The use of nitrogen (N) fertilizers is both costly to farmers and contributes to environmental degradation. N applied to wheat accounts for 18% of N applied to farmland globally, making it a prime target for reducing and optimizing N application. Chapter I is a review on nitrogen use efficiency (NUE) in wheat, with emphasis on breeding efforts and genetic resources available to increase NUE. The concept of effective use of nitrogen (EUN) as yield per unit N applied as a measure of N use, is also introduced. Chapter II is a study using two bi-parental double haploid families to evaluate genetic variability of both the genetic main effects (intercept) and linear response to N (slope) and determine the feasibility of selection for EUN in wheat. Using cross validation, a genomic prediction accuracy of 0.68 for intercept and 0.50 for slope was found, indicating that EUN is under genetic control and can be selected for. The prospect of breeding for EUN under limited resources, i.e., using fewer N rates and fewer experimental plots, is also explored. It was found that two different N treatments can be used to produce accurate predictions of intercept and slope as high as 0.98 and 0.95, respectively. Chapter III uses the same population described in chapter II to further investigate feasibility of selection for EUN using a normalized difference vegetation index (NDVI) obtained from multi-spectral aerial images gathered throughout the growing season. Cumulative photosynthesis across the growing season was estimated by integration across the NDVI curve, and compared to grain yield estimates to determine the efficacy of aerial imaging to identify high EUN lines. NDVI values and the area under the NDVI curve were able to predict yield and had the strongest ability to predict yield in moderate to low N treatments, with R2 values as high as 0.81 and 0.78 respectively. / Master of Science / Chapter I is a review on nitrogen use efficiency (NUE) in wheat, with emphasis on breeding efforts and genetic resources available to increase NUE. The concept of effective use of nitrogen (EUN) defined as grain yield per unit N applied, is contrasted to NUE as a more economic breeding goal. Chapter II uses two bi-parental mapping populations to evaluate genetic variability of both the genetic main effects and the linear response to N and determine the feasibility of selection for EUN in wheat. The efficacy of genomic prediction for EUN is explored and the prospect of breeding for EUN under limited resources is also explored. Chapter III uses the same populations described in chapter II to further investigate the feasibility of selection for EUN using a normalized difference vegetation index (NDVI) obtained from multi-spectral aerial images gathered throughout the growing season. Cumulative photosynthesis across the growing season was estimated and found to be predictive of grain yield estimates at accuracies ranging from 0.31 to 0.78.

In multiple species, genome-wide association (GWA) studies have become an increasingly prevalent method of identifying the quantitative trait loci (QTLs) that underlie complex traits. Despite this, relatively few GWA analyses using high-density genomic markers have been carried out on highly quantitative traits in wheat. We utilized single-nucleotide polymorphism (SNP) data generated via a genotyping-by-sequencing (GBS) protocol to perform GWA on multiple yield-related traits using a panel of 329 soft red winter wheat genotypes grown in four environments. In addition, the SNP data was used to examine linkage disequilibrium and population structure within the testing panel. The results indicated that an alien translocation from the species Triticum timopheevii was responsible for the majority of observed population structure. In addition, a total of 50 significant marker-trait associations were identified. However, a subsequent study cast some doubt upon the reproducibility and reliability of plant QTLs identified via GWA analyses. We used two highly-related panels of different genotypes grown in different sets of environments to attempt to identify highly stable QTLs. No QTLs were shared across panels for any trait, suggesting that QTL-by-environment and QTL-by-genetic background interaction effects are significant, even when testing across many environments. In light of the challenges involved in QTL mapping, prediction of phenotypes using whole-genome marker data is an attractive alternative. However, many evaluations of genomic prediction in crop species have utilized univariate models adapted from animal breeding. These models cannot directly account for genotype-by-environment interaction, and hence are often not suitable for use with lower-heritability traits assessed in multiple environments. We sought to test genomic prediction models capable of more ad-hoc analyses, utilizing highly unbalanced experimental designs consisting of individuals with varying degrees of relatedness. The results suggest that these designs can successfully be used to generate reasonably accurate phenotypic predictions. In addition, multivariate models can dramatically increase predictive accuracy for some traits, though this depends upon the quantity and characteristics of genotype-by-environment interaction. / Ph. D.

