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.

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.

Fusarium verticillioides è l’agente responsabile della Fusariosi della Spiga del mais, contamina la granella con fumonisine, micotossine responsabili di diverse patologie umane e animali. Per la resistenza alla fusariosi e all’accumulo di fumonisine esiste variabilità tra genotipi diversi ma non sono ancora disponibili ibridi immuni. L’obiettivo di questo lavoro è stato quello di individuare marcatori associati alla resistenza a F. verticillioides. Mediante un bioassay è stato testato un association panel per la resistenza a F. verticillioides. Al fine di identificare i marcatori di resistenza sono stati applicati un approccio GWAS e uno per geni candidati. L’analisi GWAS è stata eseguita con 227K SNPs restituendo 206 marcatori significativi. Da un lavoro di RNASequencing sono stati individuati i geni coinvolti nella risposta a F. verticillioides mentre i geni R sono stati recuperati della letteratura scientifica. Genotipi resistenti (CO433 e CO441) e suscettibili (CO354 e CO389) sono stati scelti per individuare polimorfismi nei geni candidati da associare ai fenotipi rilevati mediante il bioassay. Quattro marcatori sono risultati significativi. Infine, la correlazione tra l’incidenza della fusariosi rilevata in campo e mediante bioassay è stata analizzata in una popolazione di 172 RIL derivanti da CO441 x CO354, tuttavia, non è stata individuata alcuna corrispondenza. / Fusarium verticillioides is the causal agent of Fusarium ear rot (FER) in maize and contaminates grains with fumonisin, a family of mycotoxins involved in several human and animal diseases. Quantitative genetic variation exists for resistance to FER and fumonisin contamination among genotypes, however, resistant maize hybrids are currently not available. The aim of this work was the identification of genetic markers associated to resistance against F. verticillioides. A bioassay was used to screen inbred lines of the maize association population for FER resistance, GWAS and candidate gene approaches were applied to identify markers. GWAS was performed using a 227K SNP matrix and resulting in 206 significant markers. Genes involved in F. verticillioides response in developing maize kernels were retrieved from a previous RNASequencing study while maize R genes were retrieved from scientific literature. Resistant (CO433 and CO441) and susceptible genotypes (CO389 and CO354) were selected to amplify and sequence candidate genes. Polymorphisms detected were used to find association with phenotypes scored using the bioassay. Four significant markers were found. Finally, the correlation between FER phenotypes scored in field experiments and bioassay phenotypes was investigated. A population of 172 RILs (CO441 x CO354), was tested. No correlation was found.

The case-control design is one of the most commonly used designs in genome- wide asociation studies. When we increase the sample size of either the controls or, more importantly, the cases, the power of whatever test we use will certainly increase. However increasing the sample size, means that addi- tional individuals need to be genotyped and this implies extra financial costs. However, nowadays with the emergence of genetic studies, a large number of genetic data are available at low or no extra cost. Even though those data may not be completely relevant to the current study, they can still be used to increase the probability to identify true associations. Furthermore, additional information, non-necessarily genetic, can also be used to improve the power of a method. In this thesis we extend the case-control design in order to take ad- vantage of such types of additional data and/or information. We discuss three designs; the case-cohort-control, the kin-cohort and the super-case– case–control–super-control designs. For each of these, we present methods that are adjusted or modified versions of standard case-control methods but we also propose novel ones developed with those extended designs in mind. Ultimately, we describe how those methods can be used in order to increase the power of association tests, especially compared to similar methods of the case-control design.

