Biology subjects

Eyre-Walker, A.

Publications and source records attributed to Eyre-Walker, A..

16 recordsLinked to original sources

bioRxiv2026

A simple test demonstrates that many prokaryotic accessory genes are adaptive.

Bacterial genomes often contain many genes that are only present in a subset of strains, the so-called accessory genes. Whether these genes are adaptive, neutral or deleterious remains contentious. Here we introduce a simple test to differentiate between these possibilities. If an accessory gene is adaptive then the sequence of the gene should be conserved, and the ratio of non-synonymous to synonymous diversity,{pi} n/{pi}s, should be less than one. In contrast, if the gene is neutral or deleterious, selection should not conserve the gene sequence, and{pi} n/{pi}s should equal one. We apply this test to accessory genes in Escherichia coli and Staphylococcus aureus, two highly divergent bacterial species with a large and a small pangenome respectively. We find{pi} n/{pi}s<1 for genes at all frequencies in both species demonstrating that many are adaptive. We estimate that at least 75% of all the accessory genes are maintained by selection in the two species that we have analysed, equating to thousands of adaptive accessory genes in both species, a substantial increase on previous estimates. Significance statementMany bacterial genes are found in only a subset of the strains of a bacterial species. These are referred to as accessory genes. Whether, accessory genes are adaptive, allowing certain strains to inhabit particular niches, remains a highly contentious question. In this paper we introduce a simple test of whether accessory genes are adaptive and show that >75% of them are, in two highly divergent bacterial species. This radically alters our view of this type of genetic variation and bacterial evolution.

evolutionary biology↗

bioRxiv2026

Levels of additive genetic variation vary substantially between species

A populations ability to adapt is determined by its levels of additive genetic variance (VA), and while it is agreed that most organisms have genetic variation for most traits, the extent to which it varies between species is poorly characterised. Here we investigate this question by compiling 3209 and 1852 estimates of heritability and evolvability (the additive genetic variance divided by the square of the mean) estimates respectively, for a variety of traits, from 220 and 172 multicellular eukaryotic species. Using phylogenetic generalised linear mixed models, we find substantial and highly significant interspecific variation in evolvability. Much of the variation is explained by phylogenetic relatedness, with plants in our data having substantially higher evolvability than animals. While heritability also varies between species, the differences are more subtle, and plants are not exceptional. We investigate whether the variation in evolvability and heritability between species is due to variation in the mutation rate, effective population size, genome size, ploidy and recombination rate, but find little evidence of any factor being important. However, the confidence intervals are large suggesting that we have little power to detect any associations between these factors and our estimates of VA.

evolutionary biology↗

bioRxiv2026

Nucleotide diversity is a poor predictor of short-term adaptive potential

Significance statementThe current paradigm in conservation genetics suggests that species with the lowest molecular genetic diversity have the lowest capacity to adapt. Despite previous concern that traditional measures of molecular genetic variation are not useful predictors of adaptive potential, the conflation of genetic diversity and adaptive potential remains prevalent in both scientific literature and global policy. By combining new theory with a large dataset of genetic variation across hundreds of species, we show that molecular sequence variation is weakly related to the level of heritable variation in traits across species. This demonstrates that genetic diversity does not reliably predict adaptive potential, and highlights the urgent need to move beyond simple measures when assessing the evolutionary resilience of populations. A capacity to adapt is essential for a population to avoid extinction in a changing world and is recognised as a global conservation priority. Adaptation requires additive (heritable) genetic variation for traits that influence survival and fecundity, but measuring this variation is difficult, particularly in species of conservation concern. Instead, molecular genetic diversity is often used to infer adaptive potential. However, previous research has cast doubt on the suitability of traditional molecular markers (allozymes and microsatellites) for this purpose given their weak relationship with heritability - a common measure of additive genetic variance. Recent advances in sequencing technology have since shifted focus towards nucleotide diversity and variation in functional regions, but their practicality for predicting adaptive potential remains debated and untested. Furthermore, heritability itself is a poor proxy for adaptive potential because it depends on environmental variance. We collated 2,113 published estimates of evolvability - a measure of additive genetic variance that avoids environmental confounding - across 193 eukaryotic species, and evaluated how well evolvability is predicted by molecular diversity. We find that microsatellite and nucleotide diversity are not significantly correlated to each other, and neither predict evolvability (nucleotide diversity explains 0.7% of interspecific differences in evolvability and doubling nucleotide diversity only corresponds to a 9.2% increase in evolvability). With new theoretical work, we show that such weak associations are expected. Together, our results suggest that simple molecular measures of genetic variation are insufficient for predicting adaptive potential and continued reliance on these metrics risks misinforming conservation management.

evolutionary biology↗

bioRxiv2022

The silent impact: codon usage bias and protein evolution in bacteria

Bias in synonymous codon usage has been reported across all kingdoms of life. Evidence across species suggests that codon usage bias is often driven by selective pressures, typically for translational efficiency. These selective pressures have been shown to depress the rate at which synonymous sites evolve. We hypothesise that selection on synonymous codon use could also slow the rate of protein evolution if two amino acids have different preferred codons. We test this hypothesis by looking at patterns of protein evolution using polymorphism and substitution data in bacteria. We found that non-synonymous mutations that change from unpreferred to preferred codons are more common than the opposite, but only amongst codons that vary substantially in their preference level. Overall, selection on codon bias seems to have little influence over non-synonymous polymorphism or substitution patterns.