A tropical forage breeding program contains several peculiarities, especially when it involves polyploid species and facultative apomixis. Despite their importance, there is still a lack of information on genetic studies of critical forage traits and on the employment of genomic tools when compared to other crops and temperate forages. The genus Brachiaria is the most important for forage in tropical regions mainly beef production. The commercial species in this genus are excellent perennial forage, and the identification of superior genotypes depends on the selection of many characteristics under complex genetic control, with high cost and time-consuming evaluation. Therefore, the knowledge about uses and applications of classic and genomic tools in forage traits may be useful to support breeding programs and the development of new cultivars. In this context, the aim was to evaluate several different classic and genomic tools to be employed as selection strategies in a traditional tropical forage breeding program. A panel of tetraploid hybrids obtained from crossing Urochloa brizantha x Urochloa ruziziensis was phenotyped and genotyped to evaluate genetic parameters and perform genomic studies. The classic phenotypic analysis showed no clear trend of the importance of additive and non-additive genetics effects for agronomical and nutritional traits. The Mulamba and Mock index should be used in the univariate level, due to the promotion of a more balanced response to selection for all traits in the multivariate selection. In the genomic extraction and evaluations, the reads that were aligned to a \'mock\' reference genome, created from GBS data of the cultivar \'Marandu\', had more SNP discovered compared to the closest true reference genomes, Setaria viridis and S. italica. We recommended different thresholds of sample depth and genotype quality (GQ) to eliminate poor quality reads without introducing genotype bias. Cross-validation revealed that missing genotypes were imputed with a median accuracy of 0.85 using Random Forest algorithm to produce a complete genotype matrix, regardless of heterozygote frequency. The genome-wide association analysis (GWAS) revealed candidate genes associated with many tropical forage traits across all cutting seasons, which could be the first step toward marker-assisted selection (MAS). Moreover, our results suggest that accounting for allele dosage is essential, since the tetraploid level provided more information about the true biological state. Therefore, our findings revealed the complexity of the genetic architecture of Urochloa spp. traits and provided important insights towards the application of GWAS in polyploids species. The genomic selection analysis revealed that GBLUP-A (additive) and GBLUP-AD (additive + dominance) showed similar prediction abilities considering both single and multi-trait models. Conversely, combining GBLUP-AD and tetraploid information could improve the selection coincidence. Furthermore, the multi-trait validation scheme 2 (VS2), where one trait is not evaluated for some individuals, provided an increment of up to 30% to the prediction ability. Therefore, it is an useful strategy for traits with low heritability. Overall, all genomic selection models considered provided greater genetic gains than the phenotypic selection. Similarly, the allele dosage associated with additive, dominance and multi-trait factors increased the accuracy of genomic prediction models for interspecific polyploid hybrids. Finally, genomic tools should be used in forages breeding programs in order to reduce cost and time. / Um programa de melhoramento de forragem tropical contém várias peculiaridades, especialmente quando se trata de espécies poliplóides e de apomixia facultativa. Apesar de sua importância, atualmente, faltam informações sobre estudos genéticos de características forrageiras e sobre o emprego de ferramentas genômicas quando comparadas a outras culturas e forragens de clima temperado. O gênero Brachiaria é o mais importante para formação de pastagens nas regiões tropicais, principalmente para produção de carne bovina. As espécies comerciais deste gênero são excelentes forrageiras perenes, e a identificação de genótipos superiores depende da seleção de muitas características sob controle genético complexo, com alto custo e avaliação demorada. Portanto, o conhecimento sobre usos e aplicações de ferramentas clássicas e genômicas em características forrageiras pode ser útil para apoiar programas de melhoramento e o desenvolvimento de novas cultivares. Nesse contexto, objetivou-se avaliar diversas ferramentas clássicas e