An effective model for natural selection in promoters

Mutational scans reveal differential evolvability of Drosophila promoters and enhancers

Rapid enhancer and slow promoter evolution have been demonstrated through comparative genomics. However, it is not clear how this information is encoded genetically and if this can be used to place evolution in a predictive context. Part of the challenge is that our understanding of the potential for regulatory evolution is biased primarily toward natural variation or limited experimental perturbations. Here, to explore the evolutionary capacity of promoter variation, we surveyed an unbiased mutation library for three promoters in Drosophila melanogaster. We found that mutations in promoters had limited to no effect on spatial patterns of gene expression. Compared to developmental enhancers, promoters are more robust to mutations and have more access to mutations that can increase gene expression, suggesting that their low activity might be a result of selection. Consistent with these observations, increasing the promoter activity at the endogenous locus of shavenbaby led to increased transcription yet limited phenotypic changes. Taken together, developmental promoters may encode robust transcriptional outputs allowing evolvability through the integration of diverse developmental enhancers.

This article is part of the theme issue ‘Interdisciplinary approaches to predicting evolutionary biology’.

TRACE: transcription factor footprinting using chromatin accessibility data and DNA sequence

Transcription is tightly regulated by cis-regulatory DNA elements where transcription factors (TFs) can bind. Thus, identification of TF binding sites (TFBSs) is key to understanding gene expression and whole regulatory networks within a cell. The standard approaches used for TFBS prediction, such as position weight matrices (PWMs) and chromatin immunoprecipitation followed by sequencing (ChIP-seq), are widely used but have their drawbacks, including high false-positive rates and limited antibody availability, respectively. Several computational footprinting algorithms have been developed to detect TFBSs by investigating chromatin accessibility patterns; however, these also have limitations. We have developed a footprinting method to predict TF footprints in active chromatin elements (TRACE) to improve the prediction of TFBS footprints. TRACE incorporates DNase-seq data and PWMs within a multivariate hidden Markov model (HMM) to detect footprint-like regions with matching motifs. TRACE is an unsupervised method that accurately annotates binding sites for specific TFs automatically with no requirement for pregenerated candidate binding sites or ChIP-seq training data. Compared with published footprinting algorithms, TRACE has the best overall performance with the distinct advantage of targeting multiple motifs in a single model.

Functional effects of variation in transcription factor binding highlight long-range gene regulation by epromoters

Identifying DNA cis-regulatory modules (CRMs) that control the expression of specific genes is crucial for deciphering the logic of transcriptional control. Natural genetic variation can point to the possible gene regulatory function of specific sequences through their allelic associations with gene expression. However, comprehensive identification of causal regulatory sequences in brute-force association testing without incorporating prior knowledge is challenging due to limited statistical power and effects of linkage disequilibrium. Sequence variants affecting transcription factor (TF) binding at CRMs have a strong potential to influence gene regulatory function, which provides a motivation for prioritizing such variants in association testing. Here, we generate an atlas of CRMs showing predicted allelic variation in TF binding affinity in human lymphoblastoid cell lines and test their association with the expression of their putative target genes inferred from Promoter Capture Hi-C and immediate linear proximity. We reveal >1300 CRM TF-binding variants associated with target gene expression, the majority of them undetected with standard association testing. A large proportion of CRMs showing associations with the expression of genes they contact in 3D localize to the promoter regions of other genes, supporting the notion of 'epromoters': dual-action CRMs with promoter and distal enhancer activity.

Evidence of a Conserved Molecular Response to Selection for Increased Brain Size in Primates

The adaptive significance of human brain evolution has been frequently studied through comparisons with other primates. However, the evolution of increased brain size is not restricted to the human lineage but is a general characteristic of primate evolution. Whether or not these independent episodes of increased brain size share a common genetic basis is unclear. We sequenced and de novo assembled the transcriptome from the neocortical tissue of the most highly encephalized nonhuman primate, the tufted capuchin monkey (Cebus apella). Using this novel data set, we conducted a genome-wide analysis of orthologous brain-expressed protein coding genes to identify evidence of conserved gene–phenotype associations and species-specific adaptations during three independent episodes of brain size increase. We identify a greater number of genes associated with either total brain mass or relative brain size across these six species than show species-specific accelerated rates of evolution in individual large-brained lineages. We test the robustness of these associations in an expanded data set of 13 species, through permutation tests and by analyzing how genome-wide patterns of substitution co-vary with brain size. Many of the genes targeted by selection during brain expansion have glutamatergic functions or roles in cell cycle dynamics. We also identify accelerated evolution in a number of individual capuchin genes whose human orthologs are associated with human neuropsychiatric disorders. These findings demonstrate the value of phenotypically informed genome analyses, and suggest at least some aspects of human brain evolution have occurred through conserved gene–phenotype associations. Understanding these commonalities is essential for distinguishing human-specific selection events from general trends in brain evolution.