evolutionary biology↗

bioRxiv2021

Statistical inference in population genomics

The field of population genomics has grown rapidly in response to the recent advent of affordable, large-scale sequencing technologies. As opposed to the situation during the majority of the 20th century, in which the development of theoretical and statistical population-genetic insights out-paced the generation of data to which they could be applied, genomic data are now being produced at a far greater rate than they can be meaningfully analyzed and interpreted. With this wealth of data has come a tendency to focus on fitting specific (and often rather idiosyncratic) models to data, at the expense of a careful exploration of the range of possible underlying evolutionary processes. For example, the approach of directly investigating models of adaptive evolution in each newly sequenced population or species often neglects the fact that a thorough characterization of ubiquitous non-adaptive processes is a prerequisite for accurate inference. We here describe the perils of these tendencies, present our consensus views on current best practices in population genomic data analysis, and highlight areas of statistical inference and theory that are in need of further attention. Thereby, we argue for the importance of defining a biologically relevant baseline model tuned to the details of each new analysis, of skepticism and scrutiny in interpreting model-fitting results, and of carefully defining addressable hypotheses and underlying uncertainties.

evolutionary biology↗

bioRxiv2021

Patterns of selection in the evolution of a transposable element

Transposable elements (TEs) are a major component of most eukaryotic genomes. Here, we present a new approach which allows us to study patterns of natural selection in the evolution of TEs over short time scales. The method uses the alignment of all elements with intact gag/pol genes of a TE family from a single genome. We predict that the ratio of non-synonymous to synonymous variants (vN/vS) in the alignment should decrease as a function of the frequency of the variants, because elements with non-synonymous variants that reduce transposition will have fewer progeny. We apply our method to Sirevirus LTR retrotransposons that are abundant in maize and other plant species and show that vN/vS declines as variant frequency increases, indicating that negative selection is acting strongly on the Sirevirus genome. The asymptotic value of vN/vS suggests that at least 85% of all non-synonymous mutations in the TE reduce transposition. Crucially, these patterns in vN/vS are only predicted to occur if the gene products from a particular TE insertion preferentially promote the transposition of the same insertion. Overall, this study is the first to use large numbers of intact elements to shed new light on the selective processes that act on TEs.

evolutionary biology↗

bioRxiv2021

Site level factors that affect the rate of adaptive evolution in humans and chimpanzees; the effect of contracting population size.

It has previously been shown in other species that the rate of adaptive evolution is higher at sites that are more exposed in a protein structure and lower between amino acid pairs that are more dissimilar. We have investigated whether these patterns are found in the divergence between humans and chimpanzees using an extension of the MacDonald-Kreitman test. We confirm previous findings and find that the rate of adaptive evolution, relative to the rate of mutation, is higher for more exposed amino acids, lower for amino acid pairs that are more dissimilar in terms of their polarity, volume and lower for amino acid pairs that are subject to stronger purifying selection, as measured by the ratio of the numbers of non-synonymous to synonymous polymorphisms (pN /pS). However, the slope of this latter relationship is significantly shallower than in Drosophila species. We suggest that this is due to the population contraction that has occurred since humans and chimpanzees diverged. We demonstrate theoretically that population size reduction can generate an artefactual positive correlation between the rate of adaptive evolution and any factor that is correlated to the mean strength of selection acting against deleterious mutations, even if there has been no adaptive evolution (the converse is also expected). Our measure of selective constraint, pN /pS, is negatively correlated to the mean strength of selection, and hence we would expect the correlation between the rate of adaptive evolution to also be negatively correlated to pN /pS, if there is no adaptive evolution. The fact that our rate of adaptive evolution is positively correlated to pN /pS suggests that the correlation does genuinely exist, but that is has been attenuated by population size contraction.

evolutionary biology↗

bioRxiv2021

Factors that affect the rates of adaptive and non-adaptive evolution at the gene level in humans and chimpanzees

The rate of amino acid substitution has been shown to be correlated to a number of factors including the rate of recombination, the age of the gene, the length of the protein, mean expression level and gene function. However, the extent to which these correlations are due to adaptive and non-adaptive evolution has not been studied in detail, at least not in hominids. We find that the rate of adaptive evolution is significantly positively correlated to the rate of recombination, protein length and gene expression level, and negatively correlated to gene age. The correlations remain significant when each factor is controlled for in turn, except when controlling for expression in an analysis of protein length; and they also remain significant, or marginally significant, when biased gene conversion is controlled for. However, the positive correlations could be an artefact of population size contraction. We also find that the rate of non-adaptive evolution is negatively correlated to each factor, and all these correlations survive controlling for each other and biased gene conversion. Finally, we examine the effect of gene function on rates of adaptive and non-adaptive evolution; we confirm that virus interacting proteins (VIPs) have higher rates of adaptive and lower rates of non-adaptive evolution, but we also demonstrate that there is significant variation in the rate of adaptive and non-adaptive evolution between GO categories when removing VIPs. We estimate that the VIP/non-VIP axis explains about 5-8x more of the variance in evolutionary rate than GO categories.

evolutionary biology↗

bioRxiv2021

Testing the adaptive walk model of gene evolution

Understanding the dynamics of species adaptation to their environments has long been a central focus of the study of evolution. Theories of adaptation propose that populations evolve by "walking" in a fitness landscape. This "adaptive walk" is characterised by a pattern of diminishing returns, where populations further away from their fitness optimum take larger steps than those closer to their optimal conditions. Hence, we expect young genes to evolve faster and experience mutations with stronger fitness effects than older genes because they are further away from their fitness optimum. Testing this hypothesis, however, constitutes an arduous task. