Expression profiling in primates reveals a rapid evolution of human transcription factors

Ancient eukaryotic protein interactions illuminate modern genetic traits and disorders

All eukaryotes share a common ancestor from roughly 1.5 - 1.8 billion years ago, a single-celled, swimming microbe known as LECA, the Last Eukaryotic Common Ancestor. Nearly half of the genes in modern eukaryotes were present in LECA, and many current genetic diseases and traits stem from these ancient molecular systems. To better understand these systems, we compared genes across modern organisms and identified a core set of 10,092 shared protein-coding gene families likely present in LECA, a quarter of which are uncharacterized. We then integrated >26,000 mass spectrometry proteomics analyses from 31 species to infer how these proteins interact in higher-order complexes. The resulting interactome describes the biochemical organization of LECA, revealing both known and new assemblies. We analyzed these ancient protein interactions to find new human gene-disease relationships for bone density and congenital birth defects, demonstrating the value of ancestral protein interactions for guiding functional genetics today.

Divergent Evolutionary Rates of Primate Brain Regions as Revealed by Genomics and Transcriptomics

Although the primate brain contains numerous functionally distinct structures that have experienced diverse genetic changes during the course of evolution and development, these changes remain to be explored in detail. Here we utilize two classic metrics from evolutionary biology, the evolutionary rate index (ERI) and the transcriptome age index (TAI), to investigate the evolutionary alterations that have occurred in each area and developmental stage of the primate brain. We observed a higher evolutionary rate for those genes expressed in the non-cortical areas during primate evolution, particularly in human, with the highest rate of evolution being exhibited at brain developmental stages between late infancy and early childhood. Further, the transcriptome age of the non-cortical areas was lower than that of the cerebral cortex, with the youngest age apparent at brain developmental stages between late infancy and early childhood. Our exploration of the evolutionary patterns manifest in each brain area and developmental stage provides important reference points for further research into primate brain evolution.

Identification of constrained sequence elements across 239 primate genomes

Noncoding DNA is central to our understanding of human gene regulation and complex diseases1,2, and measuring the evolutionary sequence constraint can establish the functional relevance of putative regulatory elements in the human genome3-9. Identifying the genomic elements that have become constrained specifically in primates has been hampered by the faster evolution of noncoding DNA compared to protein-coding DNA10, the relatively short timescales separating primate species11, and the previously limited availability of whole-genome sequences12. Here we construct a whole-genome alignment of 239 species, representing nearly half of all extant species in the primate order. Using this resource, we identified human regulatory elements that are under selective constraint across primates and other mammals at a 5% false discovery rate. We detected 111,318 DNase I hypersensitivity sites and 267,410 transcription factor binding sites that are constrained specifically in primates but not across other placental mammals and validate their cis-regulatory effects on gene expression. These regulatory elements are enriched for human genetic variants that affect gene expression and complex traits and diseases. Our results highlight the important role of recent evolution in regulatory sequence elements differentiating primates, including humans, from other placental mammals.

Urbanization drives adaptive evolution in a Neotropical bird

Urbanization has dramatic impacts on natural habitats and such changes may potentially drive local adaptation of urban populations. Behavioral change has been specifically shown to facilitate the fast adaptation of birds to changing environments, but few studies have investigated the genetic mechanisms of this process. Such investigations could provide insights into questions about both evolutionary theory and management of urban populations. In this study, we investigated whether local adaptation has occurred in urban populations of a Neotropical bird species, Coereba flaveola, specifically addressing whether observed behavioral adaptations are correlated to genetic signatures of natural selection. To answer this question, we sampled 24 individuals in urban and rural environments, and searched for selected loci through a genome-scan approach based on RADseq genomic data, generated and assembled using a reference genome for the species. We recovered 46 loci as putative selection outliers, and 30 of them were identified as associated with biological processes possibly related to urban adaptation, such as the regulation of energetic metabolism, regulation of genetic expression, and changes in the immunological system. Moreover, genes involved in the development of the nervous system showed signatures of selection, suggesting a link between behavioral and genetic adaptations. Our findings, in conjunction with similar results in previous studies, support the idea that cities provide a similar selective pressure on urban populations and that behavioral plasticity may be enhanced through genetic changes in urban populations.

The relationship between regulatory changes in cis and trans and the evolution of gene expression in humans and chimpanzees

BACKGROUND

Comparative gene expression studies in apes are fundamentally limited by the challenges associated with sampling across different tissues. Here, we used single-cell RNA sequencing of embryoid bodies to collect transcriptomic data from over 70 cell types in three humans and three chimpanzees.

RESULTS

We find hundreds of genes whose regulation is conserved across cell types, as well as genes whose regulation likely evolves under directional selection in one or a handful of cell types. Using embryoid bodies from a human-chimpanzee fused cell line, we also infer the proportion of inter-species regulatory differences due to changes in cis and trans elements between the species. Using the cis/trans inference and an analysis of transcription factor binding sites, we identify dozens of transcription factors whose inter-species differences in expression are affecting expression differences between humans and chimpanzees in hundreds of target genes.

CONCLUSIONS

Here, we present the most comprehensive dataset of comparative gene expression from humans and chimpanzees to date, including a catalog of regulatory mechanisms associated with inter-species differences.

Differential Hsp90-dependent gene expression is strain-specific and common among yeast strains

Enhanced phenotypic diversity increases a population's likelihood of surviving catastrophic conditions. Hsp90, an essential molecular chaperone and a central network hub in eukaryotes, has been observed to suppress or enhance the effects of genetic variation on phenotypic diversity in response to environmental cues. Because many Hsp90-interacting genes are involved in signaling transduction pathways and transcriptional regulation, we tested how common Hsp90-dependent differential gene expression is in natural populations. Many genes exhibited Hsp90-dependent strain-specific differential expression in five diverse yeast strains. We further identified transcription factors (TFs) potentially contributing to variable expression. We found that on Hsp90 inhibition or environmental stress, activities or abundances of Hsp90-dependent TFs varied among strains, resulting in differential strain-specific expression of their target genes, which consequently led to phenotypic diversity. We provide evidence that individual strains can readily display specific Hsp90-dependent gene expression, suggesting that the evolutionary impacts of Hsp90 are widespread in nature.

