Strategies for applying genomic selection in beef cattle breeding programs

Abstract

The use of low density SNP panels for selection candidates, as well as the proportion of each category that should be genotyped, may reduce the genotyping costs and thus increase the efficiency of animal breeding programs by using genomic selection. In beef cattle, there are few studies which identified the proper densities of marker panels for each category of animals and which proportion they should be genotyped, with the purpose of not compromising the accuracy of genomic prediction and the genetic gain. Therefore, the aim of the present study is to identify strategies for applying genomic selection in beef cattle which maximize the genetic gain for economically important traits and optimize the cost-effectiveness of its application. The best strategy will be based on genetic gain per year, expressed in genetic standard deviation, on the cost of each panel and on the number of animals genotyped. Firstly, the scenarios will be a deterministic study, which will be compared by the genetic gain. Then different densities of panels, associated to distinct proportions of animals genotyped in each category, will be tested by using stochastic simulation. The simulated genome will be composed by 29 pairs of autosomes, totaling 2333 cM. Different panels of SNP markers will be simulated, which are similar to those employed in real populations, of low (6k and 50k), and high density (777k). The low densities panels will be imputed to high density. The genomic analysis will be conducted using a Single Step Genomic BLUP methodology. The information generated by this study may be useful in order to apply different strategies of genomic selection in beef cattle, aiming to improve the cost-effectiveness of its application. (AU)