Seleção genômica para características de carcaça em bovinos da raça Nelore

• Autor(a) principal: Fernandes Júnior, Gerardo Alves [UNESP]
• Data de Publicação: 2015
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://hdl.handle.net/11449/123656; http://www.athena.biblioteca.unesp.br/exlibris/bd/cathedra/08-06-2015/000834736.pdf
• topic: Bovino de corte; Nelore (Zebu); Bovino de corte - Carcaças; Genômica; Marcadores genéticos; Genetica animal; Genomics

Economic relevant traits as carcass, measured after slaughter, are not included in the animal breeding program of Nelore breed due to the difficult and high cost to measure. With the advent of genomic selection, it is possible to select animals without the need of recording phenotypic performance of its own or from close relatives, and there is also the possibility of investigating genes or chromosome regions affecting the expression of traits using genome-wide association study (GWAS). The aim of this study was to compare different models on the predictive ability of genomic breeding values (GEBVs), and to perform a GWAS for the following traits: hot carcass weight, rib eye area, and backfat thickness, in order to contribute to the incorporation of genomic information into the genetic evaluation of beef cattle in Brazil. Genotypic and phenotypic information of 1,756 Nelore bulls were used in the analysis. Genotypes were generated based on a panel with 777.962 SNPs. The GEBVs were predicted using three models: Bayesian Ridge Regression (BRR), BayesC (BC) e Bayesian Lasso (BL), and two types of response variables: estimated breeding value and adjusted phenotypes for the fixed effects. GWAS was performed using the singlestep approach which combines all available phenotypic, pedigree and genomic information adjusting a polygenic-genomic model. In general, it was verified that heritability and response variable affected the genomic predictions, where the adjusted phenotype was the most appropriate response variable to perform SNPs estimates. It was also observed that the predictive abilities were similar among the methods (BRR, BC and BL). GWAS study detected potential genome regions that may be affecting the phenotypes. These regions can contribute to understand the genetic control of these traits and can be useful to include them into the genetic process for selecting the animals. The results showed that marker assited selection is ...