Tropomyosin Isoform Diversity in the Cynomolgus Monkey Heart and Skeletal Muscles Compared to Human Tissues

Old world monkeys separated from the great apes, including the ancestor of humans, about 25 million years ago, but most of the genes in humans and various nonhuman primates are quite similar even though their anatomical appearances are quite different. Like other mammals, primates have four tropomyosin genes (TPM1, TPM2, TPM3, and TPM4) each of which generates a multitude of TPM isoforms via alternative splicing. Only TPM1 produces two sarcomeric isoforms (TPM1α and TPM1κ), and TPM2, TPM3, and TPM4 each generate one sarcomeric isoform. We have cloned and sequenced TPM1α, TPM1κ, TPM2α, TPM3α, and TPM4α with RNA from cynomolgus (Cyn) monkey hearts and skeletal muscle. We believe this is the first report of directly cloning and sequencing of these monkey transcripts. In the Cyn monkey heart, the rank order of TPM isoform expression is TPM1α > TPM2α > TPM1κ > TPM3α > TPM4α. In the Cyn monkey skeletal muscle, the rank order of expression is TPM1α > TPM2α > TPM3α > TPM1κ > TPM4α. The major differences in the human heart are the increased expression of TPM1κ, although TPM1α is still the dominant transcript. In the Cyn monkey heart, the only sarcomeric TPM isoform at the protein level is TPM1α. This is in contrast to human hearts where TPM1α is the major sarcomeric isoform but a lower quantity of TPM1κ, TPM2α, and TPM3α is also detected at the protein level. These differences of tropomyosin and/or other cardiac protein expression in human and Cyn monkey hearts may reflect the differences in physiological activities in daily life.

Accounting for cis-regulatory constraint prioritizes genes likely to affect species-specific traits

Measuring allele-specific expression in interspecies hybrids is a powerful way to detect cis-regulatory changes underlying adaptation. However, it remains difficult to identify genes most likely to explain species-specific traits. Here, we outline a simple strategy that leverages population-scale allele-specific RNA-seq data to identify genes that show constrained cis-regulation within species yet show divergence between species. Applying this strategy to data from human-chimpanzee hybrid cortical organoids, we identify signatures of lineage-specific selection on genes related to saccharide metabolism, neurodegeneration, and primary cilia. We also highlight cis-regulatory divergence in CUX1 and EDNRB that may shape the trajectory of human brain development.

A Phylogenetic Framework to Simulate Synthetic Interspecies RNA-Seq Data

Interspecies RNA-Seq datasets are increasingly common, and have the potential to answer new questions about the evolution of gene expression. Single-species differential expression analysis is now a well-studied problem that benefits from sound statistical methods. Extensive reviews on biological or synthetic datasets have provided the community with a clear picture on the relative performances of the available methods in various settings. However, synthetic dataset simulation tools are still missing in the interspecies gene expression context. In this work, we develop and implement a new simulation framework. This tool builds on both the RNA-Seq and the phylogenetic comparative methods literatures to generate realistic count datasets, while taking into account the phylogenetic relationships between the samples. We illustrate the usefulness of this new framework through a targeted simulation study, that reproduces the features of a recently published dataset, containing gene expression data in adult eye tissue across blind and sighted freshwater crayfish species. Using our simulated datasets, we perform a fair comparison of several approaches used for differential expression analysis. This benchmark reveals some of the strengths and weaknesses of both the classical and phylogenetic approaches for interspecies differential expression analysis, and allows for a reanalysis of the crayfish dataset. The tool has been integrated in the R package compcodeR, freely available on Bioconductor.

Evolution of pathogenicity in obligate fungal pathogens and allied genera

Obligate fungal pathogens (ascomycetes and basidiomycetes) and oomycetes are known to cause diseases in cereal crop plants. They feed on living cells and most of them have learned to bypass the host immune machinery. This paper discusses some of the factors that are associated with pathogenicity drawing examples from ascomycetes, basidiomycetes and oomycetes, with respect to their manifestation in crop plants. The comparisons have revealed a striking similarity in the three groups suggesting convergent pathways that have arisen from three lineages independently leading to an obligate lifestyle. This review has been written with the intent, that new information on adaptation strategies of biotrophs, modifications in pathogenicity strategies and population dynamics will improve current strategies for breeding with stable resistance.

Detecting signatures of selection on gene expression

A substantial amount of phenotypic diversity results from changes in gene expression levels and patterns. Understanding how the transcriptome evolves is therefore a key priority in identifying mechanisms of adaptive change. However, in contrast to powerful models of sequence evolution, we lack a consensus model of gene expression evolution. Furthermore, recent work has shown that many of the comparative approaches used to study gene expression are subject to biases that can lead to false signatures of selection. Here we first outline the main approaches for describing expression evolution and their inherent biases. Next, we bridge the gap between the fields of phylogenetic comparative methods and transcriptomics to reinforce the main pitfalls of inferring selection on expression patterns and use simulation studies to show that shifts in tissue composition can heavily bias inferences of selection. We close by highlighting the multi-dimensional nature of transcriptional variation and identifying major unanswered questions in disentangling how selection acts on the transcriptome.

Coexpression reveals conserved gene programs that co-vary with cell type across kingdoms

What makes a mouse a mouse, and not a hamster? Differences in gene regulation between the two organisms play a critical role. Comparative analysis of gene coexpression networks provides a general framework for investigating the evolution of gene regulation across species. Here, we compare coexpression networks from 37 species and quantify the conservation of gene activity 1) as a function of evolutionary time, 2) across orthology prediction algorithms, and 3) with reference to cell- and tissue-specificity. We find that ancient genes are expressed in multiple cell types and have well conserved coexpression patterns, however they are expressed at different levels across cell types. Thus, differential regulation of ancient gene programs contributes to transcriptional cell identity. We propose that this differential regulation may play a role in cell diversification in both the animal and plant kingdoms.

Long-range promoter-enhancer contacts are conserved during evolution and contribute to gene expression robustness

Gene expression is regulated through complex molecular interactions, involving cis-acting elements that can be situated far away from their target genes. Data on long-range contacts between promoters and regulatory elements are rapidly accumulating. However, it remains unclear how these regulatory relationships evolve and how they contribute to the establishment of robust gene expression profiles. Here, we address these questions by comparing genome-wide maps of promoter-centered chromatin contacts in mouse and human. We show that there is significant evolutionary conservation of cis-regulatory landscapes, indicating that selective pressures act to preserve not only regulatory element sequences but also their chromatin contacts with target genes. The extent of evolutionary conservation is remarkable for long-range promoter–enhancer contacts, illustrating how the structure of regulatory landscapes constrains large-scale genome evolution. We show that the evolution of cis-regulatory landscapes, measured in terms of distal element sequences, synteny, or contacts with target genes, is significantly associated with gene expression evolution.

Interspecies variation in hominid gut microbiota controls host gene regulation

The gut microbiome exhibits extreme compositional variation between hominid hosts. However, it is unclear how this variation impacts host physiology across species and whether this effect can be mediated through microbial regulation of host gene expression in interacting epithelial cells. Here, we characterize the transcriptional response of human colonic epithelial cells in vitro to live microbial communities extracted from humans, chimpanzees, gorillas, and orangutans. We find that most host genes exhibit a conserved response, whereby they respond similarly to the four hominid microbiomes. However, hundreds of host genes exhibit a divergent response, whereby they respond only to microbiomes from specific host species. Such genes are associated with intestinal diseases in humans, including inflammatory bowel disease and Crohn’s disease. Last, we find that inflammation-associated microbial species regulate the expression of host genes previously associated with inflammatory bowel disease, suggesting health-related consequences for species-specific host-microbiome interactions across hominids.