genômicas a serem empregadas como estratégias de seleção em um programa tradicional de melhoramento de forrageiras tropicais. Um painel de híbridos tetraplóides obtidos do cruzamento Urochloa brizantha x Urochloa ruziziensis foi fenotipado e genotipado para avaliar parâmetros genéticos e realizar estudos genômicos. Para a análise fenotípica clássica, concluímos que não havia uma tendência clara da importância dos efeitos genéticos aditivos e não-aditivos para características agronômicas e nutricionais. O índice de Mulamba e Mock deve ser usado no nível univariado, devido à promoção de uma resposta mais equilibrada à seleção para todas as características na seleção multivariada. Na extração e nas avaliações genômicas, as leituras que foram alinhadas ao genoma de referência \'simulado\', criado a partir dos dados de GBS da cultivar \'Marandu\', tiveram a maior porcentagem de descoberta de marcadores SNP comparado aos genomas de referência mais próximos, Setaria viridis e S. italica. Recomendamos diferentes limiares de profundidade de leitura e qualidade de genótipo (GQ) para eliminar leituras de baixa qualidade sem introduzir viés de chamada de genótipo. A validação cruzada revelou que os genótipos ausentes foram imputados com uma precisão mediana de 0,85 pelo algoritmo Random Forest para produzir uma matriz genotípica completa, independentemente da frequência de heterozigotos. A análise de associação genômica ampla (GWAS) revelou genes candidatos associados a muitas características forrageiras tropicais, o que poderia ser o primeiro passo em direção à seleção assistida por marcadores (MAS). Além disso, nossos resultados sugerem que a contabilização da dosagem alélica é essencial, uma vez que o nível tetraploide fornece mais informações sobre o verdadeiro estado biológico. Portanto, nossos achados revelam a complexidade da arquitetura genética de características de Urochloa spp. e fornecem informações importantes para a aplicação de GWAS em espécies poliploides. A análise de seleção genômica revela que o GBLUP-A (aditivo) e o GBLUP-AD (aditivo + dominância) mostraram capacidades de predição semelhantes, considerando tanto os modelos simples quanto os multi-característica. Por outro lado, combinando-se GBLUP-AD e informação tetraploide foi possível melhorar a coincidência de seleção. Além disso, o esquema de validação multi-característica 2 (VS2), onde uma característica não é avaliada para alguns indivíduos, pode fornecer um incremento de até 30% da capacidade de previsão. Portanto, é uma estratégia útil para características com baixa herdabilidade. No geral, todos os modelos de seleção genômica considerados proporcionaram maiores ganhos genéticos do que a seleção fenotípica tradicional. Da mesma forma, a dosagem do alelo associado a fatores aditivos, de dominância e multicaracteres aumentou a acurácia dos modelos genômicos de predição para híbridos poliploides interespecíficos. Finalmente, ferramentas genômicas devem ser utilizadas em programas de melhoramento de forragens para reduzir custos e tempo.

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.

This thesis develops and evaluates statistical methods for different types of genetic analyses, including quantitative trait loci (QTL) analysis, genome-wide association study (GWAS), and genomic evaluation. The main contribution of the thesis is to provide novel insights in modeling genetic variance, especially via random effects models. In variance component QTL analysis, a full likelihood model accounting for uncertainty in the identity-by-descent (IBD) matrix was developed. It was found to be able to correctly adjust the bias in genetic variance component estimation and gain power in QTL mapping in terms of precision.  Double hierarchical generalized linear models, and a non-iterative simplified version, were implemented and applied to fit data of an entire genome. These whole genome models were shown to have good performance in both QTL mapping and genomic prediction. A re-analysis of a publicly available GWAS data set identified significant loci in Arabidopsis that control phenotypic variance instead of mean, which validated the idea of variance-controlling genes.  The works in the thesis are accompanied by R packages available online, including a general statistical tool for fitting random effects models (hglm), an efficient generalized ridge regression for high-dimensional data (bigRR), a double-layer mixed model for genomic data analysis (iQTL), a stochastic IBD matrix calculator (MCIBD), a computational interface for QTL mapping (qtl.outbred), and a GWAS analysis tool for mapping variance-controlling loci (vGWAS).

