Environmentally robust cis- regulatory changes underlie rapid climatic adaptation

Data, code, and analyses associated with the manuscript, "Environmentally robust cis- regulatory changes underlie rapid climatic adaptation".

Abstract: Changes in gene expression are thought to play a major role in adaptive evolution. While it is known that gene expression is highly sensitive to the environment, very few studies have determined the influence of genetic and environmental effects on adaptive gene expression differences in natural populations. Here, we utilize allele- specific expression to characterize cis and trans gene regulatory divergence in temperate and tropical house mice in two metabolic tissues under two thermal conditions. First, we show that gene expression divergence is pervasive between populations and across thermal conditions, with  roughly  5  to  10%  of  genes  exhibiting  genotype- by- environment  interactions.  Second, we found that most expression divergence was due to cis- regulatory changes that were stable across temperatures. In contrast, patterns of expression plasticity were largely  attributable  to  trans- effects,  which  showed  greater  sensitivity  to  temperature.  Nonetheless, we found a small subset of temperature- dependent cis- regulatory changes, thereby identifying loci underlying expression plasticity. Finally, we performed scans for selection in wild house mice to identify genomic signatures of rapid adaptation. Genomic outliers  were  enriched  in  genes  with  evidence  for  cis- regulatory  divergence.  Notably,  these genes were associated with phenotypes that affected body weight and metabolism, suggesting that cis- regulatory changes are a possible mechanism for adaptive body size evolution between populations. Our results show that gene expression plasticity, largely controlled in trans, may facilitate the colonization of new environments, but that evolved changes in gene expression are largely controlled in cis, illustrating the genetic and non-genetic mechanisms underlying the establishment of populations in new environments.

Code associated with the analysis of these data can be found on GitHub at https://github.com/malballinger/BallingerMack_NYBZase_2023