Muehlbauer et al. investigate how variation between different hominid microbiomes drives host gene expression in colonic epithelial cell cultures. They find that host genes that respond only to microbiomes from a specific hominid species are linked to gastrointestinal diseases, suggesting implications for understanding how the microbiome can impact human health.

Distribution, expression and methylation analysis of positively selected genes provides insights into the evolution in Brassica rapa

It is believed that positive selection is one of the major evolutionary forces underlying organism phenotypic diversification. Nevertheless, the characteristics of positively selected genes (PSGs), have not been well investigated. In this study, we performed a genome-wide analysis of orthologous genes between Brassica rapa (B. rapa) and Brassica oleracea (B. oleracea), and identified 468 putative PSGs. Our data show that, (1) PSGs are enriched in plant hormone signal transduction pathway and the transcription factor family; (2) PSGs are significantly lower expressed than randomly selected non-PSGs; (3) PSGs with tissue specificity are significantly higher expressed in the callus and reproductive tissues (flower and silique) than in vegetable tissues (root, stem and leaf); (4) the proportion of PSGs is positively correlated with the number of retained triplication gene copies, but the expression level of PSGs decay with the increasing of triplication gene copies; (5) the CG and CHG methylation levels of PSGs are significantly higher in introns and UTRs than in the promoter and exon regions; (6) the percent of transposable element is in proportion to the methylation level, and DNA methylation (especially in the CG content) has the tendency to reduce the expression of PSGs. This study provides insights into the characteristics, evolution, function, expression and methylation of PSGs in B. rapa.

Local adaptation contributes to gene expression divergence in maize

Gene expression links genotypes to phenotypes, so identifying genes whose expression is shaped by selection will be important for understanding the traits and processes underlying local adaptation. However, detecting local adaptation for gene expression will require distinguishing between divergence due to selection and divergence due to genetic drift. Here, we adapt a QST−FST framework to detect local adaptation for transcriptome-wide gene expression levels in a population of diverse maize genotypes. We compare the number and types of selected genes across a wide range of maize populations and tissues, as well as selection on cold-response genes, drought-response genes, and coexpression clusters. We identify a number of genes whose expression levels are consistent with local adaptation and show that genes involved in stress response show enrichment for selection. Due to its history of intense selective breeding and domestication, maize evolution has long been of interest to researchers, and our study provides insight into the genes and processes important for in local adaptation of maize.

Polyadenylation-related isoform switching in human evolution revealed by full-length transcript structure

Rhesus macaque is a unique nonhuman primate model for human evolutionary and translational study, but the error-prone gene models critically limit its applications. Here, we de novo defined full-length macaque gene models based on single molecule, long-read transcriptome sequencing in four macaque tissues (frontal cortex, cerebellum, heart and testis). Overall, 8 588 227 poly(A)-bearing complementary DNA reads with a mean length of 14 106 nt were generated to compile the backbone of macaque transcripts, with the fine-scale structures further refined by RNA sequencing and cap analysis gene expression sequencing data. In total, 51 605 macaque gene models were accurately defined, covering 89.7% of macaque or 75.7% of human orthologous genes. Based on the full-length gene models, we performed a human–macaque comparative analysis on polyadenylation (PA) regulation. Using macaque and mouse as outgroup species, we identified 79 distal PA events newly originated in humans and found that the strengthening of the distal PA sites, rather than the weakening of the proximal sites, predominantly contributes to the origination of these human-specific isoforms. Notably, these isoforms are selectively constrained in general and contribute to the temporospatially specific reduction of gene expression, through the tinkering of previously existed mechanisms of nuclear retention and microRNA (miRNA) regulation. Overall, the protocol and resource highlight the application of bioinformatics in integrating multilayer genomics data to provide an intact reference for model animal studies, and the isoform switching detected may constitute a hitherto underestimated regulatory layer in shaping the human-specific transcriptome and phenotypic changes.

Examining adaptive evolution of immune activity: opportunities provided by gastropods in the age of 'omics'

Parasites threaten all free-living organisms, including molluscs. Understanding the evolution of immune defence traits in natural host populations is crucial for predicting their long-term performance under continuous infection risk. Adaptive trait evolution requires that traits are subject to selection (i.e. contribute to organismal fitness) and that they are heritable. Despite broad interest in the evolutionary ecology of immune activity in animals, the understanding of selection on and evolutionary potential of immune defence traits is far from comprehensive. For instance, empirical observations are only rarely in line with theoretical predictions of immune activity being subject to stabilizing selection. This discrepancy may be because ecoimmunological studies can typically cover only a fraction of the complexity of an animal immune system. Similarly, molecular immunology/immunogenetics studies provide a mechanistic understanding of immunity, but neglect variation that arises from natural genetic differences among individuals and from environmental conditions. Here, we review the current literature on natural selection on and evolutionary potential of immune traits in animals, signal how merging ecological immunology and genomics will strengthen evolutionary ecological research on immunity, and indicate research opportunities for molluscan gastropods for which well-established ecological understanding and/or 'immune-omics' resources are already available. This article is part of the Theo Murphy meeting issue 'Molluscan genomics: broad insights and future directions for a neglected phylum'.

Transcriptome profiling of Lymnaea stagnalis (Gastropoda) for ecoimmunological research

BACKGROUND

Host immune function can contribute to numerous ecological/evolutionary processes. Ecoimmunological studies, however, typically use one/few phenotypic immune assays and thus do not consider the complexity of the immune system. Therefore, "omics" resources that allow quantifying immune activity across multiple pathways are needed for ecoimmunological models. We applied short-read based RNAseq (Illumina NextSeq 500, PE-81) to characterise transcriptome profiles of Lymnaea stagnalis (Gastropoda), a multipurpose model snail species. We used a genetically diverse snail stock and exposed individuals to immune elicitors (injury, bacterial/trematode pathogens) and changes in environmental conditions that can alter immune activity (temperature, food availability).

RESULTS

Immune defence factors identified in the de novo assembly covered elements broadly described in other gastropods. For instance, pathogen-recognition receptors (PRR) and lectins activate Toll-like receptor (TLR) pathway and cytokines that regulate cellular and humoral defences. Surprisingly, only modest diversity of antimicrobial peptides and fibrinogen related proteins were detected when compared with other taxa. Additionally, multiple defence factors that may contribute to the phenotypic immune assays used to quantify antibacterial activity and phenoloxidase (PO)/melanisation-type reaction in this species were found. Experimental treatments revealed factors from non-self recognition (lectins) and signalling (TLR pathway, cytokines) to effectors (e.g., antibacterial proteins, PO enzymes) whose transcription depended on immune stimuli and environmental conditions, as well as components of snail physiology/metabolism that may drive these effects. Interestingly, the transcription of many factors (e.g., PRR, lectins, cytokines, PO enzymes, antibacterial proteins) showed high among-individual variation.