This thesis develops and evaluates statistical methods for different types of genetic analyses, including quantitative trait loci (QTL) analysis, genome-wide association study (GWAS), and genomic evaluation. The main contribution of the thesis is to provide novel insights in modeling genetic variance, especially via random effects models. In variance component QTL analysis, a full likelihood model accounting for uncertainty in the identity-by-descent (IBD) matrix was developed. It was found to be able to correctly adjust the bias in genetic variance component estimation and gain power in QTL mapping in terms of precision.  Double hierarchical generalized linear models, and a non-iterative simplified version, were implemented and applied to fit data of an entire genome. These whole genome models were shown to have good performance in both QTL mapping and genomic prediction. A re-analysis of a publicly available GWAS data set identified significant loci in Arabidopsis that control phenotypic variance instead of mean, which validated the idea of variance-controlling genes.  The works in the thesis are accompanied by R packages available online, including a general statistical tool for fitting random effects models (hglm), an efficient generalized ridge regression for high-dimensional data (bigRR), a double-layer mixed model for genomic data analysis (iQTL), a stochastic IBD matrix calculator (MCIBD), a computational interface for QTL mapping (qtl.outbred), and a GWAS analysis tool for mapping variance-controlling loci (vGWAS).

Doctor of Philosophy / Genetics - Plant Pathology / Jesse A. Poland / The global population is estimated to reach 9.1 billion by 2050. Together with climate change, insuring food security for this population presents a significant challenge to agriculture. In this context, a large number of breeding objectives must be targeted. The focus of the work presented here is to explore genomic approaches for tapping exotic germplasm for valuable alleles to increased yield, disease resistance and abiotic stress tolerance. The loss of genetic diversity in bread wheat (Triticum aestivum L.) due to bottlenecks during polyploidization, domestication and modern plant breeding can be compensated by introgressing novel exotic germplasm. Here, the potential of genomic selection (GS) for rapid introgression of synthetic derived wheat is evaluated in field trials. Overall, the GS models had moderate predictive ability. However, prediction accuracies were lower than expected likely due to complex and confounding physiological effects. As such, implementation of rapid cycle GS for introgression of exotic alleles is possible but might not perform very well with synthetic derived wheat. Disease resistance is another important trait affecting grain yield. Stem rust (Puccinia graminis f. sp. tritici) has historically caused severe yield loss of wheat worldwide. In a quantitative trait loci (QTL) mapping study with a synthetic-derived mapping population, QTLs for resistance to stem rust races TRTTF and QTHJC were identified on chromosomes 1AS, 2BS, 6AS and 6AL. Some of these genes could be new resistance genes and useful for marker-assisted selection (MAS). In addition to food insecurity through lack of sufficient source of calories, nutrient deficiency is considered the ‘hidden hunger’ and can lead to serious disorders in humans. Through biofortification, essential nutrients are increased in staple crops for improved quality of food and human health. A high-throughput elemental profiling experiment was performed with the same synthetic derived mapping population to study the wheat ionome. Twenty-seven QTL for different elements in wheat shoots and two QTL in roots were identified. Four “hotspots” for nutrient accumulation in the shoots were located on chromosomes 5AL, 5BL, 6DL and 7AL. Overall, exotic germplasm is a valuable source of favorable alleles, but improved breeding methodologies are needed to rapidly utilize this diversity.

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.

Submitted by Ubirajara Cruz (ubirajara.cruz@gmail.com) on 2018-06-04T16:46:17Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) tese_carlos_ferreira.pdf: 752331 bytes, checksum: 1791efb2b3372ab1fb6e88d0ec2a0e2f (MD5) / Approved for entry into archive by Aline Batista (alinehb.ufpel@gmail.com) on 2018-06-05T11:53:24Z (GMT) No. of bitstreams: 2 tese_carlos_ferreira.pdf: 752331 bytes, checksum: 1791efb2b3372ab1fb6e88d0ec2a0e2f (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2018-06-05T11:53:24Z (GMT). No. of bitstreams: 2 tese_carlos_ferreira.pdf: 752331 bytes, checksum: 1791efb2b3372ab1fb6e88d0ec2a0e2f (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2017-02-22 / A fertilidade dos reprodutores é de suma importância para a maximização das taxas de prenhez e melhoramento genético. O exame andrológico é uma importante ferramenta para a identificação de reprodutores sub férteis e para o monitoramento da qualidade seminal. Porém, poucas características do exame estão correlacionadas com a fertilidade in vivo. Assim, é fundamental a identificação de métodos que possam auxiliar na seleção mais precisa dos futuros reprodutores. Os objetivos do primeiro trabalho foram avaliar as acurácias e o viés das predições genômicas, utilizando diferentes métodos, para a característica perímetro escrotal ajustado à idade e ajustado à idade e peso em touros das raças Hereford e Braford. Os valores estimados para a herdabilidade apresentaram magnitude moderada a alta (0,39 a 0,48), demonstrando que é possível a obtenção de ganhos genéticos a partir da seleção. A predição de valores genéticos utilizando informações genômicas pelos métodos índice de seleção e single-step possibilitou o aumento de acurácia (em torno de 30%) para as características estudadas. Os ganhos de acurácia obtidos com os métodos, combinando as informações tradicionais com a genômica em relação ao método BLUP tradicional indicam que as predições genômicas podem ser usadas como ferramenta para melhorar os ganhos genéticos e reduzir o intervalo de gerações. Já o segundo artigo teve como objetivos: determinar a expressão de RNAm das paraoxonases (PON) 1, 2 e 3 no parênquima testicular, vesículas seminais e epidídimo de touros, avaliar a atividade de PON1 na circulação sanguínea e no plasma seminal; e correlacionar esta atividade com características avaliadas durante o exame andrológico. A caracterização da expressão dos genes foi realizada por qRT-PCR e a determinação da atividade de PON1 foi realizada em amostras de soro e plasma seminal provenientes de 110 touros. As PON 1, 2 e 3 foram expressas no parênquima testicular dos animais analisados. Observou-se uma correlação positiva entre a atividade sérica e seminal de PON1 com diversos indicadores de fertilidade. / Male fertility is important to optimize pregnancy rates and genetic improvement. Breeding soundness evaluations are key tools to identify sub fertile males and to survey characteristics of sperm quality. However, few sperm quality traits are correlated with fertility in vivo. Thus, it is essential to identify methods that can assist in more precise selection of future bulls. The goals of the first study were to evaluate the accuracy and the bias of the genomic predictions, using different methods, for the characteristic scrotal perimeter adjusted to age and adjusted to age and weight in Hereford and Braford bulls. The estimates for the heritability showed moderate to high magnitude (0.39 to 0.48), demonstrating that it is possible to obtain genetic gains from selection. The prediction of genetic values using genomic information by methods of selection index and single-step made possible the increase of accuracy (around 30%) for the characteristics studied. The gains in accuracy obtained with the methods, combining the traditional with the genomic information compared to traditional BLUP method indicate that the genomic predictions can be used as a tool to improve the genetic gains and reduce the range of generations. The second article had as its objectives: to determine the mRNA expression of paraoxonases (PON) 1, 2 and 3 in the testicular parenchyma, seminal vesicles, and epididymis of bulls, to evaluate the activity of PON1 in the bloodstream and in seminal plasma; and to correlate that activity with characteristics of breeding soundness. Characterization of gene expression by qRT-PCR and the determination of PON1 activity were performed in serum and seminal plasma from bulls 110. The PON 1, 2 and 3 were expressed in testicular parenchyma of the animals examined. There was a positive correlation between activity and serum PON1 seminal with different breeding soundness estimators.

