Submitted by Samuel Wallace Boer dos Santos (samuel_wallace_eu@hotmail.com) on 2018-10-05T12:41:08Z No. of bitstreams: 1 Dissertação (compacted).pdf: 1033432 bytes, checksum: 72856099afe05132396d596489c6971b (MD5) / Approved for entry into archive by Neli Silvia Pereira null (nelisps@fcav.unesp.br) on 2018-10-08T17:47:46Z (GMT) No. of bitstreams: 1 santos_swb_me_jabo.pdf: 1033432 bytes, checksum: 72856099afe05132396d596489c6971b (MD5) / Made available in DSpace on 2018-10-08T17:47:46Z (GMT). No. of bitstreams: 1 santos_swb_me_jabo.pdf: 1033432 bytes, checksum: 72856099afe05132396d596489c6971b (MD5) Previous issue date: 2018-07-31 / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / Características de eficiência alimentar estão diretamente associadas com a lucratividade e sustentabilidade da bovinocultura de corte. Conversão alimentar, consumo alimentar residual, consumo de matéria seca, eficiência alimentar e ganho em peso, são características importantes para a seleção de animais mais eficientes dentro de um sistema de produção, porém, com exceção do ganho em peso, as demais não vêm sendo consideradas como critérios de seleção devido à dificuldade de obtenção de fenótipos para as mesmas. Com o avanço nas tecnologias de genotipagem e sequenciamento, foram desenvolvidos chips de alta densidade de marcadores do tipo SNP (Single Nucleotide Polymorphism) espalhados pelo genoma. Estas informações moleculares vêm sendo utilizadas em estudos de associação genômica ampla (GWAS) e de seleção genômica (SG). Basicamente, o GWAS permite a identificação de variações genéticas de maior efeito sobre a expressão fenotípica de características de interesse, enquanto a SG visa a predição do valor genômico direto dos candidatos à seleção utilizando apenas a informação molecular, o que tem revolucionado o melhoramento genético por proporcionar a diminuição do intervalo de geração e o aumento da acurácia de predição dos valores genéticos dos animais. Assim sendo, os objetivos do presente trabalho foram: 1) encontrar regiões cromossômicas de maior efeito sobre características de eficiência alimentar em animais Nelore provenientes de dois programas de melhoramento (Instituto de Zootecnia - IZ e Nelore Qualitas), visando encontrar possíveis diferenças/semelhanças entre as populações; 2) avaliar a existência de genes candidatos comum às populações; e 3) avaliar a possibilidade e os benefícios de combinar estas duas populações Nelore em estudos de seleção genômica. Foram utilizadas informações fenotípicas e genotípicas de 1.137 animais do IZ e 817 animais do Qualitas. Os animais foram genotipados com painel de alta densidade (Illumina BovineHD chip) ou tiveram seus genótipos imputados para HD através do software FImpute. Após o controle de qualidade dos genótipos, permaneceram para análise 408.161 SNPs para o IZ e 428.621 SNPs para o Qualitas. O GWAS foi realizado para cada população individualmente, considerando a metodologia GBLUP. Modelos unicaracterísticos foram empregados nas análises, incluindo, além dos efeitos aleatórios de animal e resíduo, os efeitos sistemáticos de grupos de contemporâneos (GC), os quais foram definidos como: sexo, ano de nascimento e instalação (IZ) e ano do teste e baia (Qualitas). Para o IZ também foram incluídos, para todas as características, os efeitos fixos de mês de nascimento, e, como covariáveis, idade do animal (linear), idade da mãe (linear e quadrática) e os dois primeiros componentes principais (obtidos a partir da matriz G). O efeito quadrático da idade do animal foi incluído no modelo apenas para o consumo de matéria seca e ganho médio diário. Para o Qualitas, foi considerado, para todas as características, o efeito linear da idade do animal como covariável. No GWAS, foram encontradas algumas regiões cromossômicas de maior efeito para cada característica nas duas populações, porém, não foram encontradas regiões em comum. No estudo de seleção genômica (SG), foram utilizados dez diferentes abordagens e esquemas envolvendo as duas populações para comparar a acurácia de predição. Em geral, a combinação das populações pode gerar benefícios para a seleção genômica, porém, tais benefícios dependem da característica e do esquema de validação. / Feed efficiency traits are directly associated with the profitability and sustainability of beef cattle. Feed conversion rate, residual feed intake, dry matter intake, feed efficiency and average daily gain are important traits for the selection of more efficiency animals within a production system, but, except for weight gain, the others have not been considered as selection criteria due to the difficulty of obtaining phenotypes. With the advance in genotyping and sequencing technologies, high density chips of SNP (Single Nucleotide Polymorphism) have been developed. This molecular information has been used in genome-wide association (GWAS) and genomic selection (GS) studies. Basically, GWAS allows