CONCLUSIONS

Our results indicate several uniform aspects of gastropod immunity, but also apparent differences between L. stagnalis and some previously examined taxa. Interestingly, in addition to immune defence factors that responded to immune elicitors and changes in environmental conditions, many factors showed high among-individual variation across experimental snails. We propose that such factors are highly important to be included in future ecoimmunological studies because they may be the key determinants of differences in parasite resistance among individuals both within and between natural snail populations.

The evolution of group differences in changing environments

The selection pressures that have shaped the evolution of complex traits in humans remain largely unknown, and in some contexts highly contentious, perhaps above all where they concern mean trait differences among groups. To date, the discussion has focused on whether such group differences have any genetic basis, and if so, whether they are without fitness consequences and arose via random genetic drift, or whether they were driven by selection for different trait optima in different environments. Here, we highlight a plausible alternative: that many complex traits evolve under stabilizing selection in the face of shifting environmental effects. Under this scenario, there will be rapid evolution at the loci that contribute to trait variation, even when the trait optimum remains the same. These considerations underscore the strong assumptions about environmental effects that are required in ascribing trait differences among groups to genetic differences.

Gene expression variability in human and chimpanzee populations share common determinants

Inter-individual variation in gene expression has been shown to be heritable and is often associated with differences in disease susceptibility between individuals. Many studies focused on mapping associations between genetic and gene regulatory variation, yet much less attention has been paid to the evolutionary processes that shape the observed differences in gene regulation between individuals in humans or any other primate. To begin addressing this gap, we performed a comparative analysis of gene expression variability and expression quantitative trait loci (eQTLs) in humans and chimpanzees, using gene expression data from primary heart samples. We found that expression variability in both species is often determined by non-genetic sources, such as cell-type heterogeneity. However, we also provide evidence that inter-individual variation in gene regulation can be genetically controlled, and that the degree of such variability is generally conserved in humans and chimpanzees. In particular, we found a significant overlap of orthologous genes associated with eQTLs in both species. We conclude that gene expression variability in humans and chimpanzees often evolves under similar evolutionary pressures.

Microbial control of host gene regulation and the evolution of host-microbiome interactions in primates

Recent comparative studies have found evidence consistent with the action of natural selection on gene regulation across primate species. Other recent work has shown that the microbiome can regulate host gene expression in a wide range of relevant tissues, leading to downstream effects on immunity, metabolism and other biological systems in the host. In primates, even closely related host species can have large differences in microbiome composition. One potential consequence of these differences is that host species-specific microbial traits could lead to differences in gene expression that influence primate physiology and adaptation to local environments. Here, we will discuss and integrate recent findings from primate comparative genomics and microbiome research, and explore the notion that the microbiome can influence host evolutionary dynamics by affecting gene regulation across primate host species. This article is part of the theme issue 'The role of the microbiome in host evolution'.

Speciation and the developmental alarm clock

New species arise as the genomes of populations diverge. The developmental 'alarm clock' of speciation sounds off when sufficient divergence in genetic control of development leads hybrid individuals to infertility or inviability, the world awoken to the dawn of new species with intrinsic post-zygotic reproductive isolation. Some developmental stages will be more prone to hybrid dysfunction due to how molecular evolution interacts with the ontogenetic timing of gene expression. Considering the ontogeny of hybrid incompatibilities provides a profitable connection between 'evo-devo' and speciation genetics to better link macroevolutionary pattern, microevolutionary process, and molecular mechanisms. Here, we explore speciation alongside development, emphasizing their mutual dependence on genetic network features, fitness landscapes, and developmental system drift. We assess models for how ontogenetic timing of reproductive isolation can be predictable. Experiments and theory within this synthetic perspective can help identify new rules of speciation as well as rules in the molecular evolution of development.

Independent evolution of transcript abundance and gene regulatory dynamics

Changes in gene expression drive novel phenotypes, raising interest in how gene expression evolves. In contrast to the static genome, cells modulate gene expression in response to changing environments. Previous comparative studies focused on specific conditions, describing interspecies variation in expression levels, but providing limited information about variation across different conditions. To close this gap, we profiled mRNA levels of two related yeast species in hundreds of conditions and used coexpression analysis to distinguish variation in the dynamic pattern of gene expression from variation in expression levels. The majority of genes whose expression varied between the species maintained a conserved dynamic pattern. Cases of diverged dynamic pattern correspond to genes that were induced under distinct subsets of conditions in the two species. Profiling the interspecific hybrid allowed us to distinguish between genes with predominantly cis- or trans-regulatory variation. We find that trans-varying alleles are dominantly inherited, and that cis-variations are often complemented by variations in trans Based on these results, we suggest that gene expression diverges primarily through changes in expression levels, but does not alter the pattern by which these levels are dynamically regulated.

Cell Type and Species-specific Patterns in Neuronal and Non-neuronal Methylomes of Human and Chimpanzee Cortices

Epigenetic changes have likely contributed to the large size and enhanced cognitive abilities of the human brain which evolved within the last 2 million years after the human–chimpanzee split. Using reduced representation bisulfite sequencing, we have compared the methylomes of neuronal and non-neuronal cells from 3 human and 3 chimpanzee cortices. Differentially methylated regions (DMRs) with genome-wide significance were enriched in specific genomic regions. Intraspecific methylation differences between neuronal and non-neuronal cells were approximately 3 times more abundant than interspecific methylation differences between human and chimpanzee cell types. The vast majority (>90%) of human intraspecific DMRs (including DMRs in retrotransposons) were hypomethylated in neurons, compared with glia. Intraspecific DMRs were enriched in genes associated with different neuropsychiatric disorders. Interspecific DMRs were enriched in genes showing human-specific brain histone modifications. Human–chimpanzee methylation differences were much more frequent in non-neuronal cells (n. DMRs = 666) than in neurons (n. DMRs = 96). More than 95% of interspecific DMRs in glia were hypermethylated in humans. Although without an outgroup we cannot assign whether a change in methylation occurred in the human or chimpanzee lineage, our results are consistent with a wave of methylation affecting several hundred non-neuronal genes during human brain evolution.

TreeExp2: An Integrated Framework for Phylogenetic Transcriptome Analysis

Recent innovations of next-generation sequencing such as RNA-seq have generated an enormous amount of comparative transcriptome data, which have shed lights on our understanding of the complexity of transcriptional regulatory systems. Despite numerous RNA-seq analyses, statistical methods and computational tools designed for phylogenetic transcriptome analysis and evolution have not been well developed. In response to this need, we developed software TreeExp2 specifically for RNA-seq data. The R-package TreeExp2 has implemented a suite of advanced, recently developed methods for transcriptome evolutionary analysis. Its main functions include the ancestral transcriptome inference, estimation of the strength of expression conservation, new expression distance, and the relative expression rate test. TreeExp2 provides an integrated, statistically sound framework for phylogenetic transcriptome analysis. It will considerably enhance our analytical capability for exploring the evolution and selection at the transcriptome level. The current version of TreeExp2 is available under GPLv3 license at the Github developer site https://github.com/jingwyang/TreeExp; last accessed November 12, 2019, and its online tutorial which describes the biological theories in details and fully worked case studies with real data can be found at https://jingwyang.github.io/TreeExp-Tutorial; last accessed November 12, 2019.

