Detecting positive selection within genomes: the problem of biased gene conversion

SENCA: A Multilayered Codon Model to Study the Origins and Dynamics of Codon Usage

Gene sequences are the target of evolution operating at different levels, including the nucleotide, codon, and amino acid levels. Disentangling the impact of those different levels on gene sequences requires developing a probabilistic model with three layers. Here we present SENCA (site evolution of nucleotides, codons, and amino acids), a codon substitution model that separately describes 1) nucleotide processes which apply on all sites of a sequence such as the mutational bias, 2) preferences between synonymous codons, and 3) preferences among amino acids. We argue that most synonymous substitutions are not neutral and that SENCA provides more accurate estimates of selection compared with more classical codon sequence models. We study the forces that drive the genomic content evolution, intraspecifically in the core genome of 21 prokaryotes and interspecifically for five Enterobacteria. We retrieve the existence of a universal mutational bias toward AT, and that taking into account selection on synonymous codon usage has consequences on the measurement of selection on nonsynonymous substitutions. We also confirm that codon usage bias is mostly driven by selection on preferred codons. We propose new summary statistics to measure the relative importance of the different evolutionary processes acting on sequences.

Adaptive Protein Evolution in Animals and the Effective Population Size Hypothesis

The rate at which genomes adapt to environmental changes and the prevalence of adaptive processes in molecular evolution are two controversial issues in current evolutionary genetics. Previous attempts to quantify the genome-wide rate of adaptation through amino-acid substitution have revealed a surprising diversity of patterns, with some species (e.g. Drosophila) experiencing a very high adaptive rate, while other (e.g. humans) are dominated by nearly-neutral processes. It has been suggested that this discrepancy reflects between-species differences in effective population size. Published studies, however, were mainly focused on model organisms, and relied on disparate data sets and methodologies, so that an overview of the prevalence of adaptive protein evolution in nature is currently lacking. Here we extend existing estimators of the amino-acid adaptive rate by explicitly modelling the effect of favourable mutations on non-synonymous polymorphism patterns, and we apply these methods to a newly-built, homogeneous data set of 44 non-model animal species pairs. Data analysis uncovers a major contribution of adaptive evolution to the amino-acid substitution process across all major metazoan phyla—with the notable exception of humans and primates. The proportion of adaptive amino-acid substitution is found to be positively correlated to species effective population size. This relationship, however, appears to be primarily driven by a decreased rate of nearly-neutral amino-acid substitution because of more efficient purifying selection in large populations. Our results reveal that adaptive processes dominate the evolution of proteins in most animal species, but do not corroborate the hypothesis that adaptive substitutions accumulate at a faster rate in large populations. Implications regarding the factors influencing the rate of adaptive evolution and positive selection detection in humans vs. other organisms are discussed.

The rate at which species adapt to environmental changes is a controversial topic. The theory predicts that adaptation is easier in large than in small populations, and the genomic studies of model organisms have revealed a much higher adaptive rate in large population-sized flies than in small population-sized humans and apes. Here we build and analyse a large data set of protein-coding sequences made of thousands of genes in 44 pairs of species from various groups of animals including insects, molluscs, annelids, echinoderms, reptiles, birds, and mammals. Extending and improving existing data analysis methods, we show that adaptation is a major process in protein evolution across all phyla of animals: the proportion of amino-acid substitutions that occurred adaptively is above 50% in a majority of species, and reaches up to 90%. Our analysis does not confirm that population size, here approached through species genetic diversity and ecological traits, does influence the rate of adaptive molecular evolution, but points to human and apes as a special case, compared to other animals, in terms of adaptive genomic processes.

Are Synonymous Sites in Primates and Rodents Functionally Constrained?

It has been claimed that synonymous sites in mammals are under selective constraint. Furthermore, in many studies the selective constraint at such sites in primates was claimed to be more stringent than that in rodents. Given the larger effective population sizes in rodents than in primates, the theoretical expectation is that selection in rodents would be more effective than that in primates. To resolve this contradiction between expectations and observations, we used processed pseudogenes as a model for strict neutral evolution, and estimated selective constraint on synonymous sites using the rate of substitution at pseudosynonymous and pseudononsynonymous sites in pseudogenes as the neutral expectation. After controlling for the effects of GC content, our results were similar to those from previous studies, i.e., synonymous sites in primates exhibited evidence for higher selective constraint that those in rodents. Specifically, our results indicated that in primates up to 24% of synonymous sites could be under purifying selection, while in rodents synonymous sites evolved neutrally. To further control for shifts in GC content, we estimated selective constraint at fourfold degenerate sites using a maximum parsimony approach. This allowed us to estimate selective constraint using mutational patterns that cause a shift in GC content (GT ↔ TG, CT ↔ TC, GA ↔ AG, and CA ↔ AC) and ones that do not (AT ↔ TA and CG ↔ GC). Using this approach, we found that synonymous sites evolve neutrally in both primates and rodents. Apparent deviations from neutrality were caused by a higher rate of C → A and C → T mutations in pseudogenes. Such differences are most likely caused by the shift in GC content experienced by pseudogenes. We conclude that previous estimates according to which 20-40% of synonymous sites in primates were under selective constraint were most likely artifacts of the biased pattern of mutation.

Evolutionary Rate Heterogeneity of Primary and Secondary Metabolic Pathway Genes in Arabidopsis thaliana

Primary metabolism is essential to plants for growth and development, and secondary metabolism helps plants to interact with the environment. Many plant metabolites are industrially important. These metabolites are produced by plants through complex metabolic pathways. Lack of knowledge about these pathways is hindering the successful breeding practices for these metabolites. For a better knowledge of the metabolism in plants as a whole, evolutionary rate variation of primary and secondary metabolic pathway genes is a prerequisite. In this study, evolutionary rate variation of primary and secondary metabolic pathway genes has been analyzed in the model plant Arabidopsis thaliana. Primary metabolic pathway genes were found to be more conserved than secondary metabolic pathway genes. Several factors such as gene structure, expression level, tissue specificity, multifunctionality, and domain number are the key factors behind this evolutionary rate variation. This study will help to better understand the evolutionary dynamics of plant metabolism.

Recombination Rate Variation Modulates Gene Sequence Evolution Mainly via GC-Biased Gene Conversion, Not Hill-Robertson Interference, in an Avian System

The ratio of nonsynonymous to synonymous substitution rates (ω) is often used to measure the strength of natural selection. However, ω may be influenced by linkage among different targets of selection, that is, Hill–Robertson interference (HRI), which reduces the efficacy of selection. Recombination modulates the extent of HRI but may also affect ω by means of GC-biased gene conversion (gBGC), a process leading to a preferential fixation of G:C (“strong,” S) over A:T (“weak,” W) alleles. As HRI and gBGC can have opposing effects on ω, it is essential to understand their relative impact to make proper inferences of ω. We used a model that separately estimated S-to-S, S-to-W, W-to-S, and W-to-W substitution rates in 8,423 avian genes in the Ficedula flycatcher lineage. We found that the W-to-S substitution rate was positively, and the S-to-W rate negatively, correlated with recombination rate, in accordance with gBGC but not predicted by HRI. The W-to-S rate further showed the strongest impact on both d_N and d_S. However, since the effects were stronger at 4-fold than at 0-fold degenerated sites, likely because the GC content of these sites is farther away from its equilibrium, ω slightly decreases with increasing recombination rate, which could falsely be interpreted as a consequence of HRI. We corroborated this hypothesis analytically and demonstrate that under particular conditions, ω can decrease with increasing recombination rate. Analyses of the site-frequency spectrum showed that W-to-S mutations were skewed toward high, and S-to-W mutations toward low, frequencies, consistent with a prevalent gBGC-driven fixation bias.

