Practical Considerations When Using Mendelian Sampling Variances for Selection Decisions in Genomic Selection...

The purpose of this work was to test the application of selection criteria that consider the genetic variances of future generations. This has not been done previously in numerically large livestock breeding programs based on estimated rather than assumed known marker effects. A generic pure-line pig breeding program was simulated in which 40 males and 400 females were selected every generation. Daily gain was used as an example trait. Three variance-considering criteria as well as different reference population sizes were compared to investigate the effect of differences in genomic prediction accuracy on selection decisions. All variance-considering criteria retained more genetic variance than if selection was based on estimated breeding values (max. 20%). This effect was more pronounced for higher prediction accuracies and criteria assessing the variance more generations ahead. After 20 generations, the criterion with the longest planning horizon combined with the largest reference population resulted in a 2% higher genetic level of boars selected to produce finisher pigs. While the advantage of accounting for future generations diminished with lower accuracy or shorter planning horizons, the variance-considering criteria never performed worse than selection based on genomic estimated breeding values (GEBV) with respect to commercial genetic gain. We are reporting various accuracy metrics to help judge the effectiveness of using one of our tested criteria in real breeding programs. While we did not find large benefits for genetic gain when considering future variances in selection decisions, we also did not find negative side effects, while considerably more genetic variance was maintained. This means that using variance-considering criteria results in either equally good or better performance than truncation selection based on estimated breeding values. Our criteria can be applied to any genomic breeding program as long as phased genotypes, estimated marker effects and a genetic map are available.