Evaluating Chromatin Accessibility Differences Across Multiple Primate Species Using a Joint Modeling Approach

Changes in transcriptional regulation are thought to be a major contributor to the evolution of phenotypic traits, but the contribution of changes in chromatin accessibility to the evolution of gene expression remains almost entirely unknown. To address this important gap in knowledge, we developed a new method to identify DNase I Hypersensitive (DHS) sites with differential chromatin accessibility between species using a joint modeling approach. Our method overcomes several limitations inherent to conventional threshold-based pairwise comparisons that become increasingly apparent as the number of species analyzed rises. Our approach employs a single quantitative test which is more sensitive than existing pairwise methods. To illustrate, we applied our joint approach to DHS sites in fibroblast cells from five primates (human, chimpanzee, gorilla, orangutan, and rhesus macaque). We identified 89,744 DHS sites, of which 41% are identified as differential between species using the joint model compared with 33% using the conventional pairwise approach. The joint model provides a principled approach to distinguishing single from multiple chromatin accessibility changes among species. We found that nondifferential DHS sites are enriched for nucleotide conservation. Differential DHS sites with decreased chromatin accessibility relative to rhesus macaque occur more commonly near transcription start sites (TSS), while those with increased chromatin accessibility occur more commonly distal to TSS. Further, differential DHS sites near TSS are less cell type-specific than more distal regulatory elements. Taken together, these results point to distinct classes of DHS sites, each with distinct characteristics of selection, genomic location, and cell type specificity.

Reorganization of 3D genome structure may contribute to gene regulatory evolution in primates

A growing body of evidence supports the notion that variation in gene regulation plays a crucial role in both speciation and adaptation. However, a comprehensive functional understanding of the mechanisms underlying regulatory evolution remains elusive. In primates, one of the crucial missing pieces of information towards a better understanding of regulatory evolution is a comparative annotation of interactions between distal regulatory elements and promoters. Chromatin conformation capture technologies have enabled genome-wide quantifications of such distal 3D interactions. However, relatively little comparative research in primates has been done using such technologies. To address this gap, we used Hi-C to characterize 3D chromatin interactions in induced pluripotent stem cells (iPSCs) from humans and chimpanzees. We also used RNA-seq to collect gene expression data from the same lines. We generally observed that lower-order, pairwise 3D genomic interactions are conserved in humans and chimpanzees, but higher order genomic structures, such as topologically associating domains (TADs), are not as conserved. Inter-species differences in 3D genomic interactions are often associated with gene expression differences between the species. To provide additional functional context to our observations, we considered previously published chromatin data from human stem cells. We found that inter-species differences in 3D genomic interactions, which are also associated with gene expression differences between the species, are enriched for both active and repressive marks. Overall, our data demonstrate that, as expected, an understanding of 3D genome reorganization is key to explaining regulatory evolution.

The way in which a genome folds affects the regulation of gene expression. This is often due to loops in the three-dimensional structure that bring linearly distant genes and regulatory elements into close proximity. Most studies examining three-dimensional structure genome-wide are limited to a single species. In this study, we compared three-dimensional structure in the genomes of induced pluripotent stem cells from humans and chimpanzees. We collected gene expression data from the same samples, which allowed us to assess the contribution of three-dimensional chromatin conformation to gene regulatory evolution in primates. Our results demonstrate that gene expression differences between the species may often be mediated by differences in three-dimensional genomic interactions. Our data also suggest that large-scale chromatin structures (i.e. topologically associating domains, TADs) are not well conserved in their placement across species. We hope the analytical paradigms we present here could serve as a basis for future comparative studies of three-dimensional genome organization, elucidating the putative functional regulatory loci driving speciation.

Estimating the strength of expression conservation from high throughput RNA-seq data

Motivation

Evolution of gene across species is usually subject to the stabilizing selection to maintain the optimal expression level. While it is generally accepted that the resulting expression conservation may vary considerably among genes, statistically reliable estimation remains challenging, due to few species included in current comparative RNA-seq data with high number of unknown parameters.

Results

In this paper, we develop a gamma distribution model to describe how the strength of expression conservation (denoted by W) varies among genes. Given the high throughput RNA-seq datasets from multiple species, we then formulate an empirical Bayesian procedure to estimate W for each gene. Our case studies showed that those W-estimates are useful to study the evolutionary pattern of expression conservation.

Availability and implementation

Our method has been implemented in the R-package software, TreeExp, which is publically available at Github develop site https://github.com/hr1912/TreeExp. It involves three functions: estParaGamma, estParaQ and estParaWBayesian. The manual for software TreeExp is available at https://github.com/hr1912/TreeExp/tree/master/vignettes. For any question, one may contact Dr Hang Ruan (Hang.Ruan@uth.tmc.edu).

Evolution of DNA Methylation in Papio Baboons

Changes in gene regulation have long been thought to play an important role in primate evolution. However, although a number of studies have compared genome-wide gene expression patterns across primate species, fewer have investigated the gene regulatory mechanisms that underlie such patterns, or the relative contribution of drift versus selection. Here, we profiled genome-scale DNA methylation levels in blood samples from five of the six extant species of the baboon genus Papio (4-14 individuals per species). This radiation presents the opportunity to investigate DNA methylation divergence at both shallow and deeper timescales (0.380-1.4 My). In contrast to studies in human populations, but similar to studies in great apes, DNA methylation profiles clearly mirror genetic and geographic structure. Divergence in DNA methylation proceeds fastest in unannotated regions of the genome and slowest in regions of the genome that are likely more constrained at the sequence level (e.g., gene exons). Both heuristic approaches and Ornstein-Uhlenbeck models suggest that DNA methylation levels at a small set of sites have been affected by positive selection, and that this class is enriched in functionally relevant contexts, including promoters, enhancers, and CpG islands. Our results thus indicate that the rate and distribution of DNA methylation changes across the genome largely mirror genetic structure. However, at some CpG sites, DNA methylation levels themselves may have been a target of positive selection, pointing to loci that could be important in connecting sequence variation to fitness-related traits.

