Metodologia de atribuição dos escores visuais e estudo de associação genômica para os escores de conformação, precocidade e musculosidade em bovinos Nelore

• Ano de defesa: 2015
• Autor(a) principal: Duitama Carreño, Luis Orlando [UNESP]
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Estadual Paulista (Unesp)
• Palavras-chave em Português: Bovino - Melhoramento genetico; Bovino de corte; Nelore (Zebu); Genes; Genômica; Genetica animal; Genomics
• Link de acesso: http://hdl.handle.net/11449/126520; http://www.athena.biblioteca.unesp.br/exlibris/bd/cathedra/11-08-2015/000843038.pdf

The visual scores are used as selection criteria in Brazilian cattle and aiming to improve the carcass traits. These traits have the particularity of being attributed depending on relative data and not on absolute references. This property could lead to difficulties in the estimation of genetic parameters and breeding values as well. Considering the importance of the visual scores, two studies were performed with the following objectives: 1) determine if the forms in which these scores are attributed have consequences in the genetic parameters and breeding values estimation, and, 2) identify regions of the genome that are associated with the scores of conformation, finishing precocity and muscling in Nellore cattle. For the first objective, a simulation study was conducted considering populations with and without selection, and three sizes of group attribution scores (10, 40 and 100 animals), these populations were mated for 12 overlapping generations. Genetic parameters and breeding values for each generation were estimated using a threshold model. The results indicate that the estimates of genetic parameters and breeding values are not affected by how the scores are attributed; however, the estimated breeding values are affected by the group size, being recommended the formation of evaluation groups more than 40 animals. For the second objective, a GWAS was conducted using BayesC and Bayesian LASSO models with two types of dependent variable. These variables were the phenotype and the deregressed breeding values (dEBV). In the analyses, a total of 2873 records of males and females from Nellore cattle were used. The animals were genotyped using the chip BovineHD of Illumina, after the quality control, a total of 309,865 SNPs were maintained. The association criterion was the proportion of genetic variance explained by 1 Mb genome windows. After the analyses, the BayesC model was the best fitted the data, as it explained a greater ...