Gene regulation underlies environmental adaptation in house mice

Abstract

Changes in -regulatory regions are thought to play a major role in the genetic basis of adaptation. However, few studies have linked-regulatory variation with adaptation in natural populations. Here, using a combination of exome and RNA-seq data, we performed expression quantitative trait locus (eQTL) mapping and allele-specific expression analyses to study the genetic architecture of regulatory variation in wild house mice () using individuals from five populations collected along a latitudinal cline in eastern North America. Mice in this transect showed clinal patterns of variation in several traits, including body mass. Mice were larger in more northern latitudes, in accordance with Bergmann's rule. We identified 17 genes where -eQTLs were clinal outliers and for which expression level was correlated with latitude. Among these clinal outliers, we identified two genes ( and ) with-eQTLs that were associated with adaptive body mass variation and for which expression is correlated with body mass both within and between populations. Finally, we performed a weighted gene co-expression network analysis (WGCNA) to identify expression modules associated with measures of body size variation in these mice. These findings demonstrate the power of combining gene expression data with scans for selection to identify genes involved in adaptive phenotypic evolution, and also provide strong evidence for -regulatory elements as essential loci of environmental adaptation in natural populations.

Adaptive zinc tolerance is supported by extensive gene multiplication and differences in cis-regulation of a CDF transporter in an ectomycorrhizal fungus

“…Examples include adaptation of yeast towards toxins and of American house mouse towards latitude (Naranjo et al, 2015; Phifer-Rixey et al, 2018). A cumulative action of different genetic loci or eQTLs (expression quantitative loci) on the expression of a particular gene associates with the adaptive phenotype in these examples (Naranjo et al, 2015; Mack et al, 2018). In general, genetic variants affecting gene expression are a major source of phenotypic variation and allow modulation of existing cellular pathways.…”

Multi-omics data analysis implicating epigenetic inheritance in evolution and disease

“…The environmental factors used to trigger inheritance in these models included low-protein diet 17 (LPD), cold exposure 12 (CE), and a combination of high-fat diet and the diabetes phenotype inducing compound streptozotocin 18 (H+S), with the studies identified from literature-wide search using the criteria of demonstrated physiological and gene regulatory effects in the offspring. The evolutionarily related genes comprised of that showing single nucleotide polymorphism (SNP) association and allele specific expression (ASE), as also differentially expressed genes (DEG), in latitudinal adaptation 13,14 . I tested the null hypothesis that the magnitude of overlap between cold adaptation genes and LPD, CE or H+S is the same as that between the former and sperm genes in all three models combined.…”

Key genes and co-expression modules involved in asthma pathogenesis

“…The WGCNA method has been widely used in recent years (Abu-Jamous & Kelly, 2018;Liu et al, 2017;Mack et al, 2018;Radulescu et al, 2018). Instead of linking thousands of genes to the disease, this technology focuses on relationship between gene modules and disease traits.…”