Litter size at lambing influences genetic evaluation of maternal rearing ability

• Published in: Animal production science Vol. 58; no. 5; p. 791
• Main Authors: Bunter, Kim L., Swan, Andrew A., Brown, Daniel J., Brien, Forbes D., Smith, Jennifer
• Format: Journal Article
• Language: English
• Published: 2018
• ISSN: 1836-0939
• DOI: 10.1071/AN16422

The genetic parameters for maternal rearing-ability of ewes were investigated by ignoring or defining the rearing ability trait separately by litter-size class (singles versus multiples) using multi-generational data from three, fully pedigreed Merino flocks differing in prolificacy, production level and environment. Genetic correlations (ra) between litter size (LSIZE) and the percentage of lambs surviving (PLSURV) were more negative with an increasing mean flock litter size (ra: –0.21 ± 0.17 to –0.73 ± 0.08), while the corresponding range in phenotypic correlations (rp) was substantially lower (rp: –0.15 ± 0.01 to –0.33 ± 0.01). Rearing-ability traits defined separately by litter-size class were highly correlated (ra: 0.49 ± 0.19 to 0.64 ± 0.38), but not genetically identical traits in the most prolific flock. Defining rearing-ability traits separately by litter-size class reduced the antagonistic genetic correlations between LSIZE and PLSURV to between –0.39 ± 0.14 and 0.14 ± 0.28, through accommodating the change in mean and variance of PLSURV with LSIZE. Similarly, linear transformation (TSURV) of PLSURV within each litter size to a common mean and variance reduced the antagonistic trend in genetic correlations between LSIZE and TSURV to range between –0.05 ± 0.17 and –0.43 ± 0.13. Since genetic correlations are low to moderate between TSURV and LSIZE, it is possible to select for improvements in both the number of lambs born and lamb survival simultaneously. Defining rearing-ability traits separately by litter-size class and the role of transformation will be investigated further for improving the accuracy of genetic evaluation for rearing ability across a range of flocks, breeds and environmental conditions using more extensive industry data.