Inferring mammalian tissue-specific regulatory conservation by predicting tissue-specific differences in open chromatin.

BACKGROUND: Evolutionary conservation is an invaluable tool for inferring functional significance in the genome, including regions that are crucial across many species and those that have undergone convergent evolution. Computational methods to test for sequence conservation are dominated by algorithms that examine the ability of one or more nucleotides to align across large evolutionary distances. While these nucleotide alignment-based approaches have proven powerful for protein-coding genes and some non-coding elements, they fail to capture conservation of many enhancers, distal regulatory elements that control spatial and temporal patterns of gene expression. The function of enhancers is governed by a complex, often tissue- and cell type-specific code that links combinations of transcription factor binding sites and other regulation-related sequence patterns to regulatory activity. Thus, function of orthologous enhancer regions can be conserved across large evolutionary distances, even when nucleotide turnover is high. RESULTS: We present a new machine learning-based approach for evaluating enhancer conservation that leverages the combinatorial sequence code of enhancer activity rather than relying on the alignment of individual nucleotides. We first train a convolutional neural network model that can predict tissue-specific open chromatin, a proxy for enhancer activity, across mammals. Next, we apply that model to distinguish instances where the genome sequence would predict conserved function versus a loss of regulatory activity in that tissue. We present criteria for systematically evaluating model performance for this task and use them to demonstrate that our models accurately predict tissue-specific conservation and divergence in open chromatin between primate and rodent species, vastly out-performing leading nucleotide alignment-based approaches. We then apply our models to predict open chromatin at orthologs of brain and liver open chromatin regions across hundreds of mammals and find that brain enhancers associated with neuron activity have a stronger tendency than the general population to have predicted lineage-specific open chromatin. CONCLUSION: The framework presented here provides a mechanism to annotate tissue-specific regulatory function across hundreds of genomes and to study enhancer evolution using predicted regulatory differences rather than nucleotide-level conservation measurements.

Toxin expression in snake venom evolves rapidly with constant shifts in evolutionary rates.

Key innovations provide ecological opportunity by enabling access to new resources, colonization of new environments, and are associated with adaptive radiation. The most well-known pattern associated with adaptive radiation is an early burst of phenotypic diversification. Venoms facilitate prey capture and are widely believed to be key innovations leading to adaptive radiation. However, few studies have estimated their evolutionary rate dynamics. Here, we test for patterns of adaptive evolution in venom gene expression data from 52 venomous snake species. By identifying shifts in tempo and mode of evolution along with models of phenotypic evolution, we show that snake venom exhibits the macroevolutionary dynamics expected of key innovations. Namely, all toxin families undergo shifts in their rates of evolution, likely in response to changes in adaptive optima. Furthermore, we show that rapid-pulsed evolution modelled as a Lévy process better fits snake venom evolution than conventional early burst or Ornstein-Uhlenbeck models. While our results support the idea of snake venom being a key innovation, the innovation of venom chemistry lacks clear mechanisms that would lead to reproductive isolation and thus adaptive radiation. Therefore, the extent to which venom directly influences the diversification process is still a matter of contention.

Evolution of Sex-Biased Gene Expression and Dosage Compensation in the Eye and Brain of Heliconius Butterflies.

Differences in behavior and life history traits between females and males are the basis of divergent selective pressures between sexes. It has been suggested that a way for the two sexes to deal with different life history requirements is through sex-biased gene expression. In this study, we performed a comparative sex-biased gene expression analysis of the combined eye and brain transcriptome from five Heliconius species, H. charithonia, H. sara, H. erato, H. melpomene and H. doris, representing five of the main clades from the Heliconius phylogeny. We found that the degree of sexual dimorphism in gene expression is not conserved across Heliconius. Most of the sex-biased genes identified in each species are not sex-biased in any other, suggesting that sexual selection might have driven sexually dimorphic gene expression. Only three genes shared sex-biased expression across multiple species: ultraviolet opsin UVRh1 and orthologs of Drosophila Krüppel-homolog 1 and CG9492. We also observed that in some species female-biased genes have higher evolutionary rates, but in others, male-biased genes show the fastest rates when compared with unbiased genes, suggesting that selective forces driving sex-biased gene evolution in Heliconius act in a sex- and species-specific manner. Furthermore, we found dosage compensation in all the Heliconius tested, providing additional evidence for the conservation of dosage compensation across Lepidoptera. Finally, sex-biased genes are significantly enriched on the Z, a pattern that could be a result of sexually antagonistic selection.