the identification of genetic variations with major effects on the phenotypic expression of traits of interest, while SG aims at the prediction of direct genomic value for the selection candidates using only their molecular information, which has revolutionized the animal breeding by providing a decrease in generation interval and increases in the prediction accuracies of breeding values. Thus, the objectives of the present study were to: 1) identify chromosomal regions with major effects on feed efficiency traits in animals from two Nellore breeding programs (Instituto de Zootecnia and Nellore Qualitas), in order to find possible differences/similarities between the populations; 2) evaluate the existence of candidate genes in common to populations; and 3) evaluate the possibility and benefits of combining these two Nellore populations in genomic selection studies. Phenotypic and genotypic information of 1,137 animals from IZ and 817 from Qualitas were used. The animals were genotyped with high density panel (Illumina BovineHD chip) or had their genotypes imputed to HD through the FImpute software. After quality control, remained for analysis 408,161 SNPs for IZ and 428.611 SNPs for Qualitas. The GWAS was performed for each population individually, considering the GBLUP methodology. Single-trait models were implemented in the analyzes, including, in addition to the random effects of animal and residual, the systematic effects of contemporary groups (CG), which were defined as: sex, year of birth and pen for the IZ, and year of test and pen for the Qualitas. For IZ, there were also considered, for all traits, the fixed effects of month of birth and, as covariable, age of animal (linear effect), age of dam (linear and quadratic effects) and the first two principal components (calculated based on the G matrix). For ADG and DMI, the quadratic effect of age of animal, as covariable, was added to the model. For Qualitas, it was also included in the model, for all traits, the linear effect of the animal age as covariable. In GWAS, some chromosomal regions of greater effect were found for each trait in both populations. However, no common regions were found. In GS, ten different approach and schemes involving the two Nellore populations were used to compare the accuracy of genomic prediction. In general, genomic predictions combining both populations are feasible, but, the benefits will depend on the trait and validation scheme. / CNPq: 132884/2016-0 / FAPESP: 2016/24228-9 / FAPESP: 2017/13411-0

The interdisciplinary field of systems biology has evolved rapidly over the last few years. Different disciplines have contributed to the development of both its experimental and theoretical branches.Although computational biology has been an increasing activity in computer science for more than a two decades, it has been only in the past few years that optimization models have been increasingly developed and analyzed by researchers whose primary background is Operations Research(OR). This dissertation aims at contributing to the field of computational biology by applying mathematical programming to certain problems in molecular biology.Specifically, we address three problems in the domain of Genome Wide Association Studies}:(i) the Pure Parsimony Haplotyping Under uncertatind Data Problem that consists in finding the minimum number of haplotypes necessary to explain a given set of genotypes containing possible reading errors; (ii) the Parsimonious Loss Of Heterozygosity Problem that consists of partitioning suspected polymorphisms from a set of individuals into a minimum number of deletion areas; (iii) and the Multiple Individuals Polymorphic Alu Insertion Recognition Problem that consists of finding the set of locations in the genome where ALU sequences are inserted in some individual(s).All three problems are NP-hard combinatorial optimization problems. Therefore, we analyse their combinatorial structure and we propose an exact approach to solution for each of them. The proposed models are efficient, accurate, compact, polynomial-sized and usable in all those cases for which the parsimony criterion is well suited for estimation. / Option Informatique du Doctorat en Sciences / info:eu-repo/semantics/nonPublished

