-wide association studies (GWAS) in bacteria, which can find variation in bacterial genomes associated with bacterial traits such as antibiotic resistance and virulence. I then applied this method to longitudinal samples from asymptomatic carriage, and found lineages and specific variants associated with altered duration of carriage. To assess meningitis versus carriage samples I applied similar analysis techniques, and found that the bacterial genome is crucial in determining invasive potential. As well as bacterial serotype, which I found to be the main effect, I discovered many independent sequence variants associated with disease. Separately, I analysed within host-diversity during the invasive phase of disease and found it to be of less relevance to disease progression. Finally, I analysed host genotype data from four independent studies using GWAS and heritability estimates to determine the contribution of human sequence variation to pneumococcal meningitis. Host sequence accounted for some variation in susceptibility to and severity of meningitis. The work concludes with a combined analysis of pairs of bacterial and human sequences from meningitis cases, and finds variation correlated between the two.

Human ageing is accompanied by characteristic metabolic and endocrine changes, including altered hormone profiles, insulin resistance and deterioration of skeletal muscle. Obesity and diabetes may themselves drive an accelerated ageing phenotype. Untangling the causal web between ageing, obesity and diabetes is a priority in order to understand their aetiology and improve prevention and management. The role of biological ageing in determining the risk of obesity and associated conditions has often been examined using mean leukocyte telomere length (LTL), a marker of replicative fatigue and senescence. However, considering phenotypes which represent different domains of biological and functional ageing as exposures for obesity and related traits could allow the elucidation of new understudied phenotypes relevant to cardio-metabolic risk in the wider population. This PhD considers the causal role of (1) hand grip strength (HGS), a marker of overall strength and physical functioning, and (2) resting energy expenditure, an indicator of overall energy metabolism and the major component of daily energy expenditure, in cardio-metabolic risk. I also characterise a new and readily-quantifiable marker of age-related genomic instability, mosaic loss of the Y chromosome (mLOY). Observational evidence implicates each of these phenotypes in cardio-metabolic conditions and intermediate phenotypes. However, it is not possible to infer causality from these observational associations due to confounding and reverse-causality. Mendelian randomisation offers a solution to these limitations and can allow the causal nature of these relationships to be investigated. Using population-based data including UK Biobank, this thesis presents the first large-scale genetic discovery effort for each trait and provides new biological insight into their shared and separate aetiology. I used identified variants to investigate the bidirectional causal associations of each trait with cardio-metabolic outcomes, intermediate phenotypes and other related traits such as frailty and mortality. In total I identified 16 loci for hand grip strength, 19 for mLOY, and one signal for REE. I have shown that HGS is likely to be causally linked to fracture risk, and I have identified the important shared genetic architecture between mLOY, glycaemic traits and cancer. I have also demonstrated that at least one known genetic variant contributing to obesity risk acts partially via reduced REE. Overall the findings of my PhD contribute to our wider understanding of the aetiological role of ageing processes in metabolic dysfunction, and have implications for both basic science and translational applications.