Genomic approaches to studying human-specific developmental traits

Changes in developmental regulatory programs drive both disease and phenotypic differences among species. Linking human-specific traits to alterations in development is challenging, because we have lacked the tools to assay and manipulate regulatory networks in human and primate embryonic cells. This field was transformed by the sequencing of hundreds of genomes – human and non-human – that can be compared to discover the regulatory machinery of genes involved in human development. This approach has identified thousands of human-specific genome alterations in developmental genes and their regulatory regions. With recent advances in stem cell techniques, genome engineering, and genomics, we can now test these sequences for effects on developmental gene regulation and downstream phenotypes in human cells and tissues.

Kr/Kc but not dN/dS correlates positively with body mass in birds, raising implications for inferring lineage-specific selection

Background

The ratio of the rates of non-synonymous and synonymous substitution (d_N/d_S) is commonly used to estimate selection in coding sequences. It is often suggested that, all else being equal, d_N/d_S should be lower in populations with large effective size (N_e) due to increased efficacy of purifying selection. As N_e is difficult to measure directly, life history traits such as body mass, which is typically negatively associated with population size, have commonly been used as proxies in empirical tests of this hypothesis. However, evidence of whether the expected positive correlation between body mass and d_N/d_S is consistently observed is conflicting.

Results

Employing whole genome sequence data from 48 avian species, we assess the relationship between rates of molecular evolution and life history in birds. We find a negative correlation between d_N/d_S and body mass, contrary to nearly neutral expectation. This raises the question whether the correlation might be a method artefact. We therefore in turn consider non-stationary base composition, divergence time and saturation as possible explanations, but find no clear patterns. However, in striking contrast to d_N/d_S, the ratio of radical to conservative amino acid substitutions (K_r/K_c) correlates positively with body mass.

Conclusions

Our results in principle accord with the notion that non-synonymous substitutions causing radical amino acid changes are more efficiently removed by selection in large populations, consistent with nearly neutral theory. These findings have implications for the use of d_N/d_S and suggest that caution is warranted when drawing conclusions about lineage-specific modes of protein evolution using this metric.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-014-0542-8) contains supplementary material, which is available to authorized users.

Quantification of GC-biased gene conversion in the human genome

Much evidence indicates that GC-biased gene conversion (gBGC) has a major impact on the evolution of mammalian genomes. However, a detailed quantification of the process is still lacking. The strength of gBGC can be measured from the analysis of derived allele frequency spectra (DAF), but this approach is sensitive to a number of confounding factors. In particular, we show by simulations that the inference is pervasively affected by polymorphism polarization errors and by spatial heterogeneity in gBGC strength. We propose a new general method to quantify gBGC from DAF spectra, incorporating polarization errors, taking spatial heterogeneity into account, and jointly estimating mutation bias. Applying it to human polymorphism data from the 1000 Genomes Project, we show that the strength of gBGC does not differ between hypermutable CpG sites and non-CpG sites, suggesting that in humans gBGC is not caused by the base-excision repair machinery. Genome-wide, the intensity of gBGC is in the nearly neutral area. However, given that recombination occurs primarily within recombination hotspots, 1%–2% of the human genome is subject to strong gBGC. On average, gBGC is stronger in African than in non-African populations, reflecting differences in effective population sizes. However, due to more heterogeneous recombination landscapes, the fraction of the genome affected by strong gBGC is larger in non-African than in African populations. Given that the location of recombination hotspots evolves very rapidly, our analysis predicts that, in the long term, a large fraction of the genome is affected by short episodes of strong gBGC.

Molecular Evolution of Freshwater Snails with Contrasting Mating Systems

Because mating systems affect population genetics and ecology, they are expected to impact the molecular evolution of species. Self-fertilizing species experience reduced effective population size, recombination rates, and heterozygosity, which in turn should decrease the efficacy of natural selection, both adaptive and purifying, and the strength of meiotic drive processes such as GC-biased gene conversion. The empirical evidence is only partly congruent with these predictions, depending on the analyzed species, some, but not all, of the expected effects have been observed. One possible reason is that self-fertilization is an evolutionary dead-end, so that most current selfers recently evolved self-fertilization, and their genome has not yet been strongly impacted by selfing. Here, we investigate the molecular evolution of two groups of freshwater snails in which mating systems have likely been stable for several millions of years. Analyzing coding sequence polymorphism, divergence, and expression levels, we report a strongly reduced genetic diversity, decreased efficacy of purifying selection, slower rate of adaptive evolution, and weakened codon usage bias/GC-biased gene conversion in the selfer Galba compared with the outcrosser Physa, in full agreement with theoretical expectations. Our results demonstrate that self-fertilization, when effective in the long run, is a major driver of population genomic and molecular evolutionary processes. Despite the genomic effects of selfing, Galba truncatula seems to escape the demographic consequences of the genetic load. We suggest that the particular ecology of the species may buffer the negative consequences of selfing, shedding new light on the dead-end hypothesis.

Highly variable recombinational landscape modulates efficacy of natural selection in birds

Determining the rate of protein evolution and identifying the causes of its variation across the genome are powerful ways to understand forces that are important for genome evolution. By using a multitissue transcriptome data set from great tit (Parus major), we analyzed patterns of molecular evolution between two passerine birds, great tit and zebra finch (Taeniopygia guttata), using the chicken genome (Gallus gallus) as an outgroup. We investigated whether a special feature of avian genomes, the highly variable recombinational landscape, modulates the efficacy of natural selection through the effects of Hill-Robertson interference, which predicts that selection should be more effective in removing deleterious mutations and incorporating beneficial mutations in high-recombination regions than in low-recombination regions. In agreement with these predictions, genes located in low-recombination regions tend to have a high proportion of neutrally evolving sites and relaxed selective constraint on sites subject to purifying selection, whereas genes that show strong support for past episodes of positive selection appear disproportionally in high-recombination regions. There is also evidence that genes located in high-recombination regions tend to have higher gene expression specificity than those located in low-recombination regions. Furthermore, more compact genes (i.e., those with fewer/shorter introns or shorter proteins) evolve faster than less compact ones. In sum, our results demonstrate that transcriptome sequencing is a powerful method to answer fundamental questions about genome evolution in nonmodel organisms.

The relationship between dN/dS and scaled selection coefficients

Numerous computational methods exist to assess the mode and strength of natural selection in protein-coding sequences, yet how distinct methods relate to one another remains largely unknown. Here, we elucidate the relationship between two widely used phylogenetic modeling frameworks: dN/dS models and mutation-selection (MutSel) models. We derive a mathematical relationship between dN/dS and scaled selection coefficients, the focal parameters of MutSel models, and use this relationship to gain deeper insight into the behaviors, limitations, and applicabilities of these two modeling frameworks. We prove that, if all synonymous changes are neutral, standard MutSel models correspond to dN/dS ≤ 1. However, if synonymous codons differ in fitness, dN/dS can take on arbitrarily high values even if all selection is purifying. Thus, the MutSel modeling framework cannot necessarily accommodate positive, diversifying selection, while dN/dS cannot distinguish between purifying selection on synonymous codons and positive selection on amino acids. We further propose a new benchmarking strategy of dN/dS inferences against MutSel simulations and demonstrate that the widely used Goldman-Yang-style dN/dS models yield substantially biased dN/dS estimates on realistic sequence data. In contrast, the less frequently used Muse-Gaut-style models display much less bias. Strikingly, the least-biased and most precise dN/dS estimates are never found in the models with the best fit to the data, measured through both AIC and BIC scores. Thus, selecting models based on goodness-of-fit criteria can yield poor parameter estimates if the models considered do not precisely correspond to the underlying mechanism that generated the data. In conclusion, establishing mathematical links among modeling frameworks represents a novel, powerful strategy to pinpoint previously unrecognized model limitations and strengths.

