Improving Short- and Long-Term Genetic Gain by Accounting for Within-Family Variance in Optimal Cross-Selection

The implementation of genomic selection in recurrent breeding programs raises the concern that a higher inbreeding rate could compromise the long term genetic gain. An optimized mating strategy that maximizes the performance in progeny and maintains diversity for long term genetic gain is therefore essential. The optimal cross selection approach aims at identifying the optimal set of crosses that maximizes the expected genetic value in the progeny under a constraint on genetic diversity in the progeny. Optimal cross selection usually does not account for within family selection, i.e. the fact that only a selected fraction of each family is used as parents of the next generation. In this study, we consider within family variance accounting for linkage disequilibrium between quantitative trait loci to predict the expected mean performance and the expected genetic diversity in the selected progeny of a set of crosses. These predictions rely on the usefulness criterion parental contribution (UCPC) method. We compared UCPC based optimal cross selection and the optimal cross selection approach in a long term simulated recurrent genomic selection breeding program considering overlapping generations. UCPC based optimal cross selection proved to be more efficient to convert the genetic diversity into short and long term genetic gains than optimal cross selection. We also showed that using the UCPC based optimal cross selection, the long term genetic gain can be increased with only a limited reduction of the short term commercial genetic gain.