Interplay between genetic and environmental factors, genotype x environment interactions (G x E), affect phenotypes of complex traits. A methodology for assessing G x E was investigated by detecting hygiene (low and high) environment-specific SNP subsets associated with broiler chicken mortality, followed by an examination of consistency between SNP subsets selected from the 2 environments. The trait was mean progeny mortality rate in 253 sire families, after adjusting records for nuisance effects affecting mortality at the individual bird level. Over 5,000 whole-genome SNP were narrowed down via a machine-learning (filter-wrapper) feature selection procedure applied to mortality rates in each of the 2 environments. For both early and late mortality, it was found that the selected SNP subsets differed across hygiene environments, in terms of either across-environment predictive ability or extent of linkage disequilibrium between the subsets. Reduction in predictive ability due to G x E was assessed by the ratio of 2 predicted residual sum of squares statistics, one associated with SNP selected from the same hygiene environment and the other associated with the SNP subset from a different environment. Reduction was 30 and 20% for early and late mortality, respectively. An extremely low level of linkage disequilibrium between SNP subsets selected under low and high hygiene also indicated G x E. Findings suggest that there may not be a universally optimal SNP subset for predicting mortality and that interactions between genome and environmental factors need to be considered in association analysis of complex traits.