GC-Content evolution in bacterial genomes: the biased gene conversion hypothesis expands

The characterization of functional elements in genomes relies on the identification of the footprints of natural selection. In this quest, taking into account neutral evolutionary processes such as mutation and genetic drift is crucial because these forces can generate patterns that may obscure or mimic signatures of selection. In mammals, and probably in many eukaryotes, another such confounding factor called GC-Biased Gene Conversion (gBGC) has been documented. This mechanism generates patterns identical to what is expected under selection for higher GC-content, specifically in highly recombining genomic regions. Recent results have suggested that a mysterious selective force favouring higher GC-content exists in Bacteria but the possibility that it could be gBGC has been excluded. Here, we show that gBGC is probably at work in most if not all bacterial species. First we find a consistent positive relationship between the GC-content of a gene and evidence of intra-genic recombination throughout a broad spectrum of bacterial clades. Second, we show that the evolutionary force responsible for this pattern is acting independently from selection on codon usage, and could potentially interfere with selection in favor of optimal AU-ending codons. A comparison with data from human populations shows that the intensity of gBGC in Bacteria is comparable to what has been reported in mammals. We propose that gBGC is not restricted to sexual Eukaryotes but also widespread among Bacteria and could therefore be an ancestral feature of cellular organisms. We argue that if gBGC occurs in bacteria, it can account for previously unexplained observations, such as the apparent non-equilibrium of base substitution patterns and the heterogeneity of gene composition within bacterial genomes. Because gBGC produces patterns similar to positive selection, it is essential to take this process into account when studying the evolutionary forces at work in bacterial genomes.

Classical population genetics models indicate that the efficiency of selection, and hence adaptation, depends on a number of non-selective factors, such as the size of a population or the intensity of recombination. In the last 10 years, evidence has accumulated that another mechanism called GC-Biased Gene Conversion (gBGC) can interfere with selection and even mimic its effects. This phenomenon, which arises from a particularity of the recombination machinery, was first thought to be restricted to sexual eukaryotic organisms. Here, we show that this mechanism probably exists in Bacteria and has a strong impact on their genome evolution. This discovery not only explains many previously unconnected features of bacterial genome evolution, but also highlights the importance of non-adaptive evolutionary processes in Bacteria.

Germline methylation patterns determine the distribution of recombination events in the dog genome

The positive-regulatory domain containing nine gene, PRDM9, which strongly associates with the location of recombination events in several vertebrates, is inferred to be inactive in the dog genome. Here, we address several questions regarding the control of recombination and its influence on genome evolution in dogs. First, we address whether the association between CpG islands (CGIs) and recombination hotspots is generated by lack of methylation, GC-biased gene conversion (gBGC), or both. Using a genome-wide dog single nucleotide polymorphism data set and comparisons of the dog genome with related species, we show that recombination-associated CGIs have low CpG mutation rates, and that CpG mutation rate is negatively correlated with recombination rate genome wide, indicating that nonmethylation attracts the recombination machinery. We next use a neighbor-dependent model of nucleotide substitution to disentangle the effects of CpG mutability and gBGC and analyze the effects that loss of PRDM9 has on these rates. We infer that methylation patterns have been stable during canid genome evolution, but that dog CGIs have experienced a drastic increase in substitution rate due to gBGC, consistent with increased levels of recombination in these regions. We also show that gBGC is likely to have generated many new CGIs in the dog genome, but these mostly occur away from genes, whereas the number of CGIs in gene promoter regions has not increased greatly in recent evolutionary history. Recombination has a major impact on the distribution of CGIs that are detected in the dog genome due to the interaction between methylation and gBGC. The results indicate that germline methylation patterns are the main determinant of recombination rates in the absence of PRDM9.

Biased gene conversion and GC-content evolution in the coding sequences of reptiles and vertebrates

Mammalian and avian genomes are characterized by a substantial spatial heterogeneity of GC-content, which is often interpreted as reflecting the effect of local GC-biased gene conversion (gBGC), a meiotic repair bias that favors G and C over A and T alleles in high-recombining genomic regions. Surprisingly, the first fully sequenced nonavian sauropsid (i.e., reptile), the green anole Anolis carolinensis, revealed a highly homogeneous genomic GC-content landscape, suggesting the possibility that gBGC might not be at work in this lineage. Here, we analyze GC-content evolution at third-codon positions (GC3) in 44 vertebrates species, including eight newly sequenced transcriptomes, with a specific focus on nonavian sauropsids. We report that reptiles, including the green anole, have a genome-wide distribution of GC3 similar to that of mammals and birds, and we infer a strong GC3-heterogeneity to be already present in the tetrapod ancestor. We further show that the dynamic of coding sequence GC-content is largely governed by karyotypic features in vertebrates, notably in the green anole, in agreement with the gBGC hypothesis. The discrepancy between third-codon positions and noncoding DNA regarding GC-content dynamics in the green anole could not be explained by the activity of transposable elements or selection on codon usage. This analysis highlights the unique value of third-codon positions as an insertion/deletion-free marker of nucleotide substitution biases that ultimately affect the evolution of proteins.

Biased gene conversion skews allele frequencies in human populations, increasing the disease burden of recessive alleles

Gene conversion results in the nonreciprocal transfer of genetic information between two recombining sequences, and there is evidence that this process is biased toward G and C alleles. However, the strength of GC-biased gene conversion (gBGC) in human populations and its effects on hereditary disease have yet to be assessed on a genomic scale. Using high-coverage whole-genome sequences of African hunter-gatherers, agricultural populations, and primate outgroups, we quantified the effects of GC-biased gene conversion on population genomic data sets. We find that genetic distances (FST and population branch statistics) are modified by gBGC. In addition, the site frequency spectrum is left-shifted when ancestral alleles are favored by gBGC and right-shifted when derived alleles are favored by gBGC. Allele frequency shifts due to gBGC mimic the effects of natural selection. As expected, these effects are strongest in high-recombination regions of the human genome. By comparing the relative rates of fixation of unbiased and biased sites, the strength of gene conversion was estimated to be on the order of Nb ≈ 0.05 to 0.09. We also find that derived alleles favored by gBGC are much more likely to be homozygous than derived alleles at unbiased SNPs (+42.2% to 62.8%). This results in a curse of the converted, whereby gBGC causes substantial increases in hereditary disease risks. Taken together, our findings reveal that GC-biased gene conversion has important population genetic and public health implications.

Independent stratum formation on the avian sex chromosomes reveals inter-chromosomal gene conversion and predominance of purifying selection on the W chromosome

We used a comparative approach spanning three species and 90 million years to study the evolutionary history of the avian sex chromosomes. Using whole transcriptomes, we assembled the largest cross-species dataset of W-linked coding content to date. Our results show that recombination suppression in large portions of the avian sex chromosomes has evolved independently, and that long-term sex chromosome divergence is consistent with repeated and independent inversions spreading progressively to restrict recombination. In contrast, over short-term periods we observe heterogeneous and locus-specific divergence. We also uncover four instances of gene conversion between both highly diverged and recently evolved gametologs, suggesting a complex mosaic of recombination suppression across the sex chromosomes. Lastly, evidence from 16 gametologs reveal that the W chromosome is evolving with a significant contribution of purifying selection, consistent with previous findings that W-linked genes play an important role in encoding sex-specific fitness.