Evolution of Brain Active Gene Promoters in Human Lineage Towards the Increased Plasticity of Gene Regulation

Adaptability to a variety of environmental conditions is a prominent feature of Homo sapiens. We hypothesize that this feature can be explained by evolutionary changes in gene promoters active in the brain prefrontal cortex leading to a more flexible gene regulation network. The genotype-dependent range of gene expression can be broader in humans than in other higher primates. Thus, we searched for specific signatures of evolutionary changes in promoter architectures of multiple hominid genes, including the genes active in human cortical neurons that may indicate an increase of variability of gene expression rather than just changes in the level of expression, such as downregulation or upregulation of the genes. We performed a whole-genome search for genetic-based alterations that may impact gene regulation "flexibility" in a process of hominids evolution, such as (i) CpG dinucleotide content, (ii) predicted nucleosome-DNA dissociation constant, and (iii) predicted affinities for TATA-binding protein (TBP) in gene promoters. We tested all putative promoter regions across the human genome and especially gene promoters in active chromatin state in neurons of prefrontal cortex, the brain region critical for abstract thinking and social and behavioral adaptation. Our data imply that the origin of modern man has been associated with an increase of flexibility of promoter-driven gene regulation in brain. In contrast, after splitting from the ancestral lineages of H. sapiens, the evolution of ape species is characterized by reduced flexibility of gene promoter functioning, underlying reduced variability of the gene expression.

Natural selection in a population of Drosophila melanogaster explained by changes in gene expression caused by sequence variation in core promoter regions

Background

Understanding the evolutionary forces that influence variation in gene regulatory regions in natural populations is an important challenge for evolutionary biology because natural selection for such variations could promote adaptive phenotypic evolution. Recently, whole-genome sequence analyses have identified regulatory regions subject to natural selection. However, these studies could not identify the relationship between sequence variation in the detected regions and change in gene expression levels. We analyzed sequence variations in core promoter regions, which are critical regions for gene regulation in higher eukaryotes, in a natural population of Drosophila melanogaster, and identified core promoter sequence variations associated with differences in gene expression levels subjected to natural selection.

Results

Among the core promoter regions whose sequence variation could change transcription factor binding sites and explain differences in expression levels, three core promoter regions were detected as candidates associated with purifying selection or selective sweep and seven as candidates associated with balancing selection, excluding the possibility of linkage between these regions and core promoter regions. CHKov1, which confers resistance to the sigma virus and related insecticides, was identified as core promoter regions that has been subject to selective sweep, although it could not be denied that selection for variation in core promoter regions was due to linked single nucleotide polymorphisms in the regulatory region outside core promoter regions. Nucleotide changes in core promoter regions of CHKov1 caused the loss of two basal transcription factor binding sites and acquisition of one transcription factor binding site, resulting in decreased gene expression levels. Of nine core promoter regions regions associated with balancing selection, brat, and CG9044 are associated with neuromuscular junction development, and Nmda1 are associated with learning, behavioral plasticity, and memory. Diversity of neural and behavioral traits may have been maintained by balancing selection.

Conclusions

Our results revealed the evolutionary process occurring by natural selection for differences in gene expression levels caused by sequence variation in core promoter regions in a natural population. The sequences of core promoter regions were diverse even within the population, possibly providing a source for natural selection.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-016-0606-3) contains supplementary material, which is available to authorized users.

Comparative analysis of gene regulatory networks: from network reconstruction to evolution

Regulation of gene expression is central to many biological processes. Although reconstruction of regulatory circuits from genomic data alone is therefore desirable, this remains a major computational challenge. Comparative approaches that examine the conservation and divergence of circuits and their components across strains and species can help reconstruct circuits as well as provide insights into the evolution of gene regulatory processes and their adaptive contribution. In recent years, advances in genomic and computational tools have led to a wealth of methods for such analysis at the sequence, expression, pathway, module, and entire network level. Here, we review computational methods developed to study transcriptional regulatory networks using comparative genomics, from sequence to functional data. We highlight how these methods use evolutionary conservation and divergence to reliably detect regulatory components as well as estimate the extent and rate of divergence. Finally, we discuss the promise and open challenges in linking regulatory divergence to phenotypic divergence and adaptation.

