Genomic prediction for small breeds


Genomic prediction for small breeds

Gepubliceerd op
12 juni 2018

Application of genomic selection has increased genetic progress per year by up to 50% for the major livestock breeds. For smaller breeds to stay competitive with the major breeds, it is important to achieve sufficient genetic improvement, for instance through the implementation of genomic selection with sufficient accuracy. Small breeds, however, may have too small active breeding populations to enable implementation of accurate genomic selection within the breed itself. This study, undertaken within Breed4Food in collaboration with researchers in Melbourne, Australia, showed that the accuracy of genomic selection for small breeds can be marginally improved by using information of another large breed.

Multibreed genomic prediction

So far, limited improvement in accuracy of genomic selection has been observed from combining information on multiple breeds in genomic evaluations. In this study we aimed to increase the accuracy of genomic selection in a small breed (in this case Jersey) by using information of a large breed (in this case Holstein Friesian). The highest accuracy was obtained by a model that simply analysed the pooled information of Holsteins and Jerseys without considering the differences between breeds. A sophisticated Bayesian model that was able to model more subtle differences between breeds, actually resulted in slightly lower accuracies. Considering that genes with large effect are the main drivers of genomic prediction across breeds, we hypothesized that the pooling strategy’s assumption that gene effects are the same across breeds is especially appropriate for genes of large effect, while it is not detrimental for the estimation of genes of small effect.