Interpretive Summary: The impact of direct-maternal genetic correlations on international beef cattle evaluations for Limousin weaning weight
By: Anne Kamiya, MS
Maternally influenced traits include genetic factors that impact birth and weaning. Cultivating a better understanding of the heritability of maternally influenced traits may improve estimated breeding values (EBV), genetic selection and ultimately productivity. The dilemma faced is that multiple generations of pedigree data are required for accurate estimates of direct-maternal genetic correlations (rdm), which is not always possible. Oftentimes, rdm ends up being negative, possibly due to lack of sufficient modeling data. In international beef cattle evaluations, between-country, and within-country direct-maternal genetic correlations (rdm_BC and rdm_WC) are often ignored.
In this article recently published in the Journal of Animal Science, researchers evaluated the how models using international EBVs or ignoring it (setting a zero value for rdm) in the Limousin breed of cattle impacted selectivity. Data for weaning weight was collected from the Czech Republic, Denmark, Finland, France, Germany, Great Britain, Ireland, Spain, Sweden, and Switzerland. Models that used EBV for rdm_BC and rdm_WC and models that ignored it (by setting it to zero) were compared. The authors reported that setting rdm_BC and rdm_WC to zero causes small decreases in population accuracy and dispersion of EBVs. They also reported a significant reranking of direct and maternal IEBVs when rdm_WC is set to zero.
Overall, the results of this study suggest that the current practice of ignoring rdm may need to be reevaluated. More studies on traits aside weaning weight would need to be studied to better understand how setting rdm to zero versus using actual EBV values impacts accuracy and selection.
The original article, The impact of direct-maternal genetic correlations on international beef cattle evaluations for Limousin weaning weight, will soon be viewable in the Journal of Animal Science.