Sexual selection drives evolution and rapid turnover of male gene expression.

The profound and pervasive differences in gene expression observed between males and females, and the unique evolutionary properties of these genes in many species, have led to the widespread assumption that they are the product of sexual selection and sexual conflict. However, we still lack a clear understanding of the connection between sexual selection and transcriptional dimorphism, often termed sex-biased gene expression. Moreover, the relative contribution of sexual selection vs. drift in shaping broad patterns of expression, divergence, and polymorphism remains unknown. To assess the role of sexual selection in shaping these patterns, we assembled transcriptomes from an avian clade representing the full range of sexual dimorphism and sexual selection. We use these species to test the links between sexual selection and sex-biased gene expression evolution in a comparative framework. Through ancestral reconstruction of sex bias, we demonstrate a rapid turnover of sex bias across this clade driven by sexual selection and show it to be primarily the result of expression changes in males. We use phylogenetically controlled comparative methods to demonstrate that phenotypic measures of sexual selection predict the proportion of male-biased but not female-biased gene expression. Although male-biased genes show elevated rates of coding sequence evolution, consistent with previous reports in a range of taxa, there is no association between sexual selection and rates of coding sequence evolution, suggesting that expression changes may be more important than coding sequence in sexual selection. Taken together, our results highlight the power of sexual selection to act on gene expression differences and shape genome evolution.

CDROM: Classification of Duplicate gene RetentiOn Mechanisms.

BACKGROUND: Gene duplication is a major source of new genes that is thought to play an important role in phenotypic innovation. Though several mechanisms have been hypothesized to drive the functional evolution and long-term retention of duplicate genes, there are currently no software tools for assessing their genome-wide contributions. Thus, the evolutionary mechanisms by which duplicate genes acquire novel functions remain unclear in a number of taxa. RESULTS: In a recent study, researchers developed a phylogenetic approach that uses gene expression data from two species to classify the mechanisms underlying the retention of duplicate genes (Proc Natl Acad Sci USA 110:1740917414, 2013). We have implemented their classification method, as well as a more generalized method, in the R package CDROM, enabling users to apply these methods to their data and gain insights into the origin of novel biological functions after gene duplication. The CDROM R package, source code, and user manual for the R package are available for download from CRAN at https://cran.rstudio.com/web/packages/CDROM/ . Additionally, the CDROM R source code, user manual for running CDROM from the source code, and sample dataset used in this manuscript can be accessed at www.personal.psu.edu/rua15/software.html . CONCLUSIONS: CDROM is the first software package that enables genome-wide classification of the mechanisms driving the long-term retention of duplicate genes. It is user-friendly and flexible, providing researchers with a tool for studying the functional evolution of duplicate genes in a variety of taxa.

Neighboring Genes Show Correlated Evolution in Gene Expression.

When considering the evolution of a gene's expression profile, we commonly assume that this is unaffected by its genomic neighborhood. This is, however, in contrast to what we know about the lack of autonomy between neighboring genes in gene expression profiles in extant taxa. Indeed, in all eukaryotic genomes genes of similar expression-profile tend to cluster, reflecting chromatin level dynamics. Does it follow that if a gene increases expression in a particular lineage then the genomic neighbors will also increase in their expression or is gene expression evolution autonomous? To address this here we consider evolution of human gene expression since the human-chimp common ancestor, allowing for both variation in estimation of current expression level and error in Bayesian estimation of the ancestral state. We find that in all tissues and both sexes, the change in gene expression of a focal gene on average predicts the change in gene expression of neighbors. The effect is highly pronounced in the immediate vicinity (<100 kb) but extends much further. Sex-specific expression change is also genomically clustered. As genes increasing their expression in humans tend to avoid nuclear lamina domains and be enriched for the gene activator 5-hydroxymethylcytosine, we conclude that, most probably owing to chromatin level control of gene expression, a change in gene expression of one gene likely affects the expression evolution of neighbors, what we term expression piggybacking, an analog of hitchhiking.

Convergent and divergent evolution of microRNA-mediated regulation in metazoans.

The evolution of microRNAs (miRNAs) has been studied extensively to understand their roles in gene regulation and evolutionary processes. This review focuses on how miRNA-mediated regulation has evolved in bilaterian animals, highlighting both convergent and divergent evolution. Since animals and plants display significant differences in miRNA biogenesis and target recognition, the 'independent origin' hypothesis proposes that miRNA pathways in these groups independently evolved from the RNA interference (RNAi) pathway, leading to modern miRNA repertoires through convergent evolution. However, recent evidence raises the alternative possibility that the miRNA pathway might have already existed in the last common ancestor of eukaryotes, and that the differences in miRNA pathway and miRNA repertoires among animal and plant lineages arise from lineage-specific innovations and losses of miRNA pathways, miRNA acquisition, and loss of miRNAs after eukaryotic divergence. The repertoire of miRNAs has considerably expanded during bilaterian evolution, primarily through de novo creation and duplication processes, generating new miRNAs. Although ancient functionally established miRNAs are rarely lost, many newly emerged miRNAs are transient and lineage specific, following a birth-death evolutionary pattern aligning with the 'out-of-the-testis' and 'transcriptional control' hypotheses. Our focus then shifts to the convergent molecular evolution of miRNAs. We summarize how miRNA clustering and seed mimicry contribute to this phenomenon, and we review how miRNAs from different sources converge to degrade maternal messenger RNAs (mRNAs) during animal development. Additionally, we describe how miRNAs evolve across species due to changes in sequence, seed shifting, arm switching, and spatiotemporal expression patterns, which can result in variations in target sites among orthologous miRNAs across distant strains or species. We also provide a summary of the current understanding regarding how the target sites of orthologous miRNAs can vary across strains or distantly related species. Although many paralogous miRNAs retain their seed or mature sequences after duplication, alterations can occur in the seed or mature sequences or expression patterns of paralogous miRNAs, leading to functional diversification. We discuss our current understanding of the functional divergence between duplicated miRNAs, and illustrate how the functional diversification of duplicated miRNAs impacts target site evolution. By investigating these topics, we aim to enhance our current understanding of the functions and evolutionary dynamics of miRNAs. Additionally, we shed light on the existing challenges in miRNA evolutionary studies, particularly the complexity of deciphering the role of miRNA-mediated regulatory network evolution in shaping gene expression divergence and phenotypic differences among species.

Temperature-driven gene expression evolution in natural and laboratory populations highlights the crucial role of correlated fitness effects for polygenic adaptation.

The influence of pleiotropy on adaptive responses is a highly controversial topic, with limited empirical evidence available. Recognizing the pivotal role of the correlation of fitness effects, we designed an experiment to compare the adaptive gene expression evolution of natural and experimental populations. To test this, we studied the evolution of gene expression in response to temperature in two Drosophila species on a natural temperature cline in North America and replicated populations evolving in hot- and cold-temperature regimes. If fitness effects of affected traits are independent, pleiotropy is expected to constrain the adaptive response in both settings, laboratory and natural populations. However, when fitness effects are more correlated in natural populations, adaptation in the wild will be facilitated by pleiotropy. Remarkably, we find evidence for both predicted effects. In both settings, genes with strong pleiotropic effects contribute less to adaptation, indicating that the majority of fitness effects are not correlated. In addition, we discovered that genes involved in adaptation exhibited more pleiotropic effects in natural populations. We propose that this pattern can be explained by a stronger correlation of fitness effects in nature. More insights into the dual role of pleiotropy will be crucial for the understanding of polygenic adaptation.

Unraveling patterns of disrupted gene expression across a complex tissue.

Whole tissue RNASeq is the standard approach for studying gene expression divergence in evolutionary biology and provides a snapshot of the comprehensive transcriptome for a given tissue. However, whole tissues consist of diverse cell types differing in expression profiles, and the cellular composition of these tissues can evolve across species. Here, we investigate the effects of different cellular composition on whole tissue expression profiles. We compared gene expression from whole testes and enriched spermatogenesis populations in two species of house mice, Mus musculus musculus and M. m. domesticus, and their sterile and fertile F1 hybrids, which differ in both cellular composition and regulatory dynamics. We found that cellular composition differences skewed expression profiles and differential gene expression in whole testes samples. Importantly, both approaches were able to detect large-scale patterns such as disrupted X chromosome expression, although whole testes sampling resulted in decreased power to detect differentially expressed genes. We encourage researchers to account for histology in RNASeq and consider methods that reduce sample complexity whenever feasible. Ultimately, we show that differences in cellular composition between tissues can modify expression profiles, potentially altering inferred gene ontological processes, insights into gene network evolution, and processes governing gene expression evolution.

Divergence in Coding Sequence and Expression of Different Functional Categories of Immune Genes between Two Wild Rodent Species.

Differences in immune function between species could be a result of interspecific divergence in coding sequence and/or expression of immune genes. Here, we investigate how the degree of divergence in coding sequence and expression differs between functional categories of immune genes, and if differences between categories occur independently of other factors (expression level, pleiotropy). To this end, we compared spleen transcriptomes of wild-caught yellow-necked mice and bank voles. Immune genes expressed in the spleen were divided into four categories depending on the function of the encoded protein: pattern recognition receptors (PRR); signal transduction proteins; transcription factors; and cyto- and chemokines and their receptors. Genes encoding PRR and cyto-/chemokines had higher sequence divergence than genes encoding signal transduction proteins and transcription factors, even when controlling for potentially confounding factors. Genes encoding PRR also had higher expression divergence than genes encoding signal transduction proteins and transcription factors. There was a positive correlation between expression divergence and coding sequence divergence, in particular for PRR genes. We propose that this is a result of that divergence in PRR coding sequence leads to divergence in PRR expression through positive feedback of PRR ligand binding on PRR expression. When controlling for sequence divergence, expression divergence of PRR genes did not differ from other categories. Taken together, the results indicate that coding sequence divergence of PRR genes is a major cause of differences in immune function between species.

Comparative Transcriptomics across Nematode Life Cycles Reveal Gene Expression Conservation and Correlated Evolution in Adjacent Developmental Stages.

Nematodes are highly abundant animals with diverse habitats and lifestyles. Some are free living whereas others parasitize animals or plants, and among the latter, infection abilities change across developmental stages to infect hosts and complete life cycles. To determine the relationship between transcriptome evolution and morphological divergences among nematodes, we compared 48 transcriptomes of different developmental stages across eight nematode species. The transcriptomes were clustered broadly into embryo, larva, and adult stages, with the developmental plastic stages were separated from common larval stages within the larval branch. This suggests that development was the major determining factor after lifestyle changes, such as parasitism, during transcriptome evolution. Such patterns were partly accounted for by tissue-specific genes-such as those in oocytes and the hypodermis-being expressed at different proportions. Although nematodes typically have 3-5 larval stages, the transcriptomes for these stages were found to be highly correlated within each species, suggesting high similarity among larval stages across species. For the Caenorhabditis elegans-Caenorhabditis briggsae and Strongyloides stercoralis-Strongyloides venezuelensis comparisons, we found that ∼50% of genes were expressed at multiple stages, whereas half of their orthologs were also expressed in multiple but different stages. Such frequent changes in expression have resulted in concerted transcriptome evolution across adjacent stages, thus generating species-specific transcriptomes over the course of nematode evolution. Our study provides a first insight into the evolution of nematode transcriptomes beyond embryonic development.

mRNA Extraction from Gill Tissue for RNA-sequencing.

Adaptation is thought to proceed in part through spatial and temporal changes in gene expression. Fish species such as the threespine stickleback are powerful vertebrate models to study the genetic architecture of adaptive changes in gene expression since divergent adaptation to different environments is common, they are abundant and easy to study in the wild and lab, and have well-established genetic and genomic resources. Fish gills, due to their respiratory and osmoregulatory roles, show many physiological adaptations to local water chemistry, including differences in gene expression. However, obtaining high-quality RNA using popular column-based extraction methods can be challenging from small tissue samples high in cartilage and bone such as fish gills. Here, we describe a bead-based mRNA extraction and transcriptome RNA-seq protocol that does not use purification columns. The protocol can be readily scaled according to sample size for the purposes of diverse gene expression experiments using animal or plant tissue.

Cis and trans effects differentially contribute to the evolution of promoters and enhancers.

BACKGROUND: Gene expression differences between species are driven by both cis and trans effects. Whereas cis effects are caused by genetic variants located on the same DNA molecule as the target gene, trans effects are due to genetic variants that affect diffusible elements. Previous studies have mostly assessed the impact of cis and trans effects at the gene level. However, how cis and trans effects differentially impact regulatory elements such as enhancers and promoters remains poorly understood. Here, we use massively parallel reporter assays to directly measure the transcriptional outputs of thousands of individual regulatory elements in embryonic stem cells and measure cis and trans effects between human and mouse. RESULTS: Our approach reveals that cis effects are widespread across transcribed regulatory elements, and the strongest cis effects are associated with the disruption of motifs recognized by strong transcriptional activators. Conversely, we find that trans effects are rare but stronger in enhancers than promoters and are associated with a subset of transcription factors that are differentially expressed between human and mouse. While we find that cis-trans compensation is common within promoters, we do not see evidence of widespread cis-trans compensation at enhancers. Cis-trans compensation is inversely correlated with enhancer redundancy, suggesting that such compensation may often occur across multiple enhancers. CONCLUSIONS: Our results highlight differences in the mode of evolution between promoters and enhancers in complex mammalian genomes and indicate that studying the evolution of individual regulatory elements is pivotal to understand the tempo and mode of gene expression evolution.

