Genotype-environment interactions (GxE) should be expected to occur whenever more than one genotype and more than one environment are considered, although their magnitude may differ. It is important to make use of this natural phenomenon rather than ignoring it or considering it as a problem. There are several examples and estimates of GxE in pig breeding suggesting significant GxE with respect to heat stress, diseases, seasonal variations and variation in performance during different periods within farms. Reaction models are quite useful in estimating these GxE effects as genetic correlations between different levels of environmental stress. Several studies using these models have revealed lower genetic correlations between the intermediate environment and environments with higher or lower stress levels. These results suggest that indirect selection based on performance in an optimal environment, ignoring the GxE effects, would result in less than optimal performance in a stressful environment. At the same time, there are opportunities for enhancing performance under stressful environments. Most studies have revealed the availability of larger genetic variance in stressful environments, providing opportunities for selection within the environment and making faster genetic progress. Further, the reaction norm models also allow estimating breeding values of animals in non-stressful environments based on data from stressful environments for the selection of robust animals and sorting of terminal boars. Genomic information can improve the accuracy of these breeding values and enhance genetic gains. SNP-environment interactions and gene-environment interactions provide further opportunities for effective utilization of this phenomenon for future pig breeding. Keywords: genotype-environment interactions, reaction norm models, heat stress, seasonality, diseases, challenge load

Pramod Karan Mathur

Proceedings of the World Congress on Genetics Applied to Livestock Production, Volume Challenges - Genotype by Environment Interactions, , 668, 2018
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