Utilização de informações genômicas para o melhoramento genético de características da carne em bovinos da raça Nelore

Consumers have become stricter for higher quality meat and are seeking for traits such as tenderness, color and flavor. Few has been done for improving meat quality traits, due to the difficultness and high cost to measure, as well as to the necessity of culling animals. An alternative to inclusion of these measures in breeding programs may be the use of SNPs in association studies and genomic selection. Animals Nellore (1,875) were feedlot finished and slaughtered at commercial slaughterhouses were used, with an average age of 731 ± 81 days. The samples were analyzed for tenderness, lipid content, marbling, lightness (L*), redness (a*) and yellowness (b*). The animals were genotyped with a panel of 777,962 SNPs (IlluminaBovineHDBeadchip) and after quality control remained 1,634 animals with genotypes and 369,722 SNPs. In chapter 2, three genomic selection methods were evaluated: GBLUP (assumes normal distribution with variance only for all SNPs effects), BayesCπ (mixed distribution to the SNPs effects) and Bayesian Lasso (assumes double exponential distribution for SNPs effects). The adjusted phenotype for the fixed effects (Yc) and the estimated breeding value (EBV) were used as pseudo-phenotypes. For cross-validation, the population was randomly divided into five groups of similar sizes. To compare the predictive ability of the methods, the following procedures were used: correlation between the genomic values (GEBV) and the adjusted phenotypes and the correlation value divided by the square root of the heritability; correlation between EBV and GEBV; regression coefficient of the GEBV on adjusted phenotype and GEBV on EBV. The EBV as pseudo-phenotype was more accurate than the adjusted phenotype. The GBLUP showed better predictive ability for meat color. For the other traits, the Bayesian methodologies had higher predictive ability. Among the Bayesian methodologies, BayesCπ was more accurate than Lasso for all traits. In Chapter ...O consumidor tem se tornado mais exigente com relação a qualidade da carne, fatores como maciez, cor e sabor são as características mais requeridas. Pouco tem sido feito em relação à qualidade da mesma, pois essas características não são consideradas nos programas de avaliação genética para gado de corte no Brasil, por serem de mensuração difícil, alto custo, e por exigir o abate dos animais. Uma alternativa para inclusão destas medidas em programas de melhoramento pode ser o uso dos SNPs em estudos de associação e seleção genômica. Foram utilizados 1.875 animais machos da raça Nelore foram terminados em confinamento e abatidos em planta frigorífica comercial, com idade média de 731±81 dias. As amostras coletadas foram analisadas para maciez, lipídeos, marmoreio, coloração L* (luminosidade), a* (vermelha) e b* (amarela). Os animais foram genotipados com um painel de 777.962 SNPs (Illumina BovineHD Beadchip) e após o controle de qualidade restaram 1.634 animais com genótipos e 369.722 SNPs. No capítulo 2, três métodos de seleção genômica foram avaliados: GBLUP (assume distribuição normal com variância única para todos os efeitos de SNPs), BayesCπ (apresenta uma distribuição mista para os efeitos dos SNPs) e Bayesian Lasso (assume distribuição dupla exponencial para os efeitos dos SNPs). O fenótipo corrigido para os efeitos fixos (Yc) e o valor genético predito (EBV) foram utilizados como pseudo-fenótipos. Para a validação cruzada, a população foi dividida aleatoriamente em cinco grupos de tamanhos similares. Para comparar a habilidade de predição dos métodos foram calculadas: a correlação entre os valores genômicos (GEBV) e os fenótipos corrigidos e o valor da correlação dividido pela raiz quadrada da herdabilidade; a correlação entre GEBV e EBV; o coeficiente de regressão do GEBV sobre o fenótipo corrigido e do GEBV sobre o EBV. O EBV como pseudo-fenótipo foi mais acurado..

Genome-Wide Association Study for Indicator Traits of Sexual Precocity in Nellore Cattle

<div><p>The objective of this study was to perform a genome-wide association study (GWAS) to detect chromosome regions associated with indicator traits of sexual precocity in Nellore cattle. Data from Nellore animals belonging to farms which participate in the DeltaGen^® and Paint^® animal breeding programs, were used. The traits used in this study were the occurrence of early pregnancy (EP) and scrotal circumference (SC). Data from 72,675 females and 83,911 males with phenotypes were used; of these, 1,770 females and 1,680 males were genotyped. The SNP effects were estimated with a single-step procedure (WssGBLUP) and the observed phenotypes were used as dependent variables. All animals with available genotypes and phenotypes, in addition to those with only phenotypic information, were used. A single-trait animal model was applied to predict breeding values and the solutions of SNP effects were obtained from these breeding values. The results of GWAS are reported as the proportion of variance explained by windows with 150 adjacent SNPs. The 10 windows that explained the highest proportion of variance were identified. The results of this study indicate the polygenic nature of EP and SC, demonstrating that the indicator traits of sexual precocity studied here are probably controlled by many genes, including some of moderate effect. The 10 windows with large effects obtained for EP are located on chromosomes 5, 6, 7, 14, 18, 21 and 27, and together explained 7.91% of the total genetic variance. For SC, these windows are located on chromosomes 4, 8, 11, 13, 14, 19, 22 and 23, explaining 6.78% of total variance. GWAS permitted to identify chromosome regions associated with EP and SC. The identification of these regions contributes to a better understanding and evaluation of these traits, and permits to indicate candidate genes for future investigation of causal mutations.</p></div

Manhattan plot for the occurrence of early pregnancy (EP) in Nellore cattle.

<p>The y-axis shows the proportion of variance explained by the windows of 150 SNPs and the x-axis indicates the chromosome number.</p

Manhattan plot for scrotal circumference (SC) in Nellore cattle.

<p>The y-axis shows the proportion of variance explained by the windows of 150 SNPs and the x-axis indicates the chromosome number.</p

Identification of genes within the 10 windows of 150 SNPs that explained the highest proportion of genetic variance for scrotal circumference in Nellore cattle.

<p>Identification of genes within the 10 windows of 150 SNPs that explained the highest proportion of genetic variance for scrotal circumference in Nellore cattle.</p

Pedigree structure with different proportions of multiple sires.

<p>Pedigree structure with different proportions of multiple sires.</p

Accuracies of evaluation for W550 for the ALL, BULL, GEN, FEM, and YOUNG groups using different scaling for the genomic matrix (G) to match the numerator relationship matrix for genotyped animals (A₂₂).

<p>W550—weight at 550 days; S1 –scaling for all genotyped animals; S2—no scaling; S3—scaling only for animals which have known sire and dam; S4—scaling only for animals which have one known parent.</p

Breeding value accuracy estimates and standard errors for AFC and W550 using BLUP and ssGBLUP models with different proportions of multiple sires.

<p>Breeding value accuracy estimates and standard errors for AFC and W550 using BLUP and ssGBLUP models with different proportions of multiple sires.</p

Bias and standard errors using BLUP and ssGBLUP with different proportions of multiple sires.

<p>Bias and standard errors using BLUP and ssGBLUP with different proportions of multiple sires.</p