Un objectif central en biologie est de comprendre la relation entre le génotype et le phénotype. Afin de disséquer les bases génétiques de la diversité phénotypique, il est nécessaire de disposer d’une collection de données génomiques d’un grand nombre d’individus d’une même espèce. Dans ce but, mes travaux de thèse se basent sur l’étude des séquences génomiques ainsi que des données phénotypiques de 1011 isolats naturels de la levure Saccharomyces cerevisiae. Dans un premier temps, je me suis intéressé à la description de la variation génétique et phénotypique pour dresser un portrait précis de l’histoire évolutive de cette espèce. Les données de phénotypage nous ont permis de réaliser des études pangénomiques d’association génotype-phénotype avec une puissance jusque là inégalée chez Saccharomyces cerevisiae. Je me suis par la suite penché sur l’évaluation des paramètres influençant le pouvoir de détection d’une telle approche, d’en apprécier limites pour tenter de les contourner. / Elucidating the genetic origin of phenotypic diversity among individuals within the same species is essential to understand evolution. Using whole genome sequences of 1,011 Saccharomyces cerevisiae isolates, my work sought to describe intraspecific genetic variation and investigate of its phenotypic consequences. Doing so, I obtained a precise view of the evolutionary history of S. cerevisiae. Phenotypic characterization provided the opportunity to perform genotype-phenotype genome-wide association studies with unprecedented power. I then focused on the evaluation of the parameters influencing genome-wide association studies, the appreciation of the limits of such an approach, and ways to circumvent them.

Fissura de lábio com ou sem fissura de palato não-sindrômica (FL/P NS) é uma malformação craniofacial frequente, com modelo de herança multifatorial, onde fatores de risco genéticos e ambientais atuam na manifestação da doença. Variações nos níveis de expressão gênica têm sido apontadas como um importante mecanismo de susceptibilidade a doenças complexas, e variantes no DNA que regulam esses níveis de expressão (eQTL) têm sido combinadas a estudos de associação para auxiliar no entendimento da etiologia de algumas doenças. No presente trabalho, integramos eQTLs e estudo de associação para 1) verificar se variantes já associadas com FL/P NS possuem um papel regulatório em células-tronco de músculo orbicular do lábio (OOMMSC, um tecido afetado em FL/P NS), e 2) verificar se eQTLs mapeados em OOMMSC teriam associação com a mesma. Para o primeiro objetivo, verificamos a correlação entre os genótipos das variantes rs642961 e rs590223 e os níveis de expressão de IRF6, e também entre rs987525 e os níveis de expressão de MYC. Não encontramos correlação para nenhuma das três variantes testadas. É possível que essas variantes possuam um papel funcional em algum momento específico da embriogênese, ou mesmo que não tenhamos detectado essa correlação devido ao número amostral analisado (N=46). Para o segundo objetivo, realizamos um estudo de associação do tipo caso-controle dos eQTLs rs5011163, rs1505443, rs4793213, rs4793229 e rs1242500. Não encontramos associação entre nenhuma das cinco variantes e FL/P NS. Uma possível explicação para a associação negativa seria a significância marginal dessas variantes como eQTLs em OOMMSC. Além disso, estudos com baixo poder, como o mapeamento de eQTLs em OOMMSC realizado em outro projeto pelo nosso grupo, geralmente detectam os eQTLs de maior efeito, sendo esses frequentemente compartilhados entre tecidos, e, assim, podem não ter relevância para a doença em si. Outros eQTLs de OOMMSC, selecionados por critérios diferentes do presente estudo, estão sendo testados para associação com FL/P NS, o que nos permitirá avaliar a relevância dessa abordagem para detectar variantes de susceptibilidade a FL/P NS / Nonsyndromic cleft lip with or without cleft palate (NSCL/P) is a frequent craniofacial malformation, with a multifactorial model of inheritance, in which genetic and environmental risk factors act in disease manifestation. Variation of gene expression has been pointed as an important susceptibility mechanism to complex diseases, and DNA variants that regulate expression levels (eQTLs) have been combined with association studies to help elucidate the etiology of some diseases. In the present work, we integrate eQTL and association studies to 1) verify if variants associated with NSCL/P have a regulatory role in orbicularis oris muscle mesenchymal stem cells (OOMMSC, a tissue affected by NSCL/P); and 2) verify if eQTLs mapped in OOMMSC are associated with the disease. For the first goal, we verified the correlation of the rs642961 and rs590223 genotype variants with IRF6 expression levels, and also between the rs987525 genotype and MYC expression levels. We did not find correlation for any of the three variants tested. Possibly, these variants have a functional role in specific moments of embryogenesis, or sample size (N=46) was insufficient to detect correlation. For the second goal, we did a case-control association study for eQTLs rs5011163, rs1505443, rs4793213, rs4793229 and rs1242500. We did not find association between these variants and NSCL/P. The negative association could be explained by the marginal significance of these variants as eQTLs in OOMMSC. Besides, low-power studies, as the OOMMSC eQTL mapping performed in another project by our group, usually detect eQTLs of larger effect, which are frequently shared among tissues; therefore, they may not be relevant for the disease itself. Other eQTLs, selected under different criteria, are currently being tested for association with NSCL/P, which will enable us to evaluate the relevance of this approach to detect susceptibility variants for NSCL/P

