Abstract Background Optimal Contribution Selection (OCS) aims at maximizing long term response to selection by balancing short term genetic gain and inbreeding rate. In this study, OCS, trait management, and group mating methods were applied to poultry data to evaluate their potential impact. Real data from a White Leghorn line with 7 generations of pedigree and estimated breeding values (EBV) for 18 traits were used to evaluate responses from a single round of selection. It was shown that the current inbreeding rate is low and cannot be substantially reduced without significant loss of genetic gain, unless implemented in parallel with genomics to enable flexibility in population structure. Results Allowing flexible mating ratios under OCS resulted in 5.3 to 23.8% more genetic gain plus lower loss of genetic diversity compared to fixed-ratio ocs. However, in the case of multiple males per female, implementation is logistically challenging and requires genotyping of all hatched chicks. Using predicted progeny trait distribution management, a 3.2 g difference in mean EBV for egg weight was obtained for two market-targeted groups, without impact on the predicted progeny mean for the multi-trait index used for selection, or on average parental coancestry, but with a small increase in progeny inbreeding. While maintaining these two egg weight groups, tactical desired gains using trait EBV was used to favourably reduce predicted progeny genetic merit for feed intake from + 0.850 to -0.005 g/day, with little impact on genetic gain for other traits, mean index values, mean parental coancestry, or mean progeny inbreeding. Using pooled semen or multi-sire mating, while accounting for variation in male reproductive success, resulted in only a 0.5% reduction in response in predicted mean progeny index and in small increases in mean parental coancestry (from 0.014 to 0.015) and mean progeny inbreeding (from 0.005 to 0.007). Conclusions Evaluating the longer-term impacts of OCS and other methods employed requires multi-generation simulations, ideally starting from the current real data as a base. However, the current approach of using a real implementation scenario is important in decision making for real-life applications. Similar benefits from the selection and mating strategies used here are expected in breeding programs for other species.
Wolc et al. (2026) studied this question.