A widespread role of the motif environment in transcription factor binding across diverse protein families

Transcriptional regulation requires the binding of transcription factors (TFs) to short sequence-specific DNA motifs, usually located at the gene regulatory regions. Interestingly, based on a vast amount of data accumulated from genomic assays, it has been shown that only a small fraction of all potential binding sites containing the consensus motif of a given TF actually bind the protein. Recent in vitro binding assays, which exclude the effects of the cellular environment, also demonstrate selective TF binding. An intriguing conjecture is that the surroundings of cognate binding sites have unique characteristics that distinguish them from other sequences containing a similar motif that are not bound by the TF. To test this hypothesis, we conducted a comprehensive analysis of the sequence and DNA shape features surrounding the core-binding sites of 239 and 56 TFs extracted from in vitro HT-SELEX binding assays and in vivo ChIP-seq data, respectively. Comparing the nucleotide content of the regions around the TF-bound sites to the counterpart unbound regions containing the same consensus motifs revealed significant differences that extend far beyond the core-binding site. Specifically, the environment of the bound motifs demonstrated unique sequence compositions, DNA shape features, and overall high similarity to the core-binding motif. Notably, the regions around the binding sites of TFs that belong to the same TF families exhibited similar features, with high agreement between the in vitro and in vivo data sets. We propose that these unique features assist in guiding TFs to their cognate binding sites.

Estimating binding properties of transcription factors from genome-wide binding profiles

The binding of transcription factors (TFs) is essential for gene expression. One important characteristic is the actual occupancy of a putative binding site in the genome. In this study, we propose an analytical model to predict genomic occupancy that incorporates the preferred target sequence of a TF in the form of a position weight matrix (PWM), DNA accessibility data (in the case of eukaryotes), the number of TF molecules expected to be bound specifically to the DNA and a parameter that modulates the specificity of the TF. Given actual occupancy data in the form of ChIP-seq profiles, we backwards inferred copy number and specificity for five Drosophila TFs during early embryonic development: Bicoid, Caudal, Giant, Hunchback and Kruppel. Our results suggest that these TFs display thousands of molecules that are specifically bound to the DNA and that whilst Bicoid and Caudal display a higher specificity, the other three TFs (Giant, Hunchback and Kruppel) display lower specificity in their binding (despite having PWMs with higher information content). This study gives further weight to earlier investigations into TF copy numbers that suggest a significant proportion of molecules are not bound specifically to the DNA.

Homotypic clusters of transcription factor binding sites: A model system for understanding the physical mechanics of gene expression

The organization of binding sites in cis-regulatory elements (CREs) can influence gene expression through a combination of physical mechanisms, ranging from direct interactions between TF molecules to DNA looping and transient chromatin interactions. The study of simple and common building blocks in promoters and other CREs allows us to dissect how all of these mechanisms work together. Many adjacent TF binding sites for the same TF species form homotypic clusters, and these CRE architecture building blocks serve as a prime candidate for understanding interacting transcriptional mechanisms. Homotypic clusters are prevalent in both bacterial and eukaryotic genomes, and are present in both promoters as well as more distal enhancer/silencer elements. Here, we review previous theoretical and experimental studies that show how the complexity (number of binding sites) and spatial organization (distance between sites and overall distance from transcription start sites) of homotypic clusters influence gene expression. In particular, we describe how homotypic clusters modulate the temporal dynamics of TF binding, a mechanism that can affect gene expression, but which has not yet been sufficiently characterized. We propose further experiments on homotypic clusters that would be useful in developing mechanistic models of gene expression.

Physical constraints determine the logic of bacterial promoter architectures

Site-specific transcription factors (TFs) bind to their target sites on the DNA, where they regulate the rate at which genes are transcribed. Bacterial TFs undergo facilitated diffusion (a combination of 3D diffusion around and 1D random walk on the DNA) when searching for their target sites. Using computer simulations of this search process, we show that the organization of the binding sites, in conjunction with TF copy number and binding site affinity, plays an important role in determining not only the steady state of promoter occupancy, but also the order at which TFs bind. These effects can be captured by facilitated diffusion-based models, but not by standard thermodynamics. We show that the spacing of binding sites encodes complex logic, which can be derived from combinations of three basic building blocks: switches, barriers and clusters, whose response alone and in higher orders of organization we characterize in detail. Effective promoter organizations are commonly found in the E. coli genome and are highly conserved between strains. This will allow studies of gene regulation at a previously unprecedented level of detail, where our framework can create testable hypothesis of promoter logic.