Afin de caractériser les profils de distribution de l’ARN Pol II en aval des EAGs, j’ai réalisé des expériences de ChIP-seq en utilisant un anticorps reconnaissant toutes les formes d’ARN Pol II humaine. J’ai analysé les profils de Pol II en aval de 13787 gènes qui n’ont pas de gène flanquant à +/- 4kb en amont ou en aval. Nos résultats ont été analysés en comparaison avec des données disponibles de séquençage à haut débit d’ARN naissants (Global Run On assay coupled sequencing : GRO-seq). Nos résultats montrent qu’un enrichissement de la Pol II en aval de l’extrémité des unités de transcription est une caractéristique partagée par tous les gènes exprimés et reflète la présence d’ARN Pol II active. Des analyses bioinformatiques (K-means clustering) m’ont permis de distinguer quatre groupes de gènes : le premier groupe (H) est caractérisé par un profil de pause étroit alors que les trois autres groupes (PA1-PA3) montrent un profil large ou très large, pouvant aller jusqu’à 6kb en aval des EAGs. Des analyses d’annotations (Gene Ontology) révèlent que le groupe H contient pratiquement exclusivement des gènes d’histones qui ne contiennent pas d’intron et dont les transcrits ne sont pas polyadénylés. A l’inverse, les groupes PA1-PA3 contiennent des gènes codant pour des transcrits polyadénylés. J’ai confirmé par des expériences de ChIP couplées à une analyse par qPCR les différents types de profils de distribution de Pol II décrits par analyse bioinformatique. Nos résultats sont en accord avec d’autres publications et suggèrent un lien entre le profil de distribution de la Pol II à l’extrémité 3’ des gènes histones et les mécanismes particuliers de maturation de l’extrémité 3’ de ces transcrits. Cette idée est renforcée par nos analyses fonctionnelles montrant que l’inhibition des mécanismes de polyadénylation augment la présence de l’ARN Pol II en 3’ des EAGs pour les gènes codant pour des transcrits polyadénylés. / The Pol II transcription cycle can be divided into three main phases: transcription initiation, elongation and termination. Each phase represent a possibility for the regulation of gene expression. Recently, genome-wide studies demonstrated that Pol II pausing is an important regulatory step that is present at almost every eukaryotic Pol II promoter. Surprisingly, paused or slowed down polymerases were also discovered downstream of 3’ end of genes, of which the exact role is still not fully understood.During my Ph.D. I carried out projects using chromatin immunoprecipitation assay coupled to high-throughput sequencing techniques to analyze genome-wide Pol II behavior in two aspects:First, we analyzed Pol II occupancy downstream of 3’ end of transcription units. Our analyses suggest that accumulation of Pol II downstream of genes is a genome-wide feature of active transcription. We found broad, often up to 6kb long Pol II occupancy signals at genes coding for polyadenylated transcripts. In contrast, Pol II occupancy shows a narrow profile at the annotated end of core histone genes. We also found a link between RNA 3’ end processing and Pol II accumulation at the end of transcription units.Second, we were following the genome-wide response and alteration of Pol II transcription upon genotoxic stress. Following UV-B treatment we observed a progressive Pol II signal loss from the promoters of expressed genes, which will then extend through the entire transcription unit, up to four hours after irradiation. This is in good agreement with the observation that after UV irradiation transcription is arrested during the period of transcription-coupled repair (TCR).

Les études d’association pangénomique (GWAS) ont permis la mise en évidence de nouvelles voies putativement importantes dans la physiopathologie du diabète de type 2, par l’identification de variants génétiques fréquents (SNP) de susceptibilité au diabète de type 2, mais souvent avec peu ou pas d'informations sur le mécanisme sous-jacent expliquant le lien entre ces variants génétiques et le phénotype diabétique. En effet ces SNP sont souvent non codants et ont un effet modeste sur le risque de diabète de type 2, ce qui rend difficile leur étude d’un point de vue fonctionnel. Dès le début des GWAS, il a été suggéré que ces gènes associés au diabète de type 2, étaient des « gènes de la cellule β pancréatique » sans que des études fonctionnelles n’aient été faites de manière systématique. Dans ce contexte, nous avons mené une étude de fishing pour déblayer cette quantité importante de données provenant des GWAS et d’identifier des gènes potentiellement importants, pouvant être de nouvelles cibles thérapeutiques. Le premier objectif de ma thèse a été l’étude de l’expression des gènes de susceptibilité au diabète de type 2 dans un panel de tissus humains comprenant des tissus pancréatiques et des tissus sensibles à l’insuline. Pour cela nous avons utilisé une technique de quantification non biaisée de l’expression génique dans le but de montrer si ces gènes associés au diabète de type 2 avaient une expression enrichie (proportion de gènes de susceptibilité au diabète de type 2 surexprimés dans les cellules β versus les autres tissus) dans les cellules β pancréatiques. Nous avons ensuite réalisé des études fonctionnelles sur la trentaine de gènes de susceptibilité au diabète de type 2 les plus