Models for Genome x Environment Interaction: Examples in Livestock

In livestock, genotype x environment interaction (G x E) has been widely investigated, with genotype defined at the level of subspecies, breeds, individual animals within a breed (for example performance of offspring of elite sires across environments), and genotypes at single-nucleotide polymorphisms (SNPs). Environments can be described by category (e.g., tropical vs. temperate, high vs. low farm input levels, countries) and by continuous variables such as temperature. To predict breeding values of genotypes in environments described by categories, multitrait models with each category a different trait are used. The models are now being used to predict genomic estimated breeding values (GEBV) for different environments such as the value of a bull's genetics for his daughter's milk production in different countries. The multitrait genomic model has also been used to enable reference populations to be merged across environments and across countries, leading to more accurate GEBV. When the environment can be described by a continuous variable, random regression models have been used to predict response of genotypes to the environment. For example, these models have been used to determine if there are SNP genotypes associated with less sensitivity of milk production to increasing temperature. In both livestock and plant breeding, methods that use genomic information can better cope with a reduced degree of replication of individuals across environments, as it is actually the alleles that must be replicated across environments. More accurate estimates of G x E with the genomic approach may therefore be achievable than was possible in the past.