Computational approaches to identify functional genetic variants in cancer genomes

The International Cancer Genome Consortium (ICGC) aims to catalog genomic abnormalities in tumors from 50 different cancer types. Genome sequencing reveals hundreds to thousands of somatic mutations in each tumor but only a minority of these drive tumor progression. We present the result of discussions within the ICGC on how to address the challenge of identifying mutations that contribute to oncogenesis, tumor maintenance or response to therapy, and recommend computational techniques to annotate somatic variants and predict their impact on cancer phenotype.

Regulatory versus coding signatures of natural selection in a candidate gene involved in the adaptive divergence of whitefish species pairs (Coregonus spp.)

While gene expression divergence is known to be involved in adaptive phenotypic divergence and speciation, the relative importance of regulatory and structural evolution of genes is poorly understood. A recent next-generation sequencing experiment allowed identifying candidate genes potentially involved in the ongoing speciation of sympatric dwarf and normal lake whitefish (Coregonus clupeaformis), such as cytosolic malate dehydrogenase (MDH1), which showed both significant expression and sequence divergence. The main goal of this study was to investigate into more details the signatures of natural selection in the regulatory and coding sequences of MDH1 in lake whitefish and test for parallelism of these signatures with other coregonine species. Sequencing of the two regions in 118 fish from four sympatric pairs of whitefish and two cisco species revealed a total of 35 single nucleotide polymorphisms (SNPs), with more genetic diversity in European compared to North American coregonine species. While the coding region was found to be under purifying selection, an SNP in the proximal promoter exhibited significant allele frequency divergence in a parallel manner among independent sympatric pairs of North American lake whitefish and European whitefish (C. lavaretus). According to transcription factor binding simulation for 22 regulatory haplotypes of MDH1, putative binding profiles were fairly conserved among species, except for the region around this SNP. Moreover, we found evidence for the role of this SNP in the regulation of MDH1 expression level. Overall, these results provide further evidence for the role of natural selection in gene regulation evolution among whitefish species pairs and suggest its possible link with patterns of phenotypic diversity observed in coregonine species.

Genetic correlates of the evolving primate brain

The tremendous shifts in the size, structure, and function of the brain during primate evolution are ultimately caused by changes at the genetic level. Understanding what these changes are and how they effect the phenotypic changes observed lies at the heart of understanding evolutionary change. This chapter focuses on understanding the genetic basis of primate brain evolution, considering the substrates and mechanisms through which genetic change occurs. It also discusses the implications that our current understandings and tools have for what we have already discovered and where our studies will head in the future. While genetic and genomic studies have identified many regions undergoing positive selection during primate evolution, the findings are certainly not exhaustive and functional relevance remains to be confirmed. Nevertheless, a strong foundation has been built upon which future studies will emerge.

GO-Module: functional synthesis and improved interpretation of Gene Ontology patterns

GO-Module is a web-accessible synthesis and visualization tool developed for end-user biologists to greatly simplify the interpretation of prioritized Gene Ontology (GO) terms. GO-Module radically reduces the complexity of raw GO results into compact biomodules in two distinct ways, by (i) constructing biomodules from significant GO terms based on hierarchical knowledge, and (ii) refining the GO terms in each biomodule to contain only true positive results. Altogether, the features (biomodules) of GO-Module outputs are better organized and on average four times smaller than the input GO terms list (P = 0.0005, n = 16).

AVAILABILITY

http://lussierlab.org/GO-Module.

Changes in selective effects over time facilitate turnover of enhancer sequences

Correct gene expression is often critical and consequently stabilizing selection on expression is widespread. Yet few genes possess highly conserved regulatory DNA, and for the few enhancers that have been carefully characterized, substantial functional reorganization has often occurred. Given that natural selection removes mutations of even very small deleterious effect, how can transcription factor binding evolve so readily when it underlies a conserved phenotype? As a first step toward addressing this question, I combine a computational model for regulatory function that incorporates many aspects of our present biological knowledge with a model for the fitness effects of misexpression. I then use this model to study the evolution of enhancers. Several robust behaviors emerge: First, the selective effects of mutations at a site change dramatically over time due to substitutions elsewhere in the enhancer, and even the overall degree of constraint across the enhancer can change considerably. Second, many of the substitutions responsible for changes in binding occur at sites where previously the mutation would have been strongly deleterious, suggesting that fluctuations in selective effects at a site are important for functional turnover. Third, most substitutions contributing to the repatterning of binding and constraint are effectively neutral, highlighting the importance of genetic drift-even for enhancers underlying conserved phenotypes. These findings have important implications for phylogenetic inference of function and for interpretations of selection coefficients estimated for regulatory DNA.

