Incorporation of genomic information to study of milk fatty acid profile in dairy cattle raised in Brazil

Abstract

Animal breeding is an important tool for an increase in productivity and in quality of products of animal origin, mainly through the identification of animals with superior breeding values and adapted to environmental conditions. Specifically in dairy cattle, due to the small magnitude of genetic gain in traits of interest resultant from the contribution of imported genetic material, it is necessary the genetic evaluation of herds under Brazilian conditions of environment. Moreover, traits such as somatic cell count, protein, fat and fatty acids content can be used as selection criteria in breeding programs for the improvement of milk quality. Thus, in order to maximize the genetic gain in yield and quality traits using molecular markers information and genetic evaluation, the aim of this study is genotype imputation, association and estimation of SNP markers effects on production and quality traits of milk, such as somatic cells count and fatty acids profile. For this, bulls (n=50, with DNA extracted from semen samples) and cows (n=400, with DNA extracted in the previous project) will be genotyped, respectively, with high (800k) and low (6k) density panels of SNPs, for a subsequently genomic imputation to high density panels using the subgroups of cows cited formerly. It is important to highlight that the current proposal is also financially supported by FAPESP (2010/12929-6) and CNPq (482327/2010-3 and 484560/2012-3), which provided funds for 2000 cows phenotyping, partial genotyping and association analyses for five SNPs, involving cows sampled monthly for fat content, protein content, fatty acids profile, production, somatic cell count and other milk components determination. After bulls and cows genotyping, missing genotypes of cows will be imputed employing the reference panel of bulls. This amplified SNPs marker panel will be used in the association analyses between SNPs and interest traits, which will be based in single step technique, SNP by SNP, using BLUPF90 family of programs under animal model. (AU)