Lineage-Specific Expression Divergence in Grasses Is Associated with Male Reproduction, Host-Pathogen Defense, and Domestication

Poaceae (grasses) is an agriculturally important and widely distributed family of plants with extraordinary phenotypic diversity, much of which was generated under recent lineage-specific evolution. Yet, little is known about the genes and functional modules involved in the lineage-specific divergence of grasses. Here, I address this question on a genome-wide scale by applying a novel branch-based statistic of lineage-specific expression divergence, LED, to RNA-seq data from nine tissues of the wild grass Brachypodium distachyon and its domesticated relatives Oryza sativa japonica (rice) and Sorghum bicolor (sorghum). I find that LED is generally smallest in B. distachyon and largest in O. sativa japonica, which underwent domestication earlier than S. bicolor, supporting the hypothesis that domestication may increase the rate of lineage-specific expression divergence in grasses. Moreover, in all three species, LED is positively correlated with protein-coding sequence divergence and tissue specificity, and negatively correlated with network connectivity. Further analysis reveals that genes with large LED are often primarily expressed in anther, implicating lineage-specific expression divergence in the evolution of male reproductive phenotypes. Gene ontology enrichment analysis also identifies an overrepresentation of terms related to male reproduction in the two domesticated grasses, as well as to those involved in host-pathogen defense in all three species. Last, examinations of genes with the largest LED reveal that their lineage-specific expression divergence may have contributed to antimicrobial functions in B. distachyon, to enhanced adaptation and yield during domestication in O. sativa japonica, and to defense against a widespread and devastating fungal pathogen in S. bicolor. Together, these findings suggest that lineage-specific expression divergence in grasses may increase under domestication and preferentially target rapidly evolving genes involved in male reproduction, host-pathogen defense, and the origin of domesticated phenotypes.

Post-translational buffering leads to convergent protein expression levels between primates

BACKGROUND

Differences in gene regulation between human and closely related species influence phenotypes that are distinctly human. While gene regulation is a multi-step process, the majority of research concerning divergence in gene regulation among primates has focused on transcription.

RESULTS

To gain a comprehensive view of gene regulation, we surveyed genome-wide ribosome occupancy, which reflects levels of protein translation, in lymphoblastoid cell lines derived from human, chimpanzee, and rhesus macaque. We further integrated messenger RNA and protein level measurements collected from matching cell lines. We find that, in addition to transcriptional regulation, the major factor determining protein level divergence between human and closely related species is post-translational buffering. Inter-species divergence in transcription is generally propagated to the level of protein translation. In contrast, gene expression divergence is often attenuated post-translationally, potentially mediated through post-translational modifications.

CONCLUSIONS

Results from our analysis indicate that post-translational buffering is a conserved mechanism that led to relaxation of selective constraint on transcript levels in humans.

Human-specific features of spatial gene expression and regulation in eight brain regions

Molecular maps of the human brain alone do not inform us of the features unique to humans. Yet, the identification of these features is important for understanding both the evolution and nature of human cognition. Here, we approached this question by analyzing gene expression and H3K27ac chromatin modification data collected in eight brain regions of humans, chimpanzees, gorillas, a gibbon, and macaques. An analysis of spatial transcriptome trajectories across eight brain regions in four primate species revealed 1851 genes showing human-specific transcriptome differences in one or multiple brain regions, in contrast to 240 chimpanzee-specific differences. More than half of these human-specific differences represented elevated expression of genes enriched in neuronal and astrocytic markers in the human hippocampus, whereas the rest were enriched in microglial markers and displayed human-specific expression in several frontal cortical regions and the cerebellum. An analysis of the predicted regulatory interactions driving these differences revealed the role of transcription factors in species-specific transcriptome changes, and epigenetic modifications were linked to spatial expression differences conserved across species.

The naked ape as an evolutionary model, 50 years later

Evolution acts through a combination of four different drivers: (1) mutation, (2) selection, (3) genetic drift, and (4) developmental constraints. There is a tendency among some biologists to frame evolution as the sole result of natural selection, and this tendency is reinforced by many popular texts. “The Naked Ape” by Desmond Morris, published 50 years ago, is no exception. In this paper I argue that evolutionary biology is much richer than natural selection alone. I illustrate this by reconstructing the evolutionary history of five different organs of the human body: foot, pelvis, scrotum, hand and brain. Factors like developmental tinkering, by-product evolution, exaptation and heterochrony are powerful forces for body-plan innovations and the appearance of such innovations in human ancestors does not always require an adaptive explanation. While Morris explained the lack of body hair in the human species by sexual selection, I argue that molecular tinkering of regulatory genes expressed in the brain, followed by positive selection for neotenic features, may have been the driving factor, with loss of body hair as a secondary consequence.

Substantial contribution of genetic variation in the expression of transcription factors to phenotypic variation revealed by eRD-GWAS

BACKGROUND

There are significant limitations in existing methods for the genome-wide identification of genes whose expression patterns affect traits.

RESULTS

The transcriptomes of five tissues from 27 genetically diverse maize inbred lines were deeply sequenced to identify genes exhibiting high and low levels of expression variation across tissues or genotypes. Transcription factors are enriched among genes with the most variation in expression across tissues, as well as among genes with higher-than-median levels of variation in expression across genotypes. In contrast, transcription factors are depleted among genes whose expression is either highly stable or highly variable across genotypes. We developed a Bayesian-based method for genome-wide association studies (GWAS) in which RNA-seq-based measures of transcript accumulation are used as explanatory variables (eRD-GWAS). The ability of eRD-GWAS to identify true associations between gene expression variation and phenotypic diversity is supported by analyses of RNA co-expression networks, protein-protein interaction networks, and gene regulatory networks. Genes associated with 13 traits were identified using eRD-GWAS on a panel of 369 maize inbred lines. Predicted functions of many of the resulting trait-associated genes are consistent with the analyzed traits. Importantly, transcription factors are significantly enriched among trait-associated genes identified with eRD-GWAS.

CONCLUSIONS

eRD-GWAS is a powerful tool for associating genes with traits and is complementary to SNP-based GWAS. Our eRD-GWAS results are consistent with the hypothesis that genetic variation in transcription factor expression contributes substantially to phenotypic diversity.

Evolution of new regulatory functions on biophysically realistic fitness landscapes

Gene expression is controlled by networks of regulatory proteins that interact specifically with external signals and DNA regulatory sequences. These interactions force the network components to co-evolve so as to continually maintain function. Yet, existing models of evolution mostly focus on isolated genetic elements. In contrast, we study the essential process by which regulatory networks grow: the duplication and subsequent specialization of network components. We synthesize a biophysical model of molecular interactions with the evolutionary framework to find the conditions and pathways by which new regulatory functions emerge. We show that specialization of new network components is usually slow, but can be drastically accelerated in the presence of regulatory crosstalk and mutations that promote promiscuous interactions between network components.Gene networks evolve by transcription factor (TF) duplication and divergence of their binding site specificities, but little is known about the global constraints at play. Here, the authors study the coevolution of TFs and binding sites using a biophysical-evolutionary approach, and show that the emerging complex fitness landscapes strongly influence regulatory evolution with a role for crosstalk.