Dense Deposit Disease (DDD) causes chronic renal dysfunction which progresses to end-stage renal disease in about half of patients within 10 years of diagnosis. Deficiency of and mutations in complement Factor H (CFH) are associated with the development of DDD, suggesting that dysregulation of the alternative pathway (AP) of the complement cascade is important in disease pathophysiology. Patients with DDD are studied to determine whether specific allele variants of the genes of the alternative pathway of the complement system segregate preferentially with the DDD. We have screened coding and intronic regions of genes of the complement system in DDD cases and controls using PCR, restriction digest and bidirectional sequencing. We have been able to identify novel mutations, allele variants and haplotypes in several genes of the complement system which are associated with the DDD phenotype based on statistical analyses. Since we have identified several genes associated with DDD, we have determined possible gene-gene interactions using computational analyses. We have found a strong synergistic interaction between polymorphisms in CFH and C3. To ascertain if the associated allele variants had a functional impact in the complement activity of an individual, we have obtained blood samples from normal individuals and measured AP complement activity and genotyped CFH and C3 for these samples. Association between AP activity and genotypes is analyzed using statistical methods. Significant association of CFH and C3 variants with AP complement activity has been observed. We also have generated a mice deficient of CFH and Factor D (CFD). CFH deficient mice develop renal pathology similar to DDD in humans. Renal function and complement activity have been determined in the double knockout in comparison to CFH deficient and CFD deficient mice. Results have shown that absence of Factor D can inhibit complement activation in CFH mice. Our data imply that DDD is a complex genetic disease and that genes of the AP complement system contribute to level of complement activity and the pathogenesis of DDD. With this study, we hope to develop an effective diagnosis and treatment plan for DDD patients.

Investigators have discovered thousands of genetic variants associated with various traits using genome-wide association studies (GWAS). These discoveries have substantially improved our understanding of the genetic architecture of many complex traits. Despite the striking success, these trait-associated loci collectively explain relatively little of disease risk. Many reasons for this unexplained heritability have been suggested and two understudied components are hypothesized to have an impact in complex disease etiology: rare variants and gene-environment (GE) interactions. Advances in next generation sequencing have offered the opportunity to comprehensively investigate the genetic contribution of rare variants on complex traits. Such diseases are multifactorial, suggesting an interplay of both genetics and environmental factors, but most GWAS have focused on the main effects of genetic variants and disregarded GE interactions. In this dissertation, we develop statistical methods to detect GE interactions for rare variant analysis for various types of outcomes in both independent and related samples. We leverage the joint information across a set of rare variants and implement variance component score tests to reduce the computational burden. First, we develop a GE interaction test for rare variants for binary and continuous traits in related individuals, which avoids having to restrict to unrelated individuals and thereby retaining more samples. Next, we propose a method to test GE interactions in rare variants for time-to-event outcomes. Rare variant tests for survival outcomes have been underdeveloped, despite their importance in medical studies. We use a shrinkage method to impose a ridge penalty on the genetic main effects to deal with potential multicollinearity. Finally, we compare different types of penalties, such as least absolute shrinkage selection operator and elastic net regularization, to examine the performance of our second method under various simulation scenarios. We illustrate applications of the proposed methods to detect gene x smoking interaction influencing body mass index and time-to-fracture in the Framingham Heart Study. Our proposed methods can be readily applied to a wide range of phenotypes and various genetic epidemiologic studies, thereby providing insight into biological mechanisms of complex diseases, identifying high-penetrance subgroups, and eventually leading to the development of better diagnostics and therapeutic interventions.