Exploring the genesis and functions of Human Accelerated Regions sheds light on their role in human evolution

Human accelerated regions (HARs) are DNA sequences that changed very little throughout mammalian evolution, but then experienced a burst of changes in humans since divergence from chimpanzees. This unexpected evolutionary signature is suggestive of deeply conserved function that was lost or changed on the human lineage. Since their discovery, the actual roles of HARs in human evolution have remained somewhat elusive, due to their being almost exclusively non-coding sequences with no annotation. Ongoing research is beginning to crack this problem by leveraging new genome sequences, functional genomics data, computational approaches, and genetic assays to reveal that many HARs are developmental gene regulatory elements and RNA genes, most of which evolved their uniquely human mutations through positive selection before divergence of archaic hominins and diversification of modern humans.

Ascertaining regions affected by GC-biased gene conversion through weak-to-strong mutational hotspots

A major objective for evolutionary biology is to identify regions affected by positive selection. High dN/dS values for proteins and accelerated lineage-specific substitution rates for non-coding regions are considered classic signatures of positive selection. However, these could also be the result of non-adaptive phenomena, such as GC-biased gene conversion (gBGC), which favors the fixation of strong (C/G) over weak (A/T) nucleotides. Recent estimates indicate that gBGC affected up to 20% of regions with signatures of positive selection. Here we evaluate the impact of gBGC through its molecular signature of weak-to-strong mutational hotspots. We implemented specific modifications to the test proposed by Tang and Lewontin (1999) for identifying regions of differential variability and applied it to regions previously investigated for the influence of gBGC. While we found significant agreement with previous reports, our results suggest a smaller influence of gBGC than previously estimated, warranting further development of methods for its detection.

dbPSHP: a database of recent positive selection across human populations

The dbPSHP database (http://jjwanglab.org/dbpshp) aims to help researchers to efficiently identify, validate and visualize putative positively selected loci in human evolution and further discover the mechanism governing these natural selections. Recent evolution of human populations at the genomic level reflects the adaptations to the living environments, including climate change and availability and stability of nutrients. Many genetic regions under positive selection have been identified, which assist us to understand how natural selection has shaped population differences. Here, we manually collect recent positive selections in different human populations, consisting of 15,472 loci from 132 publications. We further compiled a database that used 15 statistical terms of different evolutionary attributes for single nucleotide variant sites from the HapMap 3 and 1000 Genomes Project to identify putative regions under positive selection. These attributes include variant allele/genotype properties, variant heterozygosity, within population diversity, long-range haplotypes, pairwise population differentiation and evolutionary conservation. We also provide interactive pages for visualization and annotation of different selective signals. The database is freely available to the public and will be frequently updated.

Population Genomics of Human Adaptation

Recent advances in genotyping technologies have facilitated genome-wide scans for natural selection. Identification of targets of natural selection will shed light on processes of human adaptation and evolution and could be important for identifying variation that influences both normal human phenotypic variation as well as disease susceptibility. Here we focus on studies of natural selection in modern humans who originated ~200,000 years go in Africa and migrated across the globe ~50,000 - 100,000 years ago. Movement into new environments, as well as changes in culture and technology including plant and animal domestication, resulted in local adaptation to diverse environments. We summarize statistical approaches for detecting targets of natural selection and for distinguishing the effects of demographic history from natural selection. On a genome-wide scale, immune-related genes appear to be major targets of positive selection. Genes associated with reproduction and fertility also appear to be fast evolving. Additional examples of recent human adaptation include genes associated with lactase persistence, eccrine glands, and response to hypoxia. Lastly, we emphasize the need to supplement scans of selection with functional studies to demonstrate the physiologic impact of candidate loci.

Positive selection in bone morphogenetic protein 15 targets a natural mutation associated with primary ovarian insufficiency in human

Bone Morphogenetic Protein 15 (BMP15) is a TGFβ-like oocyte-derived growth factor involved in ovarian folliculogenesis as a critical regulator of many granulosa cell processes. Alterations of the BMP15 gene have been found associated with different ovarian phenotypic effects depending on the species, from sterility to increased prolificacy in sheep, slight subfertility in mouse or associated with primary ovarian insufficiency (POI) in women. To investigate the evolving role of BMP15, a phylogenetic analysis of this particular TGFβ family member was performed. A maximum likelihood phylogenetic tree of several TGFβ/BMP family members expressed by the ovary showed that BMP15 has a very strong divergence and a rapid evolution compared to others. Moreover, among 24 mammalian species, we detected signals of positive selection in the hominidae clade corresponding to F146, L189 and Y235 residues in human BMP15. The biological importance of these residues was tested functionally after site directed-mutagenesis in a COV434 cells luciferase assay. By replacing the positively selected amino acid either by alanine or the most represented residue in other studied species, only L189A, Y235A and Y235C mutants showed a significant increase of BMP15 signaling when compared to wild type. Additionally, the Y235C mutant was more potent than wild type in inhibiting progesterone secretion of ovine granulosa cells in primary culture. Interestingly, the Y235C mutation was previously identified in association with POI in women. In conclusion, this study evidences that the BMP15 gene has evolved faster than other members of the TGFß family and was submitted to a positive selection pressure in the hominidae clade. Some residues under positive selection are of great importance for the normal function of the protein and thus for female fertility. Y235 represents a critical residue in the determination of BMP15 biological activity, thus indirectly confirming its role in the onset of POI in women.

A model-based analysis of GC-biased gene conversion in the human and chimpanzee genomes

GC-biased gene conversion (gBGC) is a recombination-associated process that favors the fixation of G/C alleles over A/T alleles. In mammals, gBGC is hypothesized to contribute to variation in GC content, rapidly evolving sequences, and the fixation of deleterious mutations, but its prevalence and general functional consequences remain poorly understood. gBGC is difficult to incorporate into models of molecular evolution and so far has primarily been studied using summary statistics from genomic comparisons. Here, we introduce a new probabilistic model that captures the joint effects of natural selection and gBGC on nucleotide substitution patterns, while allowing for correlations along the genome in these effects. We implemented our model in a computer program, called phastBias, that can accurately detect gBGC tracts about 1 kilobase or longer in simulated sequence alignments. When applied to real primate genome sequences, phastBias predicts gBGC tracts that cover roughly 0.3% of the human and chimpanzee genomes and account for 1.2% of human-chimpanzee nucleotide differences. These tracts fall in clusters, particularly in subtelomeric regions; they are enriched for recombination hotspots and fast-evolving sequences; and they display an ongoing fixation preference for G and C alleles. They are also significantly enriched for disease-associated polymorphisms, suggesting that they contribute to the fixation of deleterious alleles. The gBGC tracts provide a unique window into historical recombination processes along the human and chimpanzee lineages. They supply additional evidence of long-term conservation of megabase-scale recombination rates accompanied by rapid turnover of hotspots. Together, these findings shed new light on the evolutionary, functional, and disease implications of gBGC. The phastBias program and our predicted tracts are freely available.

Interpreting patterns of DNA sequence variation in the genomes of closely related species is critically important for understanding the causes and functional effects of nucleotide substitutions. Classical models describe patterns of substitution in terms of the fundamental forces of mutation, recombination, neutral drift, and natural selection. However, an entirely separate force, called GC-biased gene conversion (gBGC), also appears to have an important influence on substitution patterns in many species. gBGC is a recombination-associated evolutionary process that favors the fixation of strong (G/C) over weak (A/T) alleles. In mammals, gBGC is thought to promote variation in GC content, rapidly evolving sequences, and the fixation of deleterious mutations. However, its genome-wide influence remains poorly understood, in part because, it is difficult to incorporate gBGC into statistical models of evolution. In this paper, we describe a new evolutionary model that jointly describes the effects of selection and gBGC and apply it to the human and chimpanzee genomes. Our genome-wide predictions of gBGC tracts indicate that gBGC has been an important force in recent human evolution. Our publicly available computer program, called phastBias, and our genome-wide predictions will enable other researchers to consider gBGC in their analyses.