A 24 h Age Difference Causes Twice as Much Gene Expression Divergence as 100 Generations of Adaptation to a Novel Environment.

Gene expression profiling is one of the most reliable high-throughput phenotyping methods, allowing researchers to quantify the transcript abundance of expressed genes. Because many biotic and abiotic factors influence gene expression, it is recommended to control them as tightly as possible. Here, we show that a 24 h age difference of Drosophilasimulans females that were subjected to RNA sequencing (RNA-Seq) five and six days after eclosure resulted in more than 2000 differentially expressed genes. This is twice the number of genes that changed expression during 100 generations of evolution in a novel hot laboratory environment. Importantly, most of the genes differing in expression due to age introduce false positives or negatives if an adaptive gene expression analysis is not controlled for age. Our results indicate that tightly controlled experimental conditions, including precise developmental staging, are needed for reliable gene expression analyses, in particular in an evolutionary framework.

Transposable elements significantly contributed to the core promoters in the human genome.

Transposable elements (TEs) are major components of the human genome constituting at least half of it. More than half a century ago, Barbara McClintock and later Roy Britten and Eric Davidson have postulated that they might be major players in the host gene regulation. We have scanned a large amount of data produced by ENCODE project for active transcription binding sites (TFBSs) located in TE-originated parts of polymerase II promoters. In total, more than 35,000 promoters in six different tissues were analyzed and over 26,000 of them harbored TEs. Moreover, these TEs usually provide one or more of TFBSs in the host promoters, which resulted in more than 6% of active TFBSs in these regions located in the TE-originated sequences. Rewiring of transcription circuits played a major role in mammalian evolution and consequently increased their functional and morphological diversity. In this large-scale analysis, we have demonstrated that TEs contributed a large fraction of human TFBSs. Interestingly, these TFBSs usually act in a tissue-specific manner. Thus, our study clearly showed that TEs played a significant role in shaping expression pattern in mammals and humans in particular. Furthermore, since several TE families are still active in our genome, they continue to influence not only our genome architecture but also gene functioning in a broader sense.

RPASE: Individual-based allele-specific expression detection without prior knowledge of haplotype phase.

Variation in gene expression is believed to make a significant contribution to phenotypic diversity and divergence. The analysis of allele-specific expression (ASE) can reveal important insights into gene expression regulation. We developed a novel method called RPASE (Read-backed Phasing-based ASE detection) to test for genes that show ASE. With mapped RNA-seq data from a single individual and a list of SNPs from the same individual as the only input, RPASE is capable of aggregating information across multiple dependent SNPs and producing individual-based gene-level tests for ASE. RPASE performs well in simulations and comparisons. We applied RPASE to multiple bird species and found a potentially rich landscape of ASE.

Pervasive Correlated Evolution in Gene Expression Shapes Cell and Tissue Type Transcriptomes.

The evolution and diversification of cell types is a key means by which animal complexity evolves. Recently, hierarchical clustering and phylogenetic methods have been applied to RNA-seq data to infer cell type evolutionary history and homology. A major challenge for interpreting this data is that cell type transcriptomes may not evolve independently due to correlated changes in gene expression. This nonindependence can arise for several reasons, such as common regulatory sequences for genes expressed in multiple tissues, that is, pleiotropic effects of mutations. We develop a model to estimate the level of correlated transcriptome evolution (LCE) and apply it to different data sets. The results reveal pervasive correlated transcriptome evolution among different cell and tissue types. In general, tissues related by morphology or developmental lineage exhibit higher LCE than more distantly related tissues. Analyzing new data collected from bird skin appendages suggests that LCE decreases with the phylogenetic age of tissues compared, with recently evolved tissues exhibiting the highest LCE. Furthermore, we show correlated evolution can alter patterns of hierarchical clustering, causing different tissue types from the same species to cluster together. To identify genes that most strongly contribute to the correlated evolution signal, we performed a gene-wise estimation of LCE on a data set with ten species. Removing genes with high LCE allows for accurate reconstruction of evolutionary relationships among tissue types. Our study provides a statistical method to measure and account for correlated gene expression evolution when interpreting comparative transcriptome data.