Avena sativa L. (2n = 6x = 42, AACCDD genome composition) or common oat is the cereal grain possessing the highest levels of water-soluble seed (1-3,1-4)-β-D-glucan (β-glucan), a hemicellulose important to human health due to its ability to lower serum LDL cholesterol levels. Understanding the mechanisms of β-glucan accumulation in oat endosperm is, consequently, of great interest. We report a genome-wide association study (GWAS) to identify quantitative trait loci (QTLs) controlling β-glucan production in oat, identifying 58 significantly associated markers. Synteny with the barley (Hordeum vulgare L.) genome identified four major regions of interest, the CslF and CslH gene families along with UGPase and AGPase as candidate genes. Subgenome-specific expression of the A, C, and D homoeologs of major β-glucan synthase AsCslF6 revealed that AsCslF6_C is the least expressed in all tissue types and time points, with low-β-glucan varieties recording the highest proportion of AsCslF6_C expression. In order to further investigate the candidate genes identified in our GWAS study and gain a greater understanding of the other cell wall polysaccharides that comprise the total fiber content in oat we sought to characterize five additional genes. Accordingly, we cloned and sequenced the three homoeologs of AsUGP and AsAGPS1. AsAGPS1 is the small subunit 1 gene of the enzyme ADP-glucose pyrophosphorylase (AGPase), which is responsible for catalyzing the first committed step in the starch biosynthesis pathway through the production of ADP-glucose. AsUGP is the gene the codes for UDP-glucose pyrophosphorylase (UGPase) an enzyme responsible for the reversible production of UDP-glucose (UDPG). UDPG is used directly or indirectly as a precursor for the biosynthesis of cell wall polysaccharides. In high β-glucan mutant line ‘OT3044’ we observed increased expression of AsUGP with a corresponding reduction of AsAGPS1 expression. Similarly, we observed an inverse expression pattern in low-fiber mutant line ‘OT3018’, wherein AsUGP expression was decreased in favor of AsAGPS1 expression. Further, we also found evidence that these changes in both AsUGP and AsAGPS1 expression are due primarily to up- or down-regulation in the A-genome homoeoalleles. Additionally, we characterized genes in the CslC family (CslC4, CslC9) and CslA family (CslA7) responsible for xyloglucan and glucomannan synthesis, respectively. High-fiber line ‘HiFi’ showed the least amount of overall expression of these three genes, raising the possibility that the increased β-glucan is due to a reduction in other hemicelluloses. After analyzing homoeolog-specific expression in multiple genes we observed that the A genome consistently had the most highly expressed homoeoallele, hinting at a universal preference for expression of this subgenome. We present hypotheses regarding multiple points in carbohydrate metabolism having the potential to alter β-glucan content in oat.