Linking great apes genome evolution across time scales using polymorphism-aware phylogenetic models

The genomes of related species contain valuable information on the history of the considered taxa. Great apes in particular exhibit variation of evolutionary patterns along their genomes. However, the great ape data also bring new challenges, such as the presence of incomplete lineage sorting and ancestral shared polymorphisms. Previous methods for genome-scale analysis are restricted to very few individuals or cannot disentangle the contribution of mutation rates and fixation biases. This represents a limitation both for the understanding of these forces as well as for the detection of regions affected by selection. Here, we present a new model designed to estimate mutation rates and fixation biases from genetic variation within and between species. We relax the assumption of instantaneous substitutions, modeling substitutions as mutational events followed by a gradual fixation. Hence, we straightforwardly account for shared ancestral polymorphisms and incomplete lineage sorting. We analyze genome-wide synonymous site alignments of human, chimpanzee, and two orangutan species. From each taxon, we include data from several individuals. We estimate mutation rates and GC-biased gene conversion intensity. We find that both mutation rates and biased gene conversion vary with GC content. We also find lineage-specific differences, with weaker fixation biases in orangutan species, suggesting a reduced historical effective population size. Finally, our results are consistent with directional selection acting on coding sequences in relation to exonic splicing enhancers.

The branch-site test of positive selection is surprisingly robust but lacks power under synonymous substitution saturation and variation in GC

Positive selection is widely estimated from protein coding sequence alignments by the nonsynonymous-to-synonymous ratio ω. Increasingly elaborate codon models are used in a likelihood framework for this estimation. Although there is widespread concern about the robustness of the estimation of the ω ratio, more efforts are needed to estimate this robustness, especially in the context of complex models. Here, we focused on the branch-site codon model. We investigated its robustness on a large set of simulated data. First, we investigated the impact of sequence divergence. We found evidence of underestimation of the synonymous substitution rate for values as small as 0.5, with a slight increase in false positives for the branch-site test. When dS increases further, underestimation of dS is worse, but false positives decrease. Interestingly, the detection of true positives follows a similar distribution, with a maximum for intermediary values of dS. Thus, high dS is more of a concern for a loss of power (false negatives) than for false positives of the test. Second, we investigated the impact of GC content. We showed that there is no significant difference of false positives between high GC (up to ∼80%) and low GC (∼30%) genes. Moreover, neither shifts of GC content on a specific branch nor major shifts in GC along the gene sequence generate many false positives. Our results confirm that the branch-site is a very conservative test.

GC-biased gene conversion in yeast is specifically associated with crossovers: molecular mechanisms and evolutionary significance

GC-biased gene conversion (gBGC) is a process associated with recombination that favors the transmission of GC alleles over AT alleles during meiosis. gBGC plays a major role in genome evolution in many eukaryotes. However, the molecular mechanisms of gBGC are still unknown. Different steps of the recombination process could potentially cause gBGC: the formation of double-strand breaks (DSBs), the invasion of the homologous or sister chromatid, and the repair of mismatches in heteroduplexes. To investigate these models, we analyzed a genome-wide data set of crossovers (COs) and noncrossovers (NCOs) in Saccharomyces cerevisiae. We demonstrate that the overtransmission of GC alleles is specific to COs and that it occurs among conversion tracts in which all alleles are converted from the same donor haplotype. Thus, gBGC results from a process that leads to long-patch repair. We show that gBGC is associated with longer tracts and that it is driven by the nature (GC or AT) of the alleles located at the extremities of the tract. These observations invalidate the hypotheses that gBGC is due to the base excision repair machinery or to a bias in DSB formation and suggest that in S. cerevisiae, gBGC is caused by the mismatch repair (MMR) system. We propose that the presence of nicks on both DNA strands during CO resolution could be the cause of the bias in MMR activity. Our observations are consistent with the hypothesis that gBGC is a nonadaptive consequence of a selective pressure to limit the mutation rate in mitotic cells.

Bidirectional promoters as important drivers for the emergence of species-specific transcripts

The diversification of gene functions has been largely attributed to the process of gene duplication. Novel examples of genes originating from previously untranscribed regions have been recently described without regard to a unifying functional mechanism for their emergence. Here we propose a model mechanism that could generate a large number of lineage-specific novel transcripts in vertebrates through the activation of bidirectional transcription from unidirectional promoters. We examined this model in silico using human transcriptomic and genomic data and identified evidence consistent with the emergence of more than 1,000 primate-specific transcripts. These are transcripts with low coding potential and virtually no functional annotation. They initiate at less than 1 kb upstream of an oppositely transcribed conserved protein coding gene, in agreement with the generally accepted definition of bidirectional promoters. We found that the genomic regions upstream of ancestral promoters, where the novel transcripts in our dataset reside, are characterized by preferential accumulation of transposable elements. This enhances the sequence diversity of regions located upstream of ancestral promoters, further highlighting their evolutionary importance for the emergence of transcriptional novelties. By applying a newly developed test for positive selection to transposable element-derived fragments in our set of novel transcripts, we found evidence of adaptive evolution in the human lineage in nearly 3% of the novel transcripts in our dataset. These findings indicate that at least some novel transcripts could become functionally relevant, and thus highlight the evolutionary importance of promoters, through their capacity for bidirectional transcription, for the emergence of novel genes.

Sequencing of the needle transcriptome from Norway spruce (Picea abies Karst L.) reveals lower substitution rates, but similar selective constraints in gymnosperms and angiosperms

BACKGROUND

A detailed knowledge about spatial and temporal gene expression is important for understanding both the function of genes and their evolution. For the vast majority of species, transcriptomes are still largely uncharacterized and even in those where substantial information is available it is often in the form of partially sequenced transcriptomes. With the development of next generation sequencing, a single experiment can now simultaneously identify the transcribed part of a species genome and estimate levels of gene expression.

RESULTS

mRNA from actively growing needles of Norway spruce (Picea abies) was sequenced using next generation sequencing technology. In total, close to 70 million fragments with a length of 76 bp were sequenced resulting in 5 Gbp of raw data. A de novo assembly of these reads, together with publicly available expressed sequence tag (EST) data from Norway spruce, was used to create a reference transcriptome. Of the 38,419 PUTs (putative unique transcripts) longer than 150 bp in this reference assembly, 83.5% show similarity to ESTs from other spruce species and of the remaining PUTs, 3,704 show similarity to protein sequences from other plant species, leaving 4,167 PUTs with limited similarity to currently available plant proteins. By predicting coding frames and comparing not only the Norway spruce PUTs, but also PUTs from the close relatives Picea glauca and Picea sitchensis to both Pinus taeda and Taxus mairei, we obtained estimates of synonymous and non-synonymous divergence among conifer species. In addition, we detected close to 15,000 SNPs of high quality and estimated gene expression differences between samples collected under dark and light conditions.

CONCLUSIONS

Our study yielded a large number of single nucleotide polymorphisms as well as estimates of gene expression on transcriptome scale. In agreement with a recent study we find that the synonymous substitution rate per year (0.6 × 10-09 and 1.1 × 10-09) is an order of magnitude smaller than values reported for angiosperm herbs. However, if one takes generation time into account, most of this difference disappears. The estimates of the dN/dS ratio (non-synonymous over synonymous divergence) reported here are in general much lower than 1 and only a few genes showed a ratio larger than 1.

