Buffalo milk is characterized by high quantity in terms of fat, protein and total solids compared to milk of other animal species, which allows higher throughput of its derivatives, mainly in the manufacture of mozzarella cheese. Identify the genes responsible for phenotypic variation in traits of economic importance allows the development of methods of selecting superior genotypes. Therefore, genomic selection confers benefits to animal breeding due to direct use of DNA information in the selection process, increasing the genetic gain compared to traditional selection based only on phenotype. The use of SNP markers (Single Nucleotide Polymorphism) are recent, however it becomes attractive for traits measured on one sex and high cost of measurement, such as the production of milk and its constituents. However, there are still doubts among researchers on how to insert genomic information in genetic evaluation and which method is most appropriate. The objective of this study is to evaluate two methods of genomic predictions for the production and quality of milk of buffaloes: multi-step and single-step. Genomic evaluation through multi-step methodology includes three steps: 1) regular evaluation by the animal model, 2) estimation of genomic effects for a relatively small number of genotyped animals, and 3) estimation of genomic breeding values by a selection index. In the single-step model is performed the inclusion of genomic matrix of genotyped animals corrected by the genomic relationship of animals not genotyped matrix. High density specific chips to buffaloes will be used, developed by the company Affymetrix, which has approximately 90,000 SNPs (Axiom® Buffalo Genotyping Array). With the results may be possible to determine the most appropriate method for obtaining genomic values for production traits and quality of buffalo milk.
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