Gene by environment interaction for reproduction traits in Australian sheep

Summary

Reproduction is one of the most important profit drivers in the Merino industry, but genetic progress is generally difficult to achieve due to low heritabilities of the breeding objective traits associated with reproductive performance. It is unclear if the low heritability is due to a lack of precision in the definition of the environment, or the actual phenotype or because other sources of variance such as non-additive genetic effects or variation due to genotype x environment (GxE) interactions are important. 
If GxE interaction is a major source of phenotypic variation for reproduction traits, a selection strategy for robust genotypes could lead to more consistent performance in reproduction performance and lamb survival. This approach could lead overall to more robust and consistent production performance, buffering periods of sub-optimal environmental conditions. This study investigated two aspects. Firstly, the existence GxE interactions in Merino sheep in the Information Nucleus Flock were explored. Different analysis approaches were taken to define the environmental descriptor to explore if different definitions facilitate separation of genetic and environmental variances and their interactions. 
Confirming the results from previous analyses, some evidence of the existence of small GxE interactions for reproduction traits was found, but they only accounted for small proportions of phenotypic variance. All analyses yielded low heritabilities. The second aspect of this study explored a random regression approach to determine the robustness of sire performance across environments and subsequently determine underlying genomic regions and / or genes for this characteristic in a genome wide association study (GWAS). This approach has been suggested by Lillehammer et al. (2009) who detected underlying genes for robustness for milk production traits. 
This study demonstrated that the variability of sires reproductive performance across environments was low and therefore it was unlikely that a GWAS would detect significant SNPs of large effect on reproductive performance and conclusive evidence for underlying genes. Rather, the results indicated that robustness in reproduction across environments in Merino sheep of the INF is influenced by a large number of genes of small effect. Genomic information certainly offer a wider range of approaches to explore GxE interactions compared classical quantitative Genetics and genomics methods and have the potential to provide tangible solutions to industry, such as marker tests or genomic breeding values for robustness of production traits. 
No conclusive evidence of marker associations with robustness for reproduction traits were detected in this study. However, for production traits where GxE interactions have been shown to be important, the random regression approach coupled with a GWAS could potentially be a useful methodology to determine genes underlying robustness. Also, novel measurements techniques for reproduction traits might disentangle the complex phenotype and describe the underlying genetic processes more precisely than can currently be done with the traditional phenotypes.