Integrating three genetic dimensions relating to piglet birth weight: direct and maternal effects on the mean and genetic control of residual variance

Abstract

The uniformity of production traits is desired for different traits in livestock species, including the uniformity of within-litter birth weight (BW) in piglets. In pigs, BW is associated with increased vitality and survival until weaning. However, as the uniformity of the BW increases, the importance of the initial weight decreases as competition between piglets decreases. The aim of this study was to estimate the direct and maternal genetic components of BW, jointly with the maternal genetic component of the residual variance for within-litter BW, and their genetic correlations. We used two distinct datasets of Swiss Large White pigs: (1) an experimental farm dataset, and (2) a commercial farm dataset, comprising 43 135 and 23 313 records of individual piglet BW, respectively. A heteroscedastic model was used for the statistical analysis. This model assumes that both the mean BW and the residual variance are affected by systematic and random effects, with the residual variance being heterogeneous and partially under genetic control. In the most complex models, which included both genetic effects for the mean trait, the results indicated that direct genetic effects or correlations with such effects were negligible. The genetic component of the residual variance for BW ranged from 0.0712 to 0.1246 for the experimental farm and from 0.0371 to 0.0994 for the commercial farms. The genetic correlation between the mean BW and BW variability was always positive, ranging from 0.1492 to 0.3069 for the experimental farm and from 0.2197 to 0.5892 for the commercial farms. Thus, it is sufficient to model mean BW and BW variability by including only the maternal genetic effect for both traits. In addition, although moderate genetic correlations existed between the within-litter mean BW and BW variability, focusing on BW uniformity within litters would be preferable in simultaneously creating a selection index for both traits.