Promoting the promoter

Recent evolutionary studies clearly indicate that evolution is mainly driven by changes in the complex mechanisms of gene regulation and not solely by polymorphism in protein-encoding genes themselves. After a short description of the cis-regulatory mechanism, we intend in this review to argue that by applying newly available technologies and by merging research areas such as evolutionary and developmental biology, population genetics, ecology and molecular cell biology it is now possible to study evolution in an integrative way. We contend that, by analysing the effects of promoter sequence variation on phenotypic diversity in natural populations, we will soon be able to break the barrier between the study of extant genetic variability and the study of major developmental changes. This will lead to an integrative view of evolution at different scales. Because of their sessile nature and their continuous development, plants must permanently regulate their gene expression to react to their environment, and can, therefore, be considered as a remarkable model for these types of studies.

Comparative genetic approaches to the evolution of human brain and behavior

With advances in genomic technologies, the amount of genetic data available to scientists today is vast. Genomes are now available or planned for 14 different primate species and complete resequencing of numerous human individuals from numerous populations is underway. Moreover, high-throughput deep sequencing is quickly making whole genome efforts within the reach of single laboratories allowing for unprecedented studies. Comparative genetic approaches to the identification of the underlying basis of human brain, behavior, and cognitive ability are moving to the forefront. Two approaches predominate: inter-species divergence comparisons and intra-species polymorphism studies. These methodological differences are useful for different time scales of evolution and necessarily focus on different evolutionary events in the history of primate and hominin evolution. Inter-species divergence is more useful in studying large scale primate, or hominoid, evolution whereas intra-species polymorphism can be more illuminating of recent hominin evolution. These differences in methodological utility also extend to studies of differing genetic substrates; current divergence studies focus primarily on protein evolution whereas polymorphism studies are substrate ambivalent. Some of the issues inherent in these studies can be ameliorated by current sequencing capabilities whereas others remain intractable. New avenues are also being opened that allow for the incorporation of novel substrates and approaches. In the post-genomic era, the study of human evolution, specifically as it relates to the brain, is becoming more complete focusing increasingly on the totality of the system and better conceptualizing the entirety of the genetic changes that have lead to the human phenotype today.

Transcription factor binding variation in the evolution of gene regulation

Transcription factor interactions with DNA are one of the primary mechanisms by which expression is modulated, yet their evolution remains poorly understood. Chromatin immunoprecipitation followed by microarray (ChIP-chip) or sequencing (ChIP-Seq) has revolutionized the study of protein-DNA interactions. However, only recently has attention focused on determining to what extent these regulatory interactions vary between species across entire genomes. A series of recent studies have compared in vivo binding data across a range of evolutionary distances. Binding events diverge rapidly, indicating gene regulation is an evolutionarily flexible process.

Gene promoter evolution targets the center of the human protein interaction network

Assessing the contribution of promoters and coding sequences to gene evolution is an important step toward discovering the major genetic determinants of human evolution. Many specific examples have revealed the evolutionary importance of cis-regulatory regions. However, the relative contribution of regulatory and coding regions to the evolutionary process and whether systemic factors differentially influence their evolution remains unclear. To address these questions, we carried out an analysis at the genome scale to identify signatures of positive selection in human proximal promoters. Next, we examined whether genes with positively selected promoters (Prom⁺ genes) show systemic differences with respect to a set of genes with positively selected protein-coding regions (Cod⁺ genes). We found that the number of genes in each set was not significantly different (8.1% and 8.5%, respectively). Furthermore, a functional analysis showed that, in both cases, positive selection affects almost all biological processes and only a few genes of each group are located in enriched categories, indicating that promoters and coding regions are not evolutionarily specialized with respect to gene function. On the other hand, we show that the topology of the human protein network has a different influence on the molecular evolution of proximal promoters and coding regions. Notably, Prom⁺ genes have an unexpectedly high centrality when compared with a reference distribution (P = 0.008, for Eigenvalue centrality). Moreover, the frequency of Prom⁺ genes increases from the periphery to the center of the protein network (P = 0.02, for the logistic regression coefficient). This means that gene centrality does not constrain the evolution of proximal promoters, unlike the case with coding regions, and further indicates that the evolution of proximal promoters is more efficient in the center of the protein network than in the periphery. These results show that proximal promoters have had a systemic contribution to human evolution by increasing the participation of central genes in the evolutionary process.