Evaluating the role of natural selection in the evolution of gene regulation

Surveys of gene expression reveal extensive variability both within and between a wide range of species. Compelling cases have been made for adaptive changes in gene regulation, but the proportion of expression divergence attributable to natural selection remains unclear. Distinguishing adaptive changes driven by positive selection from neutral divergence resulting from mutation and genetic drift is critical for understanding the evolution of gene expression. Here, we review the various methods that have been used to test for signs of selection in genomic expression data. We also discuss properties of regulatory systems relevant to neutral models of gene expression. Despite some potential caveats, published studies provide considerable evidence for adaptive changes in gene expression. Future challenges for studies of regulatory evolution will be to quantify the frequency of adaptive changes, identify the genetic basis of expression divergence and associate changes in gene expression with specific organismal phenotypes.     

Genes that determine flower color: the role of regulatory changes in the evolution of phenotypic adaptations

A central goal of evolutionary genetics is to trace the causal pathway between mutations at particular genes and adaptation at the phenotypic level. The proximate objective is to identify adaptations through the analysis of molecular sequence data from specific candidate genes or their regulatory elements. In this paper, we consider the molecular evolution of floral color in the morning glory genus (Ipomoea) as a model for relating molecular and phenotypic evolution. To begin, flower color variation usually conforms to simple Mendelian transmission, thus facilitating genetic and molecular analyses. Population genetic studies of flower color polymorphisms in the common morning glory (Ipomoea purpurea) have shown that some morphs are subject to complex patterns of selection. Striking differences in floral color and morphology are also associated with speciation in the genus Ipomoea. The molecular bases for these adaptive shifts can be dissected because the biosynthetic pathways that determine floral pigmentation are well understood and many of the genes of flavonoid biosynthesis have been isolated and extensively studied. We present a comparative analysis of the level of gene expression in Ipomoea for several key genes in flavonoid biosynthesis. Specifically we ask: how frequently are adaptive shifts in flower color phenotypes associated with changes in regulation of gene expression versus mutations in structural genes? The results of this study show that most species differences in this crucial phenotype are associated with changes in the regulation of gene expression.     

Natural selection on gene expression

Changes in genetic regulation contribute to adaptations in natural populations and influence susceptibility to human diseases. Despite their potential phenotypic importance, the selective pressures acting on regulatory processes in general and gene expression levels in particular are largely unknown. Studies in model organisms suggest that the expression levels of most genes evolve under stabilizing selection, although a few are consistent with adaptive evolution. However, it has been proposed that gene expression levels in primates evolve largely in the absence of selective constraints. In this article, we discuss the microarray-based observations that led to these disparate interpretations. We conclude that in both primates and model organisms, stabilizing selection is likely to be the dominant mode of gene expression evolution. An important implication is that mutations affecting gene expression will often be deleterious and might underlie many human diseases.     

Differential expression of genes important for adaptation in Capsella bursa-pastoris (Brassicaceae)

Understanding the genetic basis of natural variation is of primary interest for evolutionary studies of adaptation. In Capsella bursa-pastoris, a close relative of Arabidopsis (Arabidopsis thaliana), variation in flowering time is correlated with latitude, suggestive of an adaptation to photoperiod. To identify pathways regulating natural flowering time variation in C. bursa-pastoris, we have studied gene expression differences between two pairs of early- and late-flowering C. bursa-pastoris accessions and compared their response to vernalization. Using Arabidopsis microarrays, we found a large number of significant differences in gene expression between flowering ecotypes. The key flowering time gene FLOWERING LOCUS C (FLC) was not differentially expressed prior to vernalization. This result is in contrast to those in Arabidopsis, where most natural flowering time variation acts through FLC. However, the gibberellin and photoperiodic flowering pathways were significantly enriched for gene expression differences between early- and late-flowering C. bursa-pastoris. Gibberellin biosynthesis genes were down-regulated in late-flowering accessions, whereas circadian core genes in the photoperiodic pathway were differentially expressed between early- and late-flowering accessions. Detailed time-series experiments clearly demonstrated that the diurnal rhythm of CIRCADIAN CLOCK-ASSOCIATED1 (CCA1) and TIMING OF CAB EXPRESSION1 (TOC1) expression differed between flowering ecotypes, both under constant light and long-day conditions. Differential expression of flowering time genes was biologically validated in an independent pair of flowering ecotypes, suggesting a shared genetic basis or parallel evolution of similar regulatory differences. We conclude that genes involved in regulation of the circadian clock, such as CCA1 and TOC1, are strong candidates for the evolution of adaptive flowering time variation in C. bursa-pastoris.     

Environmental adaptations as windows on molecular evolution

Changes in gene regulation may play an important role in adaptive evolution, particularly during adaptation to a changing environment. However, little is known about the molecular mechanisms underlying adaptively significant variation in gene regulation. To address this question, we are using environmental adaptations in populations of a fish, Fundulus heteroclitus as a window into the molecular evolution of gene regulation. F. heteroclitus are found along the East Coast of North America, with populations distributed along a steep thermal gradient. At the extremes of the species range, populations have undergone local adaptation to their habitat temperatures. A variety of genes differ in their regulation between these populations. We have determined the mechanism responsible for changes in lactate dehydrogenase-B (Ldh-B) gene regulation. A limited number of mutations in the regulatory sequence of this gene result in changes in its expression. Both the phenotypic (increased LDH activity) and genotypic (changes in Ldh-B regulatory sequences) differences between populations have been shown to be affected by natural selection, rather than genetic drift. Therefore, even a small number of mutations within important regulatory sequences can provide evolutionarily significant variation and have an impact on environmental adaptation.     

MicroRNA expression and regulation in human, chimpanzee, and macaque brains

Among other factors, changes in gene expression on the human evolutionary lineage have been suggested to play an important role in the establishment of human-specific phenotypes. However, the molecular mechanisms underlying these expression changes are largely unknown. Here, we have explored the role of microRNA (miRNA) in the regulation of gene expression divergence among adult humans, chimpanzees, and rhesus macaques, in two brain regions: prefrontal cortex and cerebellum. Using a combination of high-throughput sequencing, miRNA microarrays, and Q-PCR, we have shown that up to 11% of the 325 expressed miRNA diverged significantly between humans and chimpanzees and up to 31% between humans and macaques. Measuring mRNA and protein expression in human and chimpanzee brains, we found a significant inverse relationship between the miRNA and the target genes expression divergence, explaining 2%-4% of mRNA and 4%-6% of protein expression differences. Notably, miRNA showing human-specific expression localize in neurons and target genes that are involved in neural functions. Enrichment in neural functions, as well as miRNA-driven regulation on the human evolutionary lineage, was further confirmed by experimental validation of predicted miRNA targets in two neuroblastoma cell lines. Finally, we identified a signature of positive selection in the upstream region of one of the five miRNA with human-specific expression, miR-34c-5p. This suggests that miR-34c-5p expression change took place after the split of the human and the Neanderthal lineages and had adaptive significance. Taken together these results indicate that changes in miRNA expression might have contributed to evolution of human cognitive functions.     

Allelic imbalance in Drosophila hybrid heads: exons, isoforms, and evolution

Unraveling how regulatory divergence contributes to species differences and adaptation requires identifying functional variants from among millions of genetic differences. Analysis of allelic imbalance (AI) reveals functional genetic differences in cis regulation and has demonstrated differences in cis regulation within and between species. Regulatory mechanisms are often highly conserved, yet differences between species in gene expression are extensive. What evolutionary forces explain widespread divergence in cis regulation? AI was assessed in Drosophila melanogaster-Drosophila simulans hybrid female heads using RNA-seq technology. Mapping bias was virtually eliminated by using genotype-specific references. Allele representation in DNA sequencing was used as a prior in a novel Bayesian model for the estimation of AI in RNA. Cis regulatory divergence was common in the organs and tissues of the head with 41% of genes analyzed showing significant AI. Using existing population genomic data, the relationship between AI and patterns of sequence evolution was examined. Evidence of positive selection was found in 30% of cis regulatory divergent genes. Genes involved in defense, RNAi/RISC complex genes, and those that are sex regulated are enriched among adaptively evolving cis regulatory divergent genes. For genes in these groups, adaptive evolution may play a role in regulatory divergence between species. However, there is no evidence that adaptive evolution drives most of the cis regulatory divergence that is observed. The majority of genes showed patterns consistent with stabilizing selection and neutral evolutionary processes.     

Evolution of a membrane protein regulon in Saccharomyces

Expression variation is widespread between species. The ability to distinguish regulatory change driven by natural selection from the consequences of neutral drift remains a major challenge in comparative genomics. In this work, we used observations of mRNA expression and promoter sequence to analyze signatures of selection on groups of functionally related genes in Saccharomycete yeasts. In a survey of gene regulons with expression divergence between Saccharomyces cerevisiae and S. paradoxus, we found that most were subject to variation in trans-regulatory factors that provided no evidence against a neutral model. However, we identified one regulon of membrane protein genes controlled by unlinked cis- and trans-acting determinants with coherent effects on gene expression, consistent with a history of directional, nonneutral evolution. For this membrane protein group, S. paradoxus alleles at regulatory loci were associated with elevated expression and altered stress responsiveness relative to other yeasts. In a phylogenetic comparison of promoter sequences of the membrane protein genes between species, the S. paradoxus lineage was distinguished by a short branch length, indicative of strong selective constraint. Likewise, sequence variants within the S. paradoxus population, but not across strains of other yeasts, were skewed toward low frequencies in promoters of genes in the membrane protein regulon, again reflecting strong purifying selection. Our results support a model in which a distinct expression program for the membrane protein genes in S. paradoxus has been preferentially maintained by negative selection as the result of an increased importance to organismal fitness. These findings illustrate the power of integrating expression- and sequence-based tests of natural selection in the study of evolutionary forces that underlie regulatory change.     

Adaptive protein evolution and regulatory divergence in Drosophila

Two recent studies demonstrated a positive correlation between divergence in gene expression and protein sequence in Drosophila. This correlation could be driven by positive selection or variation in functional constraint. To distinguish between these alternatives, we compared patterns of molecular evolution for 1,862 genes with two previously reported estimates of expression divergence in Drosophila. We found a slight negative trend (nonsignificant) between positive selection on protein sequence and divergence in expression levels between Drosophila melanogaster and Drosophila simulans. Conversely, shifts in expression patterns during Drosophila development showed a positive association with adaptive protein evolution, though as before the relationship was weak and not significant. Overall, we found no strong evidence for an increase in the incidence of positive selection on protein-coding regions in genes with divergent expression in Drosophila, suggesting that the previously reported positive association between protein and regulatory divergence primarily reflects variation in functional constraint.     

Connecting the sun to flowering in sunflower adaptation

Species living in seasonal environments often adaptively time their reproduction in response to photoperiod cues. We characterized the expression of genes in the flowering-time regulatory network across wild populations of the common sunflower, Helianthus annuus, that we found to be adaptively differentiated for photoperiod response. The observed clinal variation was associated with changes at multiple hierarchical levels in multiple pathways. Paralogue-specific changes in FT homologue expression and tissue-specific changes in SOC1 homologue expression were associated with loss and reversal of plasticity, respectively, suggesting that redundancy and modularity are gene network characteristics easily exploited by natural selection to produce evolutionary innovation. Distinct genetic mechanisms contribute to convergent evolution of photoperiod responses within sunflower, suggesting regulatory network architecture does not impose strong constraints on the evolution of phenotypic plasticity.     

Quantifying Adaptive Evolution in the Drosophila Immune System

It is estimated that a large proportion of amino acid substitutions in Drosophila have been fixed by natural selection, and as organisms are faced with an ever-changing array of pathogens and parasites to which they must adapt, we have investigated the role of parasite-mediated selection as a likely cause. To quantify the effect, and to identify which genes and pathways are most likely to be involved in the host–parasite arms race, we have re-sequenced population samples of 136 immunity and 287 position-matched non-immunity genes in two species of Drosophila. Using these data, and a new extension of the McDonald-Kreitman approach, we estimate that natural selection fixes advantageous amino acid changes in immunity genes at nearly double the rate of other genes. We find the rate of adaptive evolution in immunity genes is also more variable than other genes, with a small subset of immune genes evolving under intense selection. These genes, which are likely to represent hotspots of host–parasite coevolution, tend to share similar functions or belong to the same pathways, such as the antiviral RNAi pathway and the IMD signalling pathway. These patterns appear to be general features of immune system evolution in both species, as rates of adaptive evolution are correlated between the D. melanogaster and D. simulans lineages. In summary, our data provide quantitative estimates of the elevated rate of adaptive evolution in immune system genes relative to the rest of the genome, and they suggest that adaptation to parasites is an important force driving molecular evolution.     

Molecular population genetics and evolution of Drosophila meiosis genes

While many functional elements of the meiotic process are well characterized in model organisms, the genetic basis of most of the natural phenotypic variation observed in meiotic pathways has not been determined. To begin to address this issue, we characterized patterns of polymorphism and divergence in the protein-coding regions of 33 genes across 31 lines of Drosophila melanogaster and 6 lines of Drosophila simulans. We sequenced genes known to be involved in chromosome segregation, recombination, DNA repair, and related heterochromatin binding. As expected, we found several of the genes to be highly conserved, consistent with purifying selection. However, a subset of genes showed patterns of polymorphism and divergence typical of other types of natural selection. Moreover, several intriguing differences between the two Drosophila lineages were evident: along the D. simulans lineage we consistently found evidence of adaptive protein evolution, whereas along the D. melanogaster lineage several loci exhibited patterns consistent with the maintenance of protein variation.     

Recurrent adaptation in RNA interference genes across the Drosophila phylogeny

RNA interference (RNAi) is quickly emerging as a vital component of genome organization, gene regulation, and immunity in Drosophila and other species. Previous studies have suggested that, as a whole, genes involved in RNAi are under intense positive selection in Drosophila melanogaster. Here, we characterize the extent and patterns of adaptive evolution in 23 known Drosophila RNAi genes, both within D. melanogaster and across the Drosophila phylogeny. We find strong evidence for recurrent protein-coding adaptation at a large number of RNAi genes, particularly those involved in antiviral immunity and defense against transposable elements. We identify specific functional domains involved in direct protein-RNA interactions as particular hotspots of recurrent adaptation in multiple RNAi genes, suggesting that targeted coadaptive arms races may be a general feature of RNAi evolution. Our observations suggest a predictive model of how selective pressures generated by evolutionary arms race scenarios may affect multiple genes across protein interaction networks and other biochemical pathways.     

Conservation and coevolution in the scale-free human gene coexpression network

The role of natural selection in biology is well appreciated. Recently, however, a critical role for physical principles of network self-organization in biological systems has been revealed. Here, we employ a systems level view of genome-scale sequence and expression data to examine the interplay between these two sources of order, natural selection and physical self-organization, in the evolution of human gene regulation. The topology of a human gene coexpression network, derived from tissue-specific expression profiles, shows scale-free properties that imply evolutionary self-organization via preferential node attachment. Genes with numerous coexpressed partners (the hubs of the coexpression network) evolve more slowly on average than genes with fewer coexpressed partners, and genes that are coexpressed show similar rates of evolution. Thus, the strength of selective constraints on gene sequences is affected by the topology of the gene coexpression network. This connection is strong for the coding regions and 3' untranslated regions (UTRs), but the 5' UTRs appear to evolve under a different regime. Surprisingly, we found no connection between the rate of gene sequence divergence and the extent of gene expression profile divergence between human and mouse. This suggests that distinct modes of natural selection might govern sequence versus expression divergence, and we propose a model, based on rapid, adaptation-driven divergence and convergent evolution of gene expression patterns, for how natural selection could influence gene expression divergence.     

Computational identification of miRNAs,their targets and functions in three‐spined stickleback (Gasterosteus aculeatus)

An intriguing question in biology is how the evolution of gene regulation is shaped by natural selection in natural populations. Among the many known regulatory mechanisms, regulation of gene expression by microRNAs (miRNAs) is of critical importance. However, our understanding of their evolution in natural populations is limited. Studying the role of miRNAs in three‐spined stickleback, an important natural model for speciation research, may provide new insights into adaptive polymorphisms. However, lack of annotation of miRNA genes in its genome is a bottleneck. To fill this research gap, we used the genome of three‐spined stickleback to predict miRNAs and their targets. We predicted 1486 mature miRNAs using the homology‐based miRNA prediction approach. We then performed functional annotation and enrichment analysis of these targets, which identified over‐represented motifs. Further, a database resource (GAmiRdb) has been developed for dynamically searching miRNAs and their targets exclusively in three‐spined stickleback. Finally, the database was used in two case studies focusing on freshwater adaptation in natural populations. In the first study, we found 44 genomic regions overlapping with predicted miRNA targets. In the second study, we identified two SNPs altering the MRE seed site of sperm‐specific glyceraldehyde‐3‐phosphate gene. These findings highlight the importance of the GAmiRdb knowledge base in understanding adaptive evolution.