The aims of this study were to analyse known and potential biomarkers of common and genetically complex human disorders and to identify genetic and environmental variation associated with plasma biomarker concentrations. Two groups of protein biomarkers were analysed. First, plasma complement factor H (CFH) was selected as a potential biomarker for age-related macular degeneration (AMD), since common variants in the CFH gene show strong association with this disorder. Secondly, two isoforms of amyloid-β (Aβ40 and Aβ42) were selected as biomarkers for Alzheimer disease (AD) since Aβ deposits are major constituents of the amyloid plaques characteristic of this disorder. Physiological and anthropometric measurements and samples of human and genomic DNA were collected from a population sample of 1,021 individuals from the Croatian island of Vis. Quantitative determination of plasma Aβ40 and Aβ42 concentrations was performed using enzyme-linked immunosorbent assays. Heritabilities and significant covariate effects were estimated for each trait in the Croatian data set. Genome-wide linkage and association analyses were conducted for the biomarker traits. A novel finding was the genome-wide significant association between a CFH and several polymorphisms close to and within the CFH gene. The strongest association was with an intronic SNP within CFH, which explained 28% of the total trait variance (P < 10-50). The association was also replicated in a Dutch sample set. A SNP haplotype was identified which accounted for a higher proportion of the phenotypic variance. Conditional haplotype analysis showed that the effect of this haplotype on plasma CFH concentration was independent of the CFH Y402H variant, and significantly stronger than a deletion of the adjacent CFHR3/CFHR1 which was already known to affect AMD susceptibility. Genetic analysis of 382 AMD cases and 201 controls was consistent with the CFH Y402H variant being the strongest AMD susceptibility locus. Variation in plasma CFH concentration was found to explain up to 1.8% of the variation in susceptibility to AMD with an odds 2.1 (95% C.I. 1.3-3.4, P = 0.003). SNPs that were strongly associated with a CFH concentration also influenced AMD susceptibility (P < 0.05) independently of the CFH Y402H polymorphism. Functional analysis of genomic regions associated with plasma CFH is needed to identify the causal variants. Associations were observed between plasma Aβ40 concentration and several novel candidate loci, spanning regions of approximately 0.2 Mb, on chromosomes 9 and X. Similarly, novel associations with plasma Aβ42 were found in several regions, each spanning 0.2-0.4 Mb, on chromosomes 2, 5, 9, 15 and 20. The proportion of the phenotypic variance in plasma Aβ42 explained by these putative associations ranged between 1.8 and 2.8%. However, none of the associated SNPs was significant after correction for multiple testing, therefore replication is required. Finally, attempts were made to identify and quantitate new protein biomarkers of disease in human plasma using mass spectrometry. Development and optimisation of techniques was initially undertaken to deplete high-abundance plasma proteins and improve signal:noise ratio. This allowed the assessment of downstream proteomic approaches including MALDI-TOF mass spectrometry (MS), capillary electrophoresis (CE) and ion exchange chromatography (IEC), each with the potential for large-scale quantitation of plasma proteins. Although the analysis of single protein analytes, using CE and IEC proved promising, the results highlighted the difficulty associated with MALDI-TOF and protein ionisation techniques in analysing complex mixtures such as plasma.

Doctor of Philosophy / Genetics Interdepartmental Program / Jesse A. Poland / A central question in modern biology is to understand the genotype-to-phenotype (G2P) link, that is, how the genetics of an organism results in specific characteristics. However, prediction of phenotypes from genotypes is a difficult problem due to the complex nature of genomes, the environment, and their interactions. While the recent advancements in genome sequencing technologies have provided almost unlimited access to high-density genetic markers, large-scale rapid and accurate phenotyping of complex plant traits remains a major bottleneck. Here, we demonstrate field-based complex trait assessment approaches using a commercially available light-weight Unmanned Aerial Systems (UAS). By deploying novel data acquisition and processing pipelines, we quantified lodging, ground cover, and crop growth rate of 1745 advanced spring wheat lines at multiple time-points over the course of three field seasons at three field sites in South Asia. High correlations of digital measures to visual estimates and superior broad-sense heritability demonstrate these approaches are amenable for reproducible assessment of complex plant traits in large breeding nurseries. Using these validated high-throughput measurements, we applied genome-wide association and prediction models to assess the underlying genetic architecture and genetic control. Our results suggest a diffuse genetic architecture for lodging and ground cover in wheat, but heritable genetic variation for prediction and selection in breeding programs. The logistic regression-derived parameters of dynamic plant height exhibited strong physiological linkages with several developmental and agronomic traits, suggesting the potential targets of selection and the associated tradeoffs. Taken together, our highly reproducible approaches provide a proof-of-concept application of UAS-based phenomics that is scalable to tens-of-thousands of plots in breeding and genetic studies as will be needed to understand the G2P and increase the rate of gain for complex traits in crop breeding.