exprimés dans notre modèle cellulaire par des tests de sécrétion d’insuline, des études de la viabilité cellulaire, du séquençage d’ARN (RNA-seq) et du western blotting dans la lignée de cellules β pancréatiques humaines EndoC-βH1. Les EndoC-βH1 sont des cellules en mesure de sécréter de l’insuline en réponse au glucose et à d’autres sécrétagogues. Nous les avons utilisé afin d’étudier le rôle de ces gènes de susceptibilité au diabète de type 2 dans la fonction de la cellule β pancréatique, en particulier dans la sécrétion insulinique. Notre étude d’expression a montré que l’expression des gènes de susceptibilité au diabète de type 2 est enrichie de manière significative dans les cellules β pancréatiques et la lignée EndoC-βH1. Pour cinq gènes du diabète de type 2 (TBC1D4, TCF19, KCNK16, CDKN2A et SLC30A8) ayant une présence et un effet déjà connus dans la fonction des cellules β, nous avons démontré une variation significative de la sécrétion d’insuline après extinction génique, en concordance avec la littérature. Par ailleurs, nous avons pu mettre en évidence quatre gènes de susceptibilité au diabète de type 2 (PRC1, SRR, ZFAND3 et ZFAND6) montrant une baisse significative de la sécrétion d’insuline après extinction génique et dont la présence ou la fonction dans la cellule β était pour l’heure inconnue. Les analyses RNA-seq ont montré une association significative de l’extinction de ces gènes avec des réseaux moléculaires liés à la physiopathologie du diabète de type 2 (par exemple : l’apoptose des cellules pancréatiques, l’insulinémie, la glycolyse, le stress du réticulum endoplasmique…). Et l’évaluation de l’expression de nos quatre gènes dans des îlots de souris obèses (ob/ob) ou traitées à la streptozotocine a montré une corrélation positive de leur expression avec celle de l’insuline. Notre étude a démontré que les études fonctionnelles post-GWAS sont importantes et permettent de définir le lien de causalité des gènes de susceptibilité avec la maladie, et ainsi de mener à des progrès sur la compréhension de la physiopathologie de la maladie [...] / Genome-wide association studies (GWAS) have identified a plethora of single nucleotide polymorphisms (SNPs) associated with the risk of type 2 diabetes, but most often with little information about the mechanism underlying the relationship between these genetic variants associated with type 2 diabetes and the diabetic phenotype. Indeed, these SNPs are often noncoding and have a modest effect on the risk of type 2 diabetes, making difficult their functional study. At the beginning of the GWAS era, it has been suggested that susceptibility genes for type 2 diabetes are strongly involved in pancreatic β cell gene function, while no functional studies had been systematically performed. In this context, we conducted a “fishing” study to decipher this large amount of data generated by GWAS and to pinpoint potentially important genes that may be new therapeutic targets. The first objective of my thesis was to study the expression of type 2 diabetes susceptibility genes in a panel of human tissues comprising pancreatic and insulin-sensitive tissues using an unbiased technique of quantification of genes expression in order to show that these genes associated with type 2 diabetes were enriched in pancreatic β-cells. We then performed functional studies on the thirty mostly expressed genes in our cell model by insulin secretion tests, cell viability test, RNA sequencing (RNA-seq) and Western blotting in the human pancreatic β cell line (EndoC-βH1). These cells are able to secrete insulin in response to glucose and other secretagogues. Our goal was to study the role of these type 2 diabetes susceptibility genes in pancreatic β cell function, particularly in insulin secretion. Our expression study of type 2 diabetes susceptibility genes showed that their expression is significantly enriched in pancreatic β cells and the EndoC-βH1 cell line. For five genes associated with type 2 diabetes (TBC1D4, TCF19, KCNK16, CDKN2A and SLC30A8) with an already known presence and function in pancreatic β cell, we showed a significant variation in glucose-stimulated insulin secretion after gene silencing, in agreement with the literature. In addition, we identified four type 2 diabetes associated genes (PRC1, SRR, ZFAND3 and ZFAND6), with a significant decrease in insulin secretion after gene silencing without already know function in pancreatic β cell. RNA-seq has shown a significant association between the extinction of these genes and molecular networks related to the pathophysiology of type 2 diabetes (e.g. apoptosis of pancreatic cells, insulinemia, glycolysis, endoplasmic reticulum stress response...). The assessment of the expression of our four genes in the islets of obese mice (ob/ob) or treated with streptozotocin shows a positive correlation between their expression and the expression of insulin. Our study has shown that post-GWAS functional studies are important and can help to define the causal link between these genes and the disease, and therefore to make progress in the understanding of the pathophysiology of type 2 diabetes. This study allowed us to identify genes whose function in β cell was not anterior known and which are involved in pancreatic β cell function and the pathophysiology of type 2 diabetes.