Hypoxia Inducible Factor (HIF) transcription factor family expansion, diversification, divergence and selection in eukaryotes

Hypoxia inducible factor (HIF) transcription factors are crucial for regulating a variety of cellular activities in response to oxygen stress (hypoxia). In this study, we determine the evolutionary history of HIF genes and their associated transactivation domains, as well as perform selection and functional divergence analyses across their four characteristic domains. Here we show that the HIF genes are restricted to metazoans: At least one HIF-α homolog is found within the genomes of non-bilaterians and bilaterian invertebrates, while most vertebrate genomes contain between two and six HIF-α genes. We also find widespread purifying selection across all four characteristic domain types, bHLH, PAS, NTAD, CTAD, in HIF-α genes, and evidence for Type I functional divergence between HIF-1α, HIF-2α /EPAS, and invertebrate HIF genes. Overall, we describe the evolutionary histories of the HIF transcription factor gene family and its associated transactivation domains in eukaryotes. We show that the NTAD and CTAD domains appear de novo, without any appearance outside of the HIF-α subunits. Although they both appear in invertebrates as well as vertebrate HIF- α sequences, there seems to have been a substantial loss across invertebrates or were convergently acquired in these few lineages. We reaffirm that HIF-1α is phylogenetically conserved among most metazoans, whereas HIF-2α appeared later. Overall, our findings can be attributed to the substantial integration of this transcription factor family into the critical tasks associated with maintenance of oxygen homeostasis and vascularization, particularly in the vertebrate lineage.

Brownian model of transcriptome evolution and phylogenetic network visualization between tissues

While phylogenetic analysis of transcriptomes of the same tissue is usually congruent with the species tree, the controversy emerges when multiple tissues are included, that is, whether species from the same tissue are clustered together, or different tissues from the same species are clustered together. Recent studies have suggested that phylogenetic network approach may shed some lights on our understanding of multi-tissue transcriptome evolution; yet the underlying evolutionary mechanism remains unclear. In this paper we develop a Brownian-based model of transcriptome evolution under the phylogenetic network that can statistically distinguish between the patterns of species-clustering and tissue-clustering. Our model can be used as a null hypothesis (neutral transcriptome evolution) for testing any correlation in tissue evolution, can be applied to cancer transcriptome evolution to study whether two tumors of an individual appeared independently or via metastasis, and can be useful to detect convergent evolution at the transcriptional level.

Impacts of Neanderthal-Introgressed Sequences on the Landscape of Human Gene Expression

Regulatory variation influencing gene expression is a key contributor to phenotypic diversity, both within and between species. Unfortunately, RNA degrades too rapidly to be recovered from fossil remains, limiting functional genomic insights about our extinct hominin relatives. Many Neanderthal sequences survive in modern humans due to ancient hybridization, providing an opportunity to assess their contributions to transcriptional variation and to test hypotheses about regulatory evolution. We developed a flexible Bayesian statistical approach to quantify allele-specific expression (ASE) in complex RNA-seq datasets. We identified widespread expression differences between Neanderthal and modern human alleles, indicating pervasive cis-regulatory impacts of introgression. Brain regions and testes exhibited significant downregulation of Neanderthal alleles relative to other tissues, consistent with natural selection influencing the tissue-specific regulatory landscape. Our study demonstrates that Neanderthal-inherited sequences are not silent remnants of ancient interbreeding but have measurable impacts on gene expression that contribute to variation in modern human phenotypes.

Evolution of transcript modification by N6-methyladenosine in primates

Phenotypic differences within populations and between closely related species are often driven by variation and evolution of gene expression. However, most analyses have focused on the effects of genomic variation at cis-regulatory elements such as promoters and enhancers that control transcriptional activity, and little is understood about the influence of post-transcriptional processes on transcript evolution. Post-transcriptional modification of RNA by N⁶-methyladenosine (m⁶A) has been shown to be widespread throughout the transcriptome, and this reversible mark can affect transcript stability and translation dynamics. Here we analyze m⁶A mRNA modifications in lymphoblastoid cell lines (LCLs) from human, chimpanzee and rhesus, and we identify patterns of m⁶A evolution among species. We find that m⁶A evolution occurs in parallel with evolution of consensus RNA sequence motifs known to be associated with the enzymatic complexes that regulate m⁶A dynamics, and expression evolution of m⁶A-modified genes occurs in parallel with m⁶A evolution.

Epigenetic mechanisms and associated brain circuits in the regulation of positive emotions: A role for transposable elements

Epigenetic programming and reprogramming are at the heart of cellular differentiation and represent developmental and evolutionary mechanisms in both germline and somatic cell lines. Only about 2% of our genome is composed of protein-coding genes, while the remaining 98%, once considered "junk" DNA, codes for regulatory/epigenetic elements that control how genes are expressed in different tissues and across time from conception to death. While we already know that epigenetic mechanisms are at play in cancer development and in regulating metabolism (cellular and whole body), the role of epigenetics in the developing prenatal and postnatal brain, and in maintaining a proper brain activity throughout the various stages of life, in addition to having played a critical role in human evolution, is a relatively new domain of knowledge. Here we present the current state-of-the-art techniques and results of these studies within the domain of emotions, and then speculate on how genomic and epigenetic mechanisms can modify and potentially alter our emotional (limbic) brain and affect our social interactions. J. Comp. Neurol. 524:2944-2954, 2016. © 2016 Wiley Periodicals, Inc.

Monkey-based research on human disease: the implications of genetic differences

Assertions that the use of monkeys to investigate human diseases is valid scientifically are frequently based on a reported 90-93% genetic similarity between the species. Critical analyses of the relevance of monkey studies to human biology, however, indicate that this genetic similarity does not result in sufficient physiological similarity for monkeys to constitute good models for research, and that monkey data do not translate well to progress in clinical practice for humans. Salient examples include the failure of new drugs in clinical trials, the highly different infectivity and pathology of SIV/HIV, and poor extrapolation of research on Alzheimer's disease, Parkinson's disease and stroke. The major molecular differences underlying these inter-species phenotypic disparities have been revealed by comparative genomics and molecular biology - there are key differences in all aspects of gene expression and protein function, from chromosome and chromatin structure to post-translational modification. The collective effects of these differences are striking, extensive and widespread, and they show that the superficial similarity between human and monkey genetic sequences is of little benefit for biomedical research. The extrapolation of biomedical data from monkeys to humans is therefore highly unreliable, and the use of monkeys must be considered of questionable value, particularly given the breadth and potential of alternative methods of enquiry that are currently available to scientists.

Evolution of Gene Regulation in Humans

As a species, we possess unique biological features that distinguish us from other primates. Here, we review recent efforts to identify changes in gene regulation that drove the evolution of novel human phenotypes. We discuss genotype-directed comparisons of human and nonhuman primate genomes to identify human-specific genetic changes that may encode new regulatory functions. We also review phenotype-directed approaches, which use comparisons of gene expression or regulatory function in homologous human and nonhuman primate cells and tissues to identify changes in expression levels or regulatory activity that may be due to genetic changes in humans. Together, these studies are beginning to reveal the landscape of regulatory innovation in human evolution and point to specific regulatory changes for further study. Finally, we highlight two novel strategies to model human-specific regulatory functions in vivo: primate induced pluripotent stem cells and the generation of humanized mice by genome editing.