La production agricole doit augmenter à un rythme jamais atteint pour faire face à la forte hausse attendue de la demande alimentaire. La sélection génomique (SG) pourrait y contribuer en donnant la possibilité de sélectionner des individus uniquement sur leur génotype, rendant ainsi l'amélioration génétique des rendements plus efficace. L'amélioration actuelle de la production du palmier à huile, première plante oléagineuse au monde, se fait par sélection récurrente réciproque pour produire des hybrides. L'intégration de la SG à ce schéma aurait des retombées majeures. Cette thèse vise à évaluer le potentiel de la SG pour prédire les aptitudes à la combinaison hybride dans les populations parentales (Deli et groupe B).Des données du dernier cycle d'amélioration ont permis d'obtenir la première estimation empirique de la précision de la SG. Malgré les petites populations disponibles pour calibrer le modèle génomique, cette étude a montré qu'avec des candidats à la sélection apparentés à la population de calibration (plein-frères, descendants), la précision était suffisante pour faire une présélection sur certaines composantes du rendement dans le groupe B. Par ailleurs, des simulations sur quatre générations ont montré que, pour plusieurs stratégies de SG (en particulier avec une calibration faite uniquement à la première génération en incluant des génotypes d'hybrides), la précision de sélection chez les individus non testés en croisement était suffisante pour sélectionner des parents uniquement sur leur génotype. Ceci a abouti à une augmentation de plus de 50% du gain génétique annuel. Une augmentation pus rapide de la consanguinité a aussi été mise en évidence, mais elle pourrait être limitée par des méthodes classiques de gestion de la consanguinité. Finalement, les données expérimentales et simulées indiquent que la SG pourrait diminuer l'intervalle moyen de génération et accroître l'intensité de sélection, accélérant ainsi considérablement le progrès génétique sur le rendement en huile de palme. Un schéma de sélection génomique récurrente réciproque est proposé pour le palmier à huile. Son application nécessite de confirmer expérimentalement les simulations en estimant sur plusieurs générations la précision de sélection sans recalibration du modèle. Ces futures recherches devraient utiliser les nouveaux modèles de SG, potentiellement plus efficaces (prise en compte des effets non additifs ou d'informations a priori sur les effets des marqueurs, etc.). / Agricultural production must increase at an unprecedented rate to meet the strong growth expected in food demand. Genomic selection (GS) could contribute to reaching this goal by allowing selection of individuals on their sole genotype, making breeding more efficient. Breeding for yield in oil palm, the first oil crop in the world, is currently based on hybrid production by reciprocal recurrent selection. The integration of GS to this scheme would have major repercussions. This thesis aims to assess the potential of GS to predict hybrid combining abilities in parental populations (Deli and group B). Data from the last breeding cycle were used to obtain the first empirical estimate of GS accuracy. Despite the small populations available to calibrate the genomic model, the study showed that with candidates related to the training population (sibs, progenies), the accuracy was sufficient to make a pre-selection in the group B on some yield components. In addition, simulations over four generations showed that the accuracy of several GS strategies (especially when training the model only in the first generation using hybrid genotypes) was high enough for non progeny tested individuals to allow selecting among them on their genotype. This resulted in an increase of more than 50% of annual genetic gain compared to traditional breeding. A faster increase in inbreeding was also demonstrated, but this could be limited by conventional methods of inbreeding management. Finally, the experimental and simulated data indicated that GS could reduce the average generation interval and increase the selection intensity, vastly speeding up the genetic progress for oil palm yield. A recurrent reciprocal genomic selection scheme was suggested for oil palm. Its application requires an experimental confirmation of the simulations, by estimating GS accuracy over several generations without retraining the model. Future research should use new GS models, potentially more effective (taking into account non additive effects or a priori information on marker effects, etc.).