Background: Imputation of partially missing or unobserved genotypes is an indispensable tool for SNP data analyses. However, research and understanding of the impact of initial SNP-data quality control on imputation results is still limited. In this paper, we aim to evaluate the effect of different strategies of pre-imputation quality filtering on the performance of the widely used imputation algorithms MaCH and IMPUTE. Results: We considered three scenarios: imputation of partially missing genotypes with usage of an external reference panel, without usage of an external reference panel, as well as imputation of ompletely un-typed SNPs using an external reference panel. We first created various datasets applying different SNP quality filters and masking certain percentages of randomly selected high-quality SNPs. We imputed these SNPs and compared the results between the different filtering scenarios by using established and newly proposed measures of imputation quality. While the established measures assess certainty of imputation results, our newly proposed measures focus on the agreement with true genotypes. These measures showed that pre-imputation SNP-filtering might be detrimental regarding imputation quality. Moreover, the strongest drivers of imputation quality were in general the burden of missingness and the number of SNPs used for imputation. We also found that using a reference panel always improves imputation quality of partially missing genotypes. MaCH performed slightly better than IMPUTE2 in most of our scenarios. Again, these results were more pronounced when using our newly defined measures of imputation quality. Conclusion: Even a moderate filtering has a detrimental effect on the imputation quality. Therefore little or no SNP filtering prior to imputation appears to be the best strategy for imputing small to moderately sized datasets. Our results also showed that for these datasets, MaCH performs slightly better than IMPUTE2 in most scenarios at the cost of increased computing time.

The genes that regulate pubertal timing in the general population are not well understood. Recently, genome-wide association studies have demonstrated that genetic variants near LIN28B associate with variation in pubertal timing in humans. To investigate where within the hypothalamic-pituitary-ovarian (HPO) axis Lin28b, and its homologue Lin28a, regulate pubertal timing, expression of these genes was assessed across the pubertal transition. The finding that Lin28a/b expression decreases only in the ovary suggests that the Lin28 pathway may exert its regulatory effects with respect to puberty in the ovary. Another aim of this thesis was to examine the effect of estrogen on Lin28b expression in immortalized GnRH neuronal cells, but the data remains equivocal and detailed future studies are needed to make definitive conclusions. The ovarian expression data lay the foundation for further studies using conditional knockout mice to verify the importance of the tissue and age specific developmental pattern that was identified.

The genes that regulate pubertal timing in the general population are not well understood. Recently, genome-wide association studies have demonstrated that genetic variants near LIN28B associate with variation in pubertal timing in humans. To investigate where within the hypothalamic-pituitary-ovarian (HPO) axis Lin28b, and its homologue Lin28a, regulate pubertal timing, expression of these genes was assessed across the pubertal transition. The finding that Lin28a/b expression decreases only in the ovary suggests that the Lin28 pathway may exert its regulatory effects with respect to puberty in the ovary. Another aim of this thesis was to examine the effect of estrogen on Lin28b expression in immortalized GnRH neuronal cells, but the data remains equivocal and detailed future studies are needed to make definitive conclusions. The ovarian expression data lay the foundation for further studies using conditional knockout mice to verify the importance of the tissue and age specific developmental pattern that was identified.

The existence of new technologies, implemented in efficient platforms and workflows has made massive genotyping available to all fields of biology and medicine. Genetic analyses are no longer dominated by experimental work in laboratories, but rather the interpretation of the resulting data. When billions of data points representing thousands of individuals are available, efficient computational tools are required. The focus of this thesis is on developing models, methods and implementations for such tools. The first theme of the thesis is multi-dimensional scans for quantitative trait loci (QTL) in experimental crosses. By mating individuals from different lines, it is possible to gather data that can be used to pinpoint the genetic variation that influences specific traits to specific genome loci. However, it is natural to expect multiple genes influencing a single trait to interact. The thesis discusses model structure and model selection, giving new insight regarding under what conditions orthogonal models can be devised. The thesis also presents a new optimization method for efficiently and accurately locating QTL, and performing the permuted data searches needed for significance testing. This method has been implemented in a software package that can seamlessly perform the searches on grid computing infrastructures. The other theme in the thesis is the development of adapted optimization schemes for using hidden Markov models in tracing allele inheritance pathways, and specifically inferring haplotypes. The advances presented form the basis for more accurate and non-biased line origin probabilities in experimental crosses, especially multi-generational ones. We show that the new tools are able to reconstruct haplotypes and even genotypes in founder individuals and offspring alike, based on only unordered offspring genotypes. The tools can also handle larger populations than competing methods, resolving inheritance pathways and phase in much larger and more complex populations. Finally, the methods presented are also applicable to datasets where individual relationships are not known, which is frequently the case in human genetics studies. One immediate application for this would be improved accuracy for imputation of SNP markers within genome-wide association studies (GWAS). / eSSENCE

No description available.

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.

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.