| The effects of genetic variants on phenotypic traits often depend on environmental and physiological conditions, but such gene-environment interactions are poorly understood. Recently developed approaches that treat transcript abundances of thousands of genes as quantitative traits offer the opportunity to broadly characterize the architecture of gene-environment interactions. We examined the genetic and molecular basis of variation in gene expression between two yeast strains (BY and RM) grown in two different conditions (glucose and ethanol carbon sources). We observed that most transcripts vary by strain and condition, with 2996, 3448, and 2037 transcripts showing significant strain, condition, and strain-condition interaction effects, respectively. We expression-profiled over 100 segregants derived from a cross between RM and BY in both growth conditions and identified 1555 linkages for 1382 transcripts that show significant gene-environment interaction. At the locus level, local linkages, which usually correspond to polymorphisms in cis-regulatory elements, tend to be more stable across conditions, such that they are more likely to show the same effect or the same direction of effect across conditions. Distant linkages, which usually correspond to polymorphisms influencing transacting factors, are more condition-dependent, and often show effects in different directions in the two conditions. We characterize five loci that influence expression in a condition-dependent manner: AMN1, MKT1, IRA2, GPA1, and DIG1. Interestingly, the RM allele of IRA2 appears to be more functional than the BY allele across these conditions, and patterns in polymorphism variation suggest that the RM allele has experienced positive selection. Finally, we use clustering methods and coregulation by transcription factors to characterize how groups of transcripts change across conditions, highlighting how the effects of variants in GPA1 and DIG1 become differentially relevant in the two conditions. Our results provide a broad overview of the genetic architecture of gene-environment interactions, as well as detailed molecular examples, and lead to key insights into how the effects of different classes of regulatory variants are modulated by the environment. These observations will guide the design of studies aimed at understanding the genetic basis of complex traits. |