Phylogenetic patterns of GC-biased gene conversion in placental mammals and the evolutionary dynamics of recombination landscapes

GC-biased gene conversion (gBGC) is a major evolutionary force shaping genomic nucleotide landscapes, distorting the estimation of the strength of selection, and having potentially deleterious effects on genome-wide fitness. Yet, a global quantitative picture, at large evolutionary scale, of the relative strength of gBGC compared with selection and random drift is still lacking. Furthermore, owing to its dependence on the local recombination rate, gBGC results in modulations of the substitution patterns along genomes and across time which, if correctly interpreted, may yield quantitative insights into the long-term evolutionary dynamics of recombination landscapes. Deriving a model of the substitution process at putatively neutral nucleotide positions from population-genetics arguments, and accounting for among-lineage and among-gene effects, we propose a reconstruction of the variation in gBGC intensity at the scale of placental mammals, and of its scaling with body-size and karyotypic traits. Our results are compatible with a simple population genetics model relating gBGC to effective population size and recombination rate. In addition, among-gene variation and phylogenetic patterns of exon-specific levels of gBGC reveal the presence of rugged recombination landscapes, and suggest that short-lived recombination hot-spots are a general feature of placentals. Across placental mammals, variation in gBGC strength spans two orders of magnitude, at its lowest in apes, strongest in lagomorphs, microbats or tenrecs, and near or above the nearly neutral threshold in most other lineages. Combined with among-gene variation, such high levels of biased gene conversion are likely to significantly impact midly selected positions, and to represent a substantial mutation load. Altogether, our analysis suggests a more important role of gBGC in placental genome evolution, compared with what could have been anticipated from studies conducted in anthropoid primates.

Recombination is associated with the evolution of genome structure and worker behavior in honey bees

The rise of insect societies, marked by the formation of reproductive and sterile castes, represents a major unsolved mystery in evolution. Across several independent origins of sociality, the genomes of social hymenopterans share two peculiar attributes: high recombination and low but heterogeneous GC content. For example, the genome of the honey bee, Apis mellifera, represents a mosaic of GC-poor and GC-rich regions with rates of recombination an order of magnitude higher than in humans. However, it is unclear how heterogeneity in GC content arises, and how it relates to the expression and evolution of worker traits. Using population genetic analyses, we demonstrate a bias in the allele frequency and fixation rate of derived C or G mutations in high-recombination regions, consistent with recombination's causal influence on GC-content evolution via biased gene conversion. We also show that recombination and biased gene conversion actively maintain the heterogeneous GC content of the honey bee genome despite an overall A/T mutation bias. Further, we found that GC-rich genes and intergenic regions have higher levels of genetic diversity and divergence relative to GC-poor regions, also consistent with recombination's causal influence on the rate of molecular evolution. Finally, we found that genes associated with behavior and those with worker-biased expression are found in GC-rich regions of the bee genome and also experience high rates of molecular evolution. Taken together, these findings suggest that recombination acts to maintain a genetically diverse and dynamic part of the genome where genes underlying worker behavior evolve more quickly.

Interaction between selection and biased gene conversion in mammalian protein-coding sequence evolution revealed by a phylogenetic covariance analysis

According to the nearly-neutral model, variation in long-term effective population size among species should result in correlated variation in the ratio of nonsynonymous over synonymous substitution rates (dN/dS). Previous empirical investigations in mammals have been consistent with this prediction, suggesting an important role for nearly-neutral effects on protein-coding sequence evolution. GC-biased gene conversion (gBGC), on the other hand, is increasingly recognized as a major evolutionary force shaping genome nucleotide composition. When sufficiently strong compared with random drift, gBGC may significantly interfere with a nearly-neutral regime and impact dN/dS in a complex manner. Here, we investigate the phylogenetic correlations between dN/dS, the equilibrium GC composition (GC*), and several life-history and karyotypic traits in placental mammals. We show that the equilibrium GC composition decreases with body mass and increases with the number of chromosomes, suggesting a modulation of the strength of biased gene conversion due to changes in effective population size and genome-wide recombination rate. The variation in dN/dS is complex and only partially fits the prediction of the nearly-neutral theory. However, specifically restricting estimation of the dN/dS ratio on GC-conservative transversions, which are immune from gBGC, results in correlations that are more compatible with a nearly-neutral interpretation. Our investigation indicates the presence of complex interactions between selection and biased gene conversion and suggests that further mechanistic development is warranted, to tease out mutation, selection, drift, and conversion.

Human-specific CpG "beacons" identify loci associated with human-specific traits and disease

Regulatory change has long been hypothesized to drive the delineation of the human phenotype from other closely related primates. Here we provide evidence that CpG dinucleotides play a special role in this process. CpGs enable epigenome variability via DNA methylation, and this epigenetic mark functions as a regulatory mechanism. Therefore, species-specific CpGs may influence species-specific regulation. We report non-polymorphic species-specific CpG dinucleotides (termed “CpG beacons”) as a distinct genomic feature associated with CpG island (CGI) evolution, human traits and disease. Using an inter-primate comparison, we identified 21 extreme CpG beacon clusters (≥ 20/kb peaks, empirical p < 1.0 × 10⁻³) in humans, which include associations with four monogenic developmental and neurological disease related genes (Benjamini-Hochberg corrected p = 6.03 × 10⁻³). We also demonstrate that beacon-mediated CpG density gain in CGIs correlates with reduced methylation in these species in orthologous CGIs over time, via human, chimpanzee and macaque MeDIP-seq. Therefore mapping into both the genomic and epigenomic space the identified CpG beacon clusters define points of intersection where a substantial two-way interaction between genetic sequence and epigenetic state has occurred. Taken together, our data support a model for CpG beacons to contribute to CGI evolution from genesis to tissue-specific to constitutively active CGIs.

Evidence for widespread GC-biased gene conversion in eukaryotes

GC-biased gene conversion (gBGC) is a process that tends to increase the GC content of recombining DNA over evolutionary time and is thought to explain the evolution of GC content in mammals and yeasts. Evidence for gBGC outside these two groups is growing but is still limited. Here, we analyzed 36 completely sequenced genomes representing four of the five major groups in eukaryotes (Unikonts, Excavates, Chromalveolates and Plantae). gBGC was investigated by directly comparing GC content and recombination rates in species where recombination data are available, that is, half of them. To study all species of our dataset, we used chromosome size as a proxy for recombination rate and compared it with GC content. Among the 17 species showing a significant relationship between GC content and chromosome size, 15 are consistent with the predictions of the gBGC model. Importantly, the species showing a pattern consistent with gBGC are found in all the four major groups of eukaryotes studied, which suggests that gBGC may be widespread in eukaryotes.

Patterns and evolution of nucleotide landscapes in seed plants

Nucleotide landscapes, which are the way base composition is distributed along a genome, strongly vary among species. The underlying causes of these variations have been much debated. Though mutational bias and selection were initially invoked, GC-biased gene conversion (gBGC), a recombination-associated process favoring the G and C over A and T bases, is increasingly recognized as a major factor. As opposed to vertebrates, evolution of GC content is less well known in plants. Most studies have focused on the GC-poor and homogeneous Arabidopsis thaliana genome and the much more GC-rich and heterogeneous rice (Oryza sativa) genome and have often been generalized as a dicot/monocot dichotomy. This vision is clearly phylogenetically biased and does not allow understanding the mechanisms involved in GC content evolution in plants. To tackle these issues, we used EST data from more than 200 species and provided the most comprehensive description of gene GC content across the seed plant phylogeny so far available. As opposed to the classically assumed dicot/monocot dichotomy, we found continuous variations in GC content from the probably ancestral GC-poor and homogeneous genomes to the more derived GC-rich and highly heterogeneous ones, with several independent enrichment episodes. Our results suggest that gBGC could play a significant role in the evolution of GC content in plant genomes.