Made available in DSpace on 2016-06-02T20:21:37Z (GMT). No. of bitstreams: 1 6501.pdf: 1672444 bytes, checksum: 64754c3f12e26620a22bf55af9f8d5ff (MD5) Previous issue date: 2014-08-13 / The Brazilian cattle industry is presented as highlighted on the world stage and the significant participation of this productive sector in the economy means that there is concern with production losses, among which stands out those caused by infestation of Rhipicephalus (Boophilus) microplus, main ectoparasite vector cattle and various diseases. The genetic variability for resistance to the cattle tick shows that this trait can be genetically improved. For the execution of this work, it was used a study of genome wide association (GWAS) for resistance to Rhipicephalus (Boophilus) microplus, performed by Dr. Fernando Flores Cardoso, with 260 Hereford and 500 Braford animals. The monitoring of the infestation was accomplished by counting tick females larger than 4.5 mm from one of the animal's body side, and the degree of infestation was evaluated for each animal by averaging at least two consecutive counts, with intervals of approximately thirty days, in the months of highest incidence of the parasite. The animals were genotyped using a 50K SNP chip, and it was found a total of 37,346 SNPs that passed in quality test. Among these markers, 178 showed significant effects and allowed the mining of 175 genes in these regions, at an interval of 200 Kb (100 Kb for each side of each marker). Most of these polymorphisms associated with the trait is located in regions without defined functions (intronic and intergenic), and only one of them is located in the splicing region. The most significant regions of the GWAS were identified on chromosomes 7, 21 and 23, which were found 72 genes in linkage disequilibrium with the molecular markers. Therefore, a functional annotation of the genes on these 3 chromosomes was performed, allowing the choice of 11 candidate genes for the study of various metabolic pathways in which they are inserted. Among these pathways, the most important are those related to immune responses, secretion and intracellular transport, calcium influx and epidermal growth and differentiation. / A bovinocultura brasileira apresenta-se como destaque no cenário mundial e a expressiva participação deste setor produtivo na economia faz com que haja preocupação com as perdas produtivas, dentre as quais destaca-se aquelas causadas pela infestação do carrapato Rhipicephalus (Boophilus) microplus, principal ectoparasita de bovinos e vetor de diversas doenças. A variabilidade genética observada para a resistência dos bovinos ao carrapato permite que essa característica seja melhorada geneticamente, como forma alternativa de controle desses ectoparasitos. Para a execução do presente trabalho, foi utilizado um estudo de associação genômica ampla (GWAS) para a resistência ao carrapato R. microplus, o qual foi realizado pela equipe do Dr. Fernando Flores Cardoso (Embrapa Pecuária Sul), com 260 animais da raça Hereford e 500 animais da raça Braford. O monitoramento das infestações foi realizado por meio da contagem de fêmeas do carrapato com tamanho superior a 4,5 mm em um dos lados do corpo do animal, e o grau de infestação de cada animal foi avaliado pela média de pelo menos duas contagens consecutivas, com intervalos de aproximadamente trinta dias, conduzidas no sobreano, nos meses de maior incidência do parasito. Os animais foram genotipados com utilização de um chip de SNPs de 50 K e, após a realização do GWAS, verificou-se que um total de 37.346 SNPs passou nos teste de qualidade. Dentre esses marcadores, 178 SNPs apresentaram efeitos significativos e permitiram a mineração de 175 genes nessas regiões, em um intervalo de 200 Kb (100 Kb para cada lado de cada marcador). A maioria dos polimorfismos associados com a característica está localizada em regiões sem funções determinadas (intergênicas e intrônicas), apenas um deles encontra-se em região de splicing. Sendo assim, estes marcadores podem constituir mutações não causais que se encontram em desequilíbrio de ligação com mutações funcionais. As regiões mais significativas do GWAS foram identificadas nos cromossomos 7, 21 e 23, onde foram identificados 72 genes em desequilíbrio de ligação com os marcadores moleculares. Portanto, foi realizada uma anotação funcional dos genes localizados nesses 3 cromossomos, o que permitiu a seleção de 11 genes candidatos para um estudo mais aprofundado das vias metabólicas nas quais eles estão inseridos. Verificou-se que esses genes participam de processos importantes em vias já relacionadas com a resistência a carrapatos, tais como apresentação de antígenos, transporte e secreção intracelular e diferenciação da epiderme.