Enhancer Runaway and the Evolution of Diploid Gene Expression

Evidence is mounting that the evolution of gene expression plays a major role in adaptation and speciation. Understanding the evolution of gene regulatory regions is indeed an essential step in linking genotypes and phenotypes and in understanding the molecular mechanisms underlying evolutionary change. The common view is that expression traits (protein folding, expression timing, tissue localization and concentration) are under natural selection at the individual level. Here, we use a theoretical approach to show that, in addition, in diploid organisms, enhancer strength (i.e., the ability of enhancers to activate transcription) may increase in a runaway process due to competition for expression between homologous enhancer alleles. These alleles may be viewed as self-promoting genetic elements, as they spread without conferring a benefit at the individual level. They gain a selective advantage by getting associated to better genetic backgrounds: deleterious mutations are more efficiently purged when linked to stronger enhancers. This process, which has been entirely overlooked so far, may help understand the observed overrepresentation of cis-acting regulatory changes in between-species phenotypic differences, and sheds a new light on investigating the contribution of gene expression evolution to adaptation.

With the advent of new sequencing technologies, the evolution of gene expression regulation is becoming a subject of intensive research. In this paper, we report an entirely new phenomenon acting on the evolution of gene regulatory sequences. We show that in a small genomic region around genes there is a selection pressure to increase expression, such that stronger enhancers are favored. This leads to an open-ended escalation of enhancer strength. This outcome is not a particular case and we expect it to occur for all genes in nearly all eukaryotic diploid organisms. We also show that this escalation is not stopped by stabilizing selection on expression profiles. Indeed, regulators may coevolve to maintain optimal phenotypes despite the enhancer strength escalation. This widespread phenomenon can significantly shift our understanding of gene regulatory regions and opens a wide array of possible tests.

Widespread and Adaptive Alterations in Genome-Wide Gene Expression Associated with Ecological Divergence of Two Oryza Species

Ecological speciation is a common mechanism by which new species arise. Despite great efforts, the role of gene expression in ecological divergence and speciation is poorly understood. Here, we conducted a genome-wide gene expression investigation of two Oryza species that are evolutionarily young and distinct in ecology and morphology. Using digital gene expression technology and the paired-end RNA sequencing method, we obtained 21,415 expressed genes across three reproduction-related tissues. Of them, approximately 8% (1,717) differed significantly in expression levels between the two species and these differentially expressed genes are randomly distributed across the genome. Moreover, 62% (1,064) of the differentially expressed genes exhibited a signature of directional selection in at least one species. Importantly, the genes with differential expression between species evolved more rapidly at the 5' flanking sequences than the genes without differential expression relative to coding sequences, suggesting that cis-regulatory changes are likely adaptive and play an important role in the ecological divergence of the two species. Finally, we showed evidence of significant differentiation between species in phenotype traits and observed that genes with differential expression were overrepresented with functional terms involving phenotypic and ecological differentiation between the two species, including reproduction- and stress-related characteristics. Our findings demonstrate that ecological speciation is associated with widespread and adaptive alterations in genome-wide gene expression and provide new insights into the importance of regulatory evolution in ecological speciation in plants.

Epigenetic modifications are associated with inter-species gene expression variation in primates

BACKGROUND

Changes in gene regulation have long been thought to play an important role in evolution and speciation, especially in primates. Over the past decade, comparative genomic studies have revealed extensive inter-species differences in gene expression levels, yet we know much less about the extent to which regulatory mechanisms differ between species.

RESULTS

To begin addressing this gap, we perform a comparative epigenetic study in primate lymphoblastoid cell lines, to query the contribution of RNA polymerase II and four histone modifications, H3K4me1, H3K4me3, H3K27ac, and H3K27me3, to inter-species variation in gene expression levels. We find that inter-species differences in mark enrichment near transcription start sites are significantly more often associated with inter-species differences in the corresponding gene expression level than expected by chance alone. Interestingly, we also find that first-order interactions among the five marks, as well as chromatin states, do not markedly contribute to the degree of association between the marks and inter-species variation in gene expression levels, suggesting that the marginal effects of the five marks dominate this contribution.

CONCLUSIONS

Our observations suggest that epigenetic modifications are substantially associated with changes in gene expression levels among primates and may represent important molecular mechanisms in primate evolution.

Phylogenetic ANOVA: The Expression Variance and Evolution Model for Quantitative Trait Evolution

A number of methods have been developed for modeling the evolution of a quantitative trait on a phylogeny. These methods have received renewed interest in the context of genome-wide studies of gene expression, in which the expression levels of many genes can be modeled as quantitative traits. We here develop a new method for joint analyses of quantitative traits within- and between species, the Expression Variance and Evolution (EVE) model. The model parameterizes the ratio of population to evolutionary expression variance, facilitating a wide variety of analyses, including a test for lineage-specific shifts in expression level, and a phylogenetic ANOVA that can detect genes with increased or decreased ratios of expression divergence to diversity, analogous to the famous Hudson Kreitman Aguadé (HKA) test used to detect selection at the DNA level. We use simulations to explore the properties of these tests under a variety of circumstances and show that the phylogenetic ANOVA is more accurate than the standard ANOVA (no accounting for phylogeny) sometimes used in transcriptomics. We then apply the EVE model to a mammalian phylogeny of 15 species typed for expression levels in liver tissue. We identify genes with high expression divergence between species as candidates for expression level adaptation, and genes with high expression diversity within species as candidates for expression level conservation and/or plasticity. Using the test for lineage-specific expression shifts, we identify several candidate genes for expression level adaptation on the catarrhine and human lineages, including genes putatively related to dietary changes in humans. We compare these results to those reported previously using a model which ignores expression variance within species, uncovering important differences in performance. We demonstrate the necessity for a phylogenetic model in comparative expression studies and show the utility of the EVE model to detect expression divergence, diversity, and branch-specific shifts.

Understanding tissue expression evolution: from expression phylogeny to phylogenetic network

Our understanding of tissue expression evolution in multi-cellular model organisms has been considerably advanced with the help of high-throughput technologies from EST, microarray to RNA-seq. Yet, many controversies remained unsolved, ranging from the evolutionary patterns of tissue expressions to expression phylogenetic analysis. Moreover, despite numerous reports published, it is desirable to have a general framework for study of tissue expression evolution. In this article, we first provide an up-to-date and concise review for the study of tissue expression evolution in multi-cellular organisms. While the expression phylogeny of the same tissues sampled from closely or intermediately related species largely reflects the species phylogeny, we demonstrate that phylogenetic network approach may shed some lights for our understanding of the developmental similarity and evolutionary relatedness during the multi-tissue evolution.