Selection on the protein-coding genome

Populations evolve as mutations arise in individual organisms and, through hereditary transmission, may become "fixed" (shared by all individuals) in the population. Most mutations are lethal or have negative fitness consequences for the organism. Others have essentially no effect on organismal fitness and can become fixed through the neutral stochastic process known as random drift. However, mutations may also produce a selective advantage that boosts their chances of reaching fixation. Regions of genes where new mutations are beneficial, rather than neutral or deleterious, tend to evolve more rapidly due to positive selection. Genes involved in immunity and defense are a well-known example; rapid evolution in these genes presumably occurs because new mutations help organisms to prevail in evolutionary "arms races" with pathogens. In recent years, genome-wide scans for selection have enlarged our understanding of the evolution of the protein-coding regions of the various species. In this chapter, we focus on the methods to detect selection in protein-coding genes. In particular, we discuss probabilistic models and how they have changed with the advent of new genome-wide data now available.

Direct and indirect consequences of meiotic recombination: implications for genome evolution

There is considerable variation within eukaryotic genomes in the local rate of crossing over. Why is this and what effect does it have on genome evolution? On the genome scale, it is known that by shuffling alleles, recombination increases the efficacy of selection. By contrast, the extent to which differences in the recombination rate modulate the efficacy of selection between genomic regions is unclear. Recombination also has direct consequences on the origin and fate of mutations: biased gene conversion and other forms of meiotic drive promote the fixation of mutations in a similar way to selection, and recombination itself may be mutagenic. Consideration of both the direct and indirect effects of recombination is necessary to understand why its rate is so variable and for correct interpretation of patterns of genome evolution.

The role of GC-biased gene conversion in shaping the fastest evolving regions of the human genome

GC-biased gene conversion (gBGC) is a recombination-associated evolutionary process that accelerates the fixation of guanine or cytosine alleles, regardless of their effects on fitness. gBGC can increase the overall rate of substitutions, a hallmark of positive selection. Many fast-evolving genes and noncoding sequences in the human genome have GC-biased substitution patterns, suggesting that gBGC-in contrast to adaptive processes-may have driven the human changes in these sequences. To investigate this hypothesis, we developed a substitution model for DNA sequence evolution that quantifies the nonlinear interacting effects of selection and gBGC on substitution rates and patterns. Based on this model, we used a series of lineage-specific likelihood ratio tests to evaluate sequence alignments for evidence of changes in mode of selection, action of gBGC, or both. With a false positive rate of less than 5% for individual tests, we found that the majority (76%) of previously identified human accelerated regions are best explained without gBGC, whereas a substantial minority (19%) are best explained by the action of gBGC alone. Further, more than half (55%) have substitution rates that significantly exceed local estimates of the neutral rate, suggesting that these regions may have been shaped by positive selection rather than by relaxation of constraint. By distinguishing the effects of gBGC, relaxation of constraint, and positive selection we provide an integrated analysis of the evolutionary forces that shaped the fastest evolving regions of the human genome, which facilitates the design of targeted functional studies of adaptation in humans.

Microevolution of cis-regulatory elements: an example from the pair-rule segmentation gene fushi tarazu in the Drosophila melanogaster subgroup

The importance of non-coding DNAs that control transcription is ever noticeable, but the characterization and analysis of the evolution of such DNAs presents challenges not found in the analysis of coding sequences. In this study of the cis-regulatory elements of the pair rule segmentation gene fushi tarazu (ftz) I report the DNA sequences of ftz's zebra element (promoter) and a region containing the proximal enhancer from a total of 45 fly lines belonging to several populations of the species Drosophila melanogaster, D. simulans, D. sechellia, D. mauritiana, D. yakuba, D. teissieri, D. orena and D. erecta. Both elements evolve at slower rate than ftz synonymous sites, thus reflecting their functional importance. The promoter evolves more slowly than the average for ftz's coding sequence while, on average, the enhancer evolves more rapidly, suggesting more functional constraint and effective purifying selection on the former. Comparative analysis of the number and nature of base substitutions failed to detect significant evidence for positive/adaptive selection in transcription-factor-binding sites. These seem to evolve at similar rates to regions not known to bind transcription factors. Although this result reflects the evolutionary flexibility of the transcription factor binding sites, it also suggests a complex and still not completely understood nature of even the characterized cis-regulatory sequences. The latter seem to contain more functional parts than those currently identified, some of which probably transcription factor binding. This study illustrates ways in which functional assignments of sequences within cis-acting sequences can be used in the search for adaptive evolution, but also highlights difficulties in how such functional assignment and analysis can be carried out.

Genomic determinants of protein evolution and polymorphism in Arabidopsis

Recent results from Drosophila suggest that positive selection has a substantial impact on genomic patterns of polymorphism and divergence. However, species with smaller population sizes and/or stronger population structure may not be expected to exhibit Drosophila-like patterns of sequence variation. We test this prediction and identify determinants of levels of polymorphism and rates of protein evolution using genomic data from Arabidopsis thaliana and the recently sequenced Arabidopsis lyrata genome. We find that, in contrast to Drosophila, there is no negative relationship between nonsynonymous divergence and silent polymorphism at any spatial scale examined. Instead, synonymous divergence is a major predictor of silent polymorphism, which suggests variation in mutation rate as the main determinant of silent variation. Variation in rates of protein divergence is mainly correlated with gene expression level and breadth, consistent with results for a broad range of taxa, and map-based estimates of recombination rate are only weakly correlated with nonsynonymous divergence. Variation in mutation rates and the strength of purifying selection seem to be major drivers of patterns of polymorphism and divergence in Arabidopsis. Nevertheless, a model allowing for varying negative and positive selection by functional gene category explains the data better than a homogeneous model, implying the action of positive selection on a subset of genes. Genes involved in disease resistance and abiotic stress display high proportions of adaptive substitution. Our results are important for a general understanding of the determinants of rates of protein evolution and the impact of selection on patterns of polymorphism and divergence.

Statistics and truth in phylogenomics

Phylogenomics refers to the inference of historical relationships among species using genome-scale sequence data and to the use of phylogenetic analysis to infer protein function in multigene families. With rapidly decreasing sequencing costs, phylogenomics is becoming synonymous with evolutionary analysis of genome-scale and taxonomically densely sampled data sets. In phylogenetic inference applications, this translates into very large data sets that yield evolutionary and functional inferences with extremely small variances and high statistical confidence (P value). However, reports of highly significant P values are increasing even for contrasting phylogenetic hypotheses depending on the evolutionary model and inference method used, making it difficult to establish true relationships. We argue that the assessment of the robustness of results to biological factors, that may systematically mislead (bias) the outcomes of statistical estimation, will be a key to avoiding incorrect phylogenomic inferences. In fact, there is a need for increased emphasis on the magnitude of differences (effect sizes) in addition to the P values of the statistical test of the null hypothesis. On the other hand, the amount of sequence data available will likely always remain inadequate for some phylogenomic applications, for example, those involving episodic positive selection at individual codon positions and in specific lineages. Again, a focus on effect size and biological relevance, rather than the P value, may be warranted. Here, we present a theoretical overview and discuss practical aspects of the interplay between effect sizes, bias, and P values as it relates to the statistical inference of evolutionary truth in phylogenomics.

