Potential of autosomal crossover count to enhance additive genetic variance in pig breeding programs
Year: 2026
Type: article
Abstract: Background Crossovers can break the linkage between loci, thereby creating novel allele combinations and releasing genetic variation. However, empirical studies evaluating their potential use in livestock breeding programs remain scarce. In this study, we investigated the link between autosomal crossover count (ACC) and additive genetic variance for reproduction and production traits in pigs. Using univariate and bivariate sire models, individuals were grouped into five bins according to the number of paternal autosomal crossovers they inherited, as estimated in a previous study. Within each bin, sire additive genetic variance was estimated. The analysis included more than 50,000 records for total number born, number born alive, and number of stillborn piglets; over 14,000 records for number of teats; and more than 35,000 records for standardized average daily gain. Results For all traits, the 95% confidence interval of the overall estimated sire additive genetic variance overlapped with the estimates obtained for each ACC bin. Likewise, the 95% confidence interval for differences in $$\:{\widehat{\sigma\:}}_{a,sire}^{2}$$ between consecutive bins also overlapped in almost all cases. These results indicate that the observed number of crossovers did not significantly affect the $$\:{\widehat{\sigma\:}}_{a,sire}^{2}$$ . Nevertheless, trait-specific patterns were apparent. For three traits, the $$\:{\widehat{\sigma\:}}_{a,sire}^{2}$$ was highest at intermediate ACC ranges, whereas for the remaining traits it reached its maximum at either low or high ACC ranges. Despite the lack of statistically significant differences, the bins with the lowest and highest $$\:{\widehat{\sigma\:}}_{a,sire}^{2}$$ differed by an average of 57% across traits. Conclusions In conclusion, ACC may be of potential interest in breeding programs as a trait worth further investigation, although the present results do not provide significant evidence to support its direct use for the analyzed ACC ranges.
Source: Genetics Selection Evolution
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,390
OpenAlex ID: W7225737205