Expanding the gain-variance Pareto via optimal recycling and genomic mating

Abstract

The optimization of mating plans, or optimal genomic mating (OGM), is a powerful breeding strategy that balances genetic gain with the preservation of diversity, securing long-term improvement. However, existing OGM implementations neglect the recycling stage, where naive truncation selection dissipates the diversity initially safeguarded. Here, we propose an integrated strategy that couples optimal recycling with genomic mating to better control genetic diversity while delivering competitive genetic gains. Using stochastic simulations of line and hybrid breeding schemes, we show that the integrated strategy retained 1.6-2.0 times more diversity than OGM alone and 3.5-5.0 times more than truncation mating based on family means and the usefulness criterion (UC). These were equivalent to maintaining around 1.7 and 2.4 times less realized inbreeding rates. Additionally, it improved the efficiency of translating variance into gain by 21.6-49.8% and 67.4-108.2% compared to the sole implementation of OGM and truncation mating strategies. We also demonstrate the utility of our newly developed intuitive and standardized metric, proportion of additive standard deviation lost (PropSD), for managing diversity in the crossing and recycling stages. Pareto optimal solutions were achieved at around 2-3% and 4-5% PropSD without and with optimal recycling. Finally, we derive a closed-form expression quantifying the expected advantage of UC over mean-based mating. Modeling within-family variance offered limited additional benefit, mainly due to high family mean-to-standard-deviation variance ratios. Overall, our proposed framework advances genomic selection programs to be sustainable by effectively preserving genetic diversity for future genetic improvement.