Detection of lineage-specific evolutionary changes among primate species

BACKGROUND

Comparison of the human genome with other primates offers the opportunity to detect evolutionary events that created the diverse phenotypes among the primate species. Because the primate genomes are highly similar to one another, methods developed for analysis of more divergent species do not always detect signs of evolutionary selection.

RESULTS

We have developed a new method, called DivE, specifically designed to find regions that have evolved either more or less rapidly than expected, for any clade within a set of very closely related species. Unlike some previous methods, DivE does not rely on rates of synonymous and nonsynonymous substitution, which enables it to detect evolutionary events in noncoding regions. We demonstrate using simulated data that DivE compares favorably to alternative methods, and we then apply DivE to the ENCODE regions in 14 primate species. We identify thousands of regions in these primates, ranging from 50 to >10000 bp in length, that appear to have experienced either constrained or accelerated rates of evolution. In particular, we detected 4942 regions that have potentially undergone positive selection in one or more primate species. Most of these regions occur outside of protein-coding genes, although we identified 20 proteins that have experienced positive selection.

CONCLUSIONS

DivE provides an easy-to-use method to predict both positive and negative selection in noncoding DNA, that is particularly well-suited to detecting lineage-specific selection in large genomes.

Ongoing GC-biased evolution is widespread in the human genome and enriched near recombination hot spots

Fast evolving regions of many metazoan genomes show a bias toward substitutions that change weak (A,T) into strong (G,C) base pairs. Single-nucleotide polymorphisms (SNPs) do not share this pattern, suggesting that it results from biased fixation rather than biased mutation. Supporting this hypothesis, analyses of polymorphism in specific regions of the human genome have identified a positive correlation between weak to strong (W→S) SNPs and derived allele frequency (DAF), suggesting that SNPs become increasingly GC biased over time, especially in regions of high recombination. Using polymorphism data generated by the 1000 Genomes Project from 179 individuals from 4 human populations, we evaluated the extent and distribution of ongoing GC-biased evolution in the human genome. We quantified GC fixation bias by comparing the DAFs of W→S mutations and S→W mutations using a Mann-Whitney U test. Genome-wide, W→S SNPs have significantly higher DAFs than S→W SNPs. This pattern is widespread across the human genome but varies in magnitude along the chromosomes. We found extreme GC-biased evolution in neighborhoods of recombination hot spots, a significant correlation between GC bias and recombination rate, and an inverse correlation between GC bias and chromosome arm length. These findings demonstrate the presence of ongoing fixation bias favoring G and C alleles throughout the human genome and suggest that the bias is caused by a recombination-associated process, such as GC-biased gene conversion.

Substitution patterns are GC-biased in divergent sequences across the metazoans

The fastest-evolving regions in the human and chimpanzee genomes show a remarkable excess of weak (A,T) to strong (G,C) nucleotide substitutions since divergence from their common ancestor. We investigated the phylogenetic extent and possible causes of this weak to strong (W→S) bias in divergent sequences (BDS) using recently sequenced genomes and recombination maps from eight trios of eukaryotic species. To quantify evidence for BDS, we inferred substitution histories using an efficient maximum likelihood approach with a context-dependent evolutionary model. We then annotated all lineage-specific substitutions in terms of W→S bias and density on the chromosomes. Finally, we used the inferred substitutions to calculate a BDS score—a log odds ratio between substitution type and density—and assessed its statistical significance with Fisher's exact test. Applying this approach, we found significant BDS in the coding and noncoding sequence of human, mouse, dog, stickleback, fruit fly, and worm. We also observed a significant lack of W→S BDS in chicken and yeast. The BDS score varies between species and across the chromosomes within each species. It is most strongly correlated with different genomic features in different species, but a strong correlation with recombination rates is found in several species. Our results demonstrate that a W→S substitution bias in fast-evolving sequences is a widespread phenomenon. The patterns of BDS observed suggest that a recombination-associated process, such as GC-biased gene conversion, is involved in the production of the bias in many species, but the strength of the BDS likely depends on many factors, including genome stability, variability in recombination rate over time and across the genome, the frequency of meiosis, and the amount of outcrossing in each species.

Effects of natural selection and gene conversion on the evolution of human glycophorins coding for MNS blood polymorphisms in malaria-endemic African populations

Malaria has been a very strong selection pressure in recent human evolution, particularly in Africa. Of the one million deaths per year due to malaria, more than 90% are in sub-Saharan Africa, a region with high levels of genetic variation and population substructure. However, there have been few studies of nucleotide variation at genetic loci that are relevant to malaria susceptibility across geographically and genetically diverse ethnic groups in Africa. Invasion of erythrocytes by Plasmodium falciparum parasites is central to the pathology of malaria. Glycophorin A (GYPA) and B (GYPB), which determine MN and Ss blood types, are two major receptors that are expressed on erythrocyte surfaces and interact with parasite ligands. We analyzed nucleotide diversity of the glycophorin gene family in 15 African populations with different levels of malaria exposure. High levels of nucleotide diversity and gene conversion were found at these genes. We observed divergent patterns of genetic variation between these duplicated genes and between different extracellular domains of GYPA. Specifically, we identified fixed adaptive changes at exons 3-4 of GYPA. By contrast, we observed an allele frequency spectrum skewed toward a significant excess of intermediate-frequency alleles at GYPA exon 2 in many populations; the degree of spectrum distortion is correlated with malaria exposure, possibly because of the joint effects of gene conversion and balancing selection. We also identified a haplotype causing three amino acid changes in the extracellular domain of glycophorin B. This haplotype might have evolved adaptively in five populations with high exposure to malaria.

GC-biased gene conversion and selection affect GC content in the Oryza genus (rice)

Base composition varies among and within eukaryote genomes. Although mutational bias and selection have initially been invoked, more recently GC-biased gene conversion (gBGC) has been proposed to play a central role in shaping nucleotide landscapes, especially in yeast, mammals, and birds. gBGC is a kind of meiotic drive in favor of G and C alleles, associated with recombination. Previous studies have also suggested that gBGC could be at work in grass genomes. However, these studies were carried on third codon positions that can undergo selection on codon usage. As most preferred codons end in G or C in grasses, gBGC and selection can be confounded. Here we investigated further the forces that might drive GC content evolution in the rice genus using both coding and noncoding sequences. We found that recombination rates correlate positively with equilibrium GC content and that selfing species (Oryza sativa and O. glaberrima) have significantly lower equilibrium GC content compared with more outcrossing species. As recombination is less efficient in selfing species, these results suggest that recombination drives GC content. We also detected a positive relationship between expression levels and GC content in third codon positions, suggesting that selection favors codons ending with G or C bases. However, the correlation between GC content and recombination cannot be explained by selection on codon usage alone as it was also observed in noncoding positions. Finally, analyses of polymorphism data ruled out the hypothesis that genomic variation in GC content is due to mutational processes. Our results suggest that both gBGC and selection on codon usage affect GC content in the Oryza genus and likely in other grass species.

Molecular population genomics: a short history

Population genomics is the study of the amount and causes of genome-wide variability in natural populations, a topic that has been under discussion since Darwin. This paper first briefly reviews the early development of molecular approaches to the subject: the pioneering unbiased surveys of genetic variability at multiple loci by means of gel electrophoresis and restriction enzyme mapping. The results of surveys of levels of genome-wide variability using DNA resequencing studies are then discussed. Studies of the extent to which variability for different classes of variants (non-synonymous, synonymous and non-coding) are affected by natural selection, or other directional forces such as biased gene conversion, are also described. Finally, the effects of deleterious mutations on population fitness and the possible role of Hill–Robertson interference in shaping patterns of sequence variability are discussed.