Abstract

Incorporation of genetic marker information in beef cattle breeding programs

The availability of molecular marker information has turned out to be an opportunity to improve animal breeding programs, by the inclusion of those effects in the estimation of breeding values. Along this perspective, the aims of present research were to compare genetic evaluation models that assume or not marker effects in the estimation of breeding values, as well as to estimate the allelic substitution effects of SNP markers, by applying six different methods (Bayesian multiple regression, Bayesian ridge regression, Bayes A, Bayes B, Bayes Cπ, and Bayesian Lasso), and to evaluate the impact of these effects on the reliability of breeding values and the divergences in animal classification based on classical breeding values and marker-assisted breeding values. Data of 83,404 animals belonging to a Nellore beef cattle (Bos indicus) selection program, measured for post-weaning gain, scrotal circumference and muscle score, and corresponding to 116,562 animals in the relationship matrix, were used.

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