Objective: We aimed to identify novel, functional, replicable and genome-wide significant risk regions specific for alcohol dependence using genome-wide association studies (GWASs). Methods: A discovery sample (1409 European-American cases with alcohol dependence and 1518 European-American controls) and a replication sample (6438 European-Australian family subjects with 1645 alcohol dependent probands) underwent association analysis. Nineteen other cohorts with 11 different neuropsychiatric disorders served as contrast groups. Additional eight samples underwent expression quantitative locus (eQTL) analysis. Results: A genome-wide significant risk gene region (NKAIN1-SERINC2) was identified in a meta-analysis of the discovery and replication samples. This region was enriched with 74 risk SNPs (unimputed); half of them had significant cis-acting regulatory effects. The distributions of -log(p) values for the SNP-disease associations or SNP-expression associations in this region were consistent throughout eight independent samples. Furthermore, imputing across the NKAIN1-SERINC2 region, we found that among all 795 SNPs in the discovery sample, 471 SNPs were nominally associated with alcohol dependence (1.7×10-7≤p≤0.047); 53 survived region- and cohort-wide correction for multiple testing; 92 SNPs were replicated in the replication sample (0.002≤p≤0.050). This region was neither significantly associated with alcohol dependence in African-Americans, nor with other non-alcoholism diseases. Finally, transcript expression of genes in NKAIN1-SERINC2 was significantly (p<3.4×10-7) associated with expression of numerous genes in the neurotransmitter systems or metabolic pathways previously associated with alcohol dependence. Conclusion: NKAIN1-SERINC2 may harbor a causal variant(s) for alcohol dependence. It may contribute to the disease risk by way of neurotransmitter systems or metabolic pathways.

Objective: We aimed to identify novel, functional, replicable and genome-wide significant risk regions specific for alcohol dependence using genome-wide association studies (GWASs). Methods: A discovery sample (1409 European-American cases with alcohol dependence and 1518 European-American controls) and a replication sample (6438 European-Australian family subjects with 1645 alcohol dependent probands) underwent association analysis. Nineteen other cohorts with 11 different neuropsychiatric disorders served as contrast groups. Additional eight samples underwent expression quantitative locus (eQTL) analysis. Results: A genome-wide significant risk gene region (NKAIN1-SERINC2) was identified in a meta-analysis of the discovery and replication samples. This region was enriched with 74 risk SNPs (unimputed); half of them had significant cis-acting regulatory effects. The distributions of -log(p) values for the SNP-disease associations or SNP-expression associations in this region were consistent throughout eight independent samples. Furthermore, imputing across the NKAIN1-SERINC2 region, we found that among all 795 SNPs in the discovery sample, 471 SNPs were nominally associated with alcohol dependence (1.7×10-7≤p≤0.047); 53 survived region- and cohort-wide correction for multiple testing; 92 SNPs were replicated in the replication sample (0.002≤p≤0.050). This region was neither significantly associated with alcohol dependence in African-Americans, nor with other non-alcoholism diseases. Finally, transcript expression of genes in NKAIN1-SERINC2 was significantly (p<3.4×10-7) associated with expression of numerous genes in the neurotransmitter systems or metabolic pathways previously associated with alcohol dependence. Conclusion: NKAIN1-SERINC2 may harbor a causal variant(s) for alcohol dependence. It may contribute to the disease risk by way of neurotransmitter systems or metabolic pathways.

The field of cancer genomics is currently being enhanced by the power of Epigenome-wide association studies (EWAS). Over the last couple of years comprehensive sequence data sets have been generated, allowing analysis of genome-wide activity in cohorts of different individuals to be increasingly available. Finding associations between epigenetic variation and phenotype is one of the biggest challenges in biomedical research. Laboratories lacking dedicated resources and programming experience require bioinformatics expertise which can be prohibitively costly and time-consuming. To address this, we have developed a collection of freely available Galaxy tools (Poterlowicz, 2018a), combining analytical methods into a range of convenient analysis pipelines with graphical user-friendly interface.The tool suite includes methods for data preprocessing, quality assessment and differentially methylated region and position discovery. The aim of this project was to make EWAS analysis flexible and accessible to everyone and compatible with routine clinical and biological use. This is exemplified by my work undertaken by integrating DNA methylation profiles of melanoma patients (at baseline and mitogen-activated protein kinase inhibitor MAPKi treatment) to identify novel epigenetic switches responsible for tumour resistance to therapy (Hugo et al., 2015). Configuration files are publicly published on our GitHub repository (Poterlowicz, 2018b) with scripts and dependency settings also available to download and install via Galaxy test toolshed (Poterlowicz, 2018a). Results and experiences using this framework demonstrate the potential for Galaxy to be a bioinformatics solution for multi-omics cancer biomarker discovery tool.