One approach to understanding the genetic basis of speciation is to scan the genomes of recently diverged taxa to identify highly differentiated regions. The house mouse, Mus musculus, provides a useful system for the study of speciation. Three subspecies (M. m. castaneus, M. m. domesticus, and M. m. musculus) diverged ∼350 KYA, are distributed parapatrically, show varying degrees of reproductive isolation in laboratory crosses, and hybridize in nature. We sequenced the testes transcriptomes of multiple wild-derived inbred lines from each subspecies to identify highly differentiated regions of the genome, to identify genes showing high expression divergence, and to compare patterns of differentiation among subspecies that have different demographic histories and exhibit different levels of reproductive isolation. Using a sliding-window approach, we found many genomic regions with high levels of sequence differentiation in each of the pairwise comparisons among subspecies. In all comparisons, the X chromosome was more highly differentiated than the autosomes. Sequence differentiation and expression divergence were greater in the M. m. domesticus-M. m. musculus comparison than in either pairwise comparison with M. m. castaneus, which is consistent with laboratory crosses that show the greatest reproductive isolation between M. m. domesticus and M. m. musculus. Coalescent simulations suggest that differences in estimates of effective population size can account for many of the observed patterns. However, there was an excess of highly differentiated regions relative to simulated distributions under a wide range of demographic scenarios. Overlap of some highly differentiated regions with previous results from QTL mapping and hybrid zone studies points to promising candidate regions for reproductive isolation.

Changes in cis-regulatory regions are thought to play a major role in the genetic basis of adaptation. However, few studies have linked cis-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 (Mus musculus domesticus) 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 cis-eQTLs were clinal outliers and for which expression level was correlated with latitude. Among these clinal outliers, we identified two genes (Adam17 and Bcat2) with cis-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 cis-regulatory elements as essential loci of environmental adaptation in natural populations.

Interactions between genes can influence how selection acts on sequence variation. In gene regulatory networks, genes that affect the expression of many other genes may be under stronger evolutionary constraint than genes whose expression affects fewer partners. While this has been studied for individual tissue types, we know less about the effects of regulatory networks on gene evolution across different tissue types. We use RNA-sequencing and genomic data collected from Mus musculus domesticus to construct and compare gene co-expression networks for 10 tissue types. We identify tissue-specific expression and local regulatory variation, and we associate these components of gene expression variation with sequence polymorphism and divergence. We found that genes with higher connectivity across tissues and genes associated with a greater number of cross-tissue modules showed significantly lower genetic diversity and lower rates of protein evolution. Consistent with this pattern, "hub" genes across multiple tissues also showed evidence of greater evolutionary constraint. Using allele-specific expression, we found that genes with cis-regulatory variation had lower average connectivity and higher levels of tissue specificity. Taken together, these results are consistent with strong purifying selection acting on genes with high connectivity within and across tissues.

House mice (Mus musculus) arrived in the Americas only recently in association with European colonization (~400-600 generations), but have spread rapidly and show evidence of local adaptation. Here, we take advantage of this genetic model system to investigate the genomic basis of environmental adaptation in house mice. First, we documented clinal patterns of phenotypic variation in 50 wild-caught mice from a latitudinal transect in Eastern North America. Next, we found that progeny of mice from different latitudes, raised in a common laboratory environment, displayed differences in a number of complex traits related to fitness. Consistent with Bergmann's rule, mice from higher latitudes were larger and fatter than mice from lower latitudes. They also built bigger nests and differed in aspects of blood chemistry related to metabolism. Then, combining exomic, genomic, and transcriptomic data, we identified specific candidate genes underlying adaptive variation. In particular, we defined a short list of genes with cis-eQTL that were identified as candidates in exomic and genomic analyses, all of which have known ties to phenotypes that vary among the studied populations. Thus, wild mice and the newly developed strains represent a valuable resource for future study of the links between genetic variation, phenotypic variation, and climate.

Increasing evidence suggests that urbanization is associated with higher mutation rates, which can affect the health and evolution of organisms that inhabit cities. Elevated pollution levels in urban areas can induce DNA damage, leading to de novo mutations. Studies on mutations induced by urban pollution are most prevalent in humans and microorganisms, whereas studies of non-human eukaryotes are rare, even though increased mutation rates have the potential to affect organisms and their populations in contemporary time. Our Perspective explores how higher mutation rates in urban environments could impact the fitness, ecology and evolution of populations. Most mutations will be neutral or deleterious, and higher mutation rates associated with elevated pollution in urban populations can increase the risk of cancer in humans and potentially other species. We highlight the potential for urban-driven increased deleterious mutational loads in some organisms, which could lead to a decline in population growth of a wide diversity of organisms. Although beneficial mutations are expected to be rare, we argue that higher mutation rates in urban areas could influence adaptive evolution, especially in organisms with short generation times. Finally, we explore avenues for future research to better understand the effects of urban-induced mutations on the fitness, ecology and evolution of city-dwelling organisms.