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.

Métodos de predição podem aumentar consideravelmente a eficiência dos programas de melhoramento de milho. O objetivo deste estudo foi predizer a performance de 250 híbridos simples de milho avaliados em múltiplos ambientes utilizando a informação de marcadores moleculares. Para isso, 50 linhagens endogâmicas provenientes de diferentes populações foram cruzadas com cinco linhagens elite, também endogâmicas, para obtenção dos 250 híbridos simples. As matrizes moleculares das linhagens e dos híbridos foram obtidas a partir da genotipagem das 55 linhagens com 614 marcadores AFLP. Os híbridos simples foram avaliados para produção de grãos em 13 ambientes. A predição dos híbridos foi realizada utilizando o modelo misto BLUP considerando diferentes coeficientes de parentesco e similaridade no estado na predição dos efeitos das capacidades geral e específica de combinação dos genitores. As médias preditas dos híbridos a partir de cada coeficiente foram correlacionadas com as médias fenotípicas para obtenção da acurácia de predição. A predição também foi realizada utilizando o modelo de seleção genômica ampla RR-BLUP. Nesse caso, a matriz molecular dos híbridos foi utilizada diretamente no modelo misto de estimação dos efeitos dos marcadores e da contribuição de cada um deles para o valor genético dos híbridos. Foram realizadas validações cruzadas entre e dentro de ambientes e entre e dentro de grupos de híbridos relacionados a fim de verificar os efeitos do tamanho da população de treinamento (N), número de marcas (NM), interação híbridos x ambientes (H x A) e da estrutura da população na estimativa da acurácia de predição. A predição genômica foi comparada com a seleção fenotípica quanto à eficiência em identificar híbridos superiores em um esquema de melhoramento de milho. Todos os coeficientes de parentesco e similaridade no estado apresentaram elevadas estimativas de acurácia, contudo foi possível observar considerável superioridade dos coeficientes Wang e Rogers Modificado tanto na predição quanto na seleção dos híbridos superiores, demonstrando o potencial dessas metodologias como ferramentas a serem utilizadas nos programas de melhoramento de milho. Os resultados da predição utilizando o modelo de seleção genômica ampla indicaram que o aumento de N e NM não alteraram significativamente as estimativas de acurácia. As estimativas da acurácia na validação cruzada dentro de ambientes foram superiores às obtidas entre ambientes, inferindo que o efeito da interação H x A foi expressivo. Também foram observadas estimativas de acurácia expressivamente maiores para populações de treinamento e validação compostas por híbridos relacionados. Em todos os casos, as estimativas de acurácia apresentaram amplos intervalos em função da amostra de híbridos utilizada nas populações de treinamento e validação, indicando que a seleção genômica pode não ser eficiente dependendo da população amostrada. Os resultados deste estudo sugerem que a predição genômica é uma ferramenta para aumentar a eficiência da seleção nos programas de melhoramento se utilizada de forma adequada pelo melhorista, considerando os efeitos de estrutura de população e interação H x A de forma a maximizar a acurácia e, consequentemente, o sucesso da predição. / Prediction using molecular markers information can greatly increase the efficiency of maize breeding programs. This study aimed to predict the performance of maize single-crosses evaluated in multiple environments and using molecular markers information. Five inbred lines used as testers were crossed to 50 inbred lines from multiple populations to obtain 250 maize single-crosses. 614 AFLP markers were used to asses molecular matrices of the inbred lines and single-crosses. The 250 single-crosses were evaluated for grain yield in 13 environments. Genomic prediction was performed using the mixed model BLUP considering different genomic relationship and similarity in state coefficients to predict the effect of general and specific combining abilities of the parents. Predicted means from each coefficient were correlated with phenotypic means for obtaining prediction accuracy. Genomewide prediction was also performed using the linear regression model RR-BLUP in the estimation of markers genotypic values and its contribution to hybrids genetic values. Cross-validations between and within environments and between and within groups of related single-crosses were performed to verify the effects of training population size (N), number of markers (NM), genotype-by-environment interaction (G x E) and population structure in estimating accuracy. Genomic prediction was compared with phenotypic selection in efficiency of selecting better hybrids in a maize breeding program. All relationship coefficients and similarity in state coefficients showed high values of accuracy, however we observed superiority of Wang relationship coefficient and Modified Rogers similarity coefficient both in predicting and in identifying the best single-crosses, showing the potential of these approaches as tools to be used in maize breeding programs. Genomewide prediction results showed that increasing N and NM did not led to higher accuracy estimates. Predicted accuracies of cross validation analysis within environments were higher than between environments, indicating that the effect of G x E interaction was significant. Greater accuracies were achieved when training and validation set were from related single-crosses. In all scenarios, wide intervals of accuracy were found, meaning that genomic prediction may not be effective depending on the sample used. Therefore, the results of this study suggest that genomic prediction is a tool to increase the efficiency of selection in breeding programs if used properly by breeders, considering the population structure and G x E interaction effect so as to reduce sample problems and maximize accuracy and hence the success of prediction.

Les études d'association sur un génome complet (GWAS) sont conçues pour découvrir les combinaisons de points de polymorphisme (SNP) associées à des maladies. La découverte de ces associations permet d'élaborer de meilleures stratégies pour détecter, traiter ou prévenir les maladies. Récemment, l'utilisation de techniques d'extraction de patterns discriminatif a été investiguée dans le cadre de problématiques GWAS. Toutefois, la découverte de combinaisons de SNP dans de grands jeux de données GWAS est encore difficile à cause de la complexité des algorithmes utilisés. La thèse se propose donc d'améliorer l'état de l'art des approches d'extraction de motifs discriminants, dans le cadre d'extraction de combinaisons de SNP corrélées à un phénotype d'intérêt. Plusieurs solutions ont été proposées, s'attaquant aux problèmes majeurs en GWAS : évaluation de la force d'association, découverte efficace de combinaisons de SNP et visualisation de ces combinaisons. Les approches proposées sont également prometteuses pour d'autres tâches de bioinformatique comme la découverte d'expressions génique, la détection de motifs de phosphorylation et la détection de motifs de régulation. / Discovering high-order SNP combinations associated with diseases is an important task of bioinformatics. Once new genetic associations are identified, they can be used to develop better trategies to detect, treat and prevent the diseases. Recently, this issue has been effectively tackled with discriminative pattern mining algorithms. However, the number of SNPs is often very large, discovering of SNP combinations remains many challenges. To address these challenges this thesis has been advanced the state-of-the-art discriminative pattern mining techniques to discover SNP combinations associated with interesting phenotype. Different solutions have been proposed in this thesis to tackle GWAS analysis. These solutions focus on efficient association strength evaluation, statistically significant discriminative SNP combinations discovery and interesting SNP combinations visualization. The solutions proposed in this thesis are also promising for other tasks of bioinformatics such as differential gene expression discovery, phosphorylation motifs detection and regulatory motif combination mining.