Bayesian Inference of Allele-Specific Gene Expression Indicates Abundant Cis-Regulatory Variation in Natural Flycatcher Populations.

Polymorphism in cis-regulatory sequences can lead to different levels of expression for the two alleles of a gene, providing a starting point for the evolution of gene expression. Little is known about the genome-wide abundance of genetic variation in gene regulation in natural populations but analysis of allele-specific expression (ASE) provides a means for investigating such variation. We performed RNA-seq of multiple tissues from population samples of two closely related flycatcher species and developed a Bayesian algorithm that maximizes data usage by borrowing information from the whole data set and combines several SNPs per transcript to detect ASE. Of 2,576 transcripts analyzed in collared flycatcher, ASE was detected in 185 (7.2%) and a similar frequency was seen in the pied flycatcher. Transcripts with statistically significant ASE commonly showed the major allele in >90% of the reads, reflecting that power was highest when expression was heavily biased toward one of the alleles. This would suggest that the observed frequencies of ASE likely are underestimates. The proportion of ASE transcripts varied among tissues, being lowest in testis and highest in muscle. Individuals often showed ASE of particular transcripts in more than one tissue (73.4%), consistent with a genetic basis for regulation of gene expression. The results suggest that genetic variation in regulatory sequences commonly affects gene expression in natural populations and that it provides a seedbed for phenotypic evolution via divergence in gene expression.

Transcriptional Interference Promotes Rapid Expression Divergence of Drosophila Nested Genes.

Nested genes are the most common form of protein-coding overlap in eukaryotic genomes. Previous studies have shown that nested genes accumulate rapidly over evolutionary time, typically via the insertion of short young duplicate genes into long introns. However, the evolutionary relationship between nested genes remains unclear. Here, I compare RNA-seq expression profiles of nested, proximal intra-chromosomal, intermediate intra-chromosomal, distant intra-chromosomal, and inter-chromosomal gene pairs in two Drosophila species. I find that expression profiles of nested genes are more divergent than those of any other class of genes, supporting the hypothesis that concurrent expression of nested genes is deleterious due to transcriptional interference. Further analysis reveals that expression profiles of derived nested genes are more divergent than those of their ancestral un-nested orthologs, which are more divergent than those of un-nested genes with similar genomic features. Thus, gene expression divergence between nested genes is likely caused by selection against nesting of genes with insufficiently divergent expression profiles, as well as by continued expression divergence after nesting. Moreover, expression divergence and sequence evolutionary rates are elevated in young nested genes and reduced in old nested genes, indicating that a burst of rapid evolution occurs after nesting. Together, these findings suggest that similarity between expression profiles of nested genes is deleterious due to transcriptional interference, and that natural selection addresses this problem both by eradicating highly deleterious nestings and by enabling rapid expression divergence of surviving nested genes, thereby quickly limiting or abolishing transcriptional interference.

Evolution of the correlation between expression divergence and protein divergence in mammals.

Divergence of protein sequences and gene expression patterns are two fundamental mechanisms that generate organismal diversity. Here, we have used genome and transcriptome data from eight mammals and one bird to study the positive correlation of these two processes throughout mammalian evolution. We demonstrate that the correlation is stable over time and most pronounced in neural tissues, which indicates that it is the result of strong negative selection. The correlation is not driven by genes with specific functions and may instead best be viewed as an evolutionary default state, which can nevertheless be evaded by certain gene types. In particular, genes with developmental and neural functions are skewed toward changes in gene expression, consistent with selection against pleiotropic effects associated with changes in protein sequences. Surprisingly, we find that the correlation between expression divergence and protein divergence is not explained by between-gene variation in expression level, tissue specificity, protein connectivity, or other investigated gene characteristics, suggesting that it arises independently of these gene traits. The selective constraints on protein sequences and gene expression patterns also fluctuate in a coordinate manner across phylogenetic branches: We find that gene-specific changes in the rate of protein evolution in a specific mammalian lineage tend to be accompanied by similar changes in the rate of expression evolution. Taken together, our findings highlight many new aspects of the correlation between protein divergence and expression divergence, and attest to its role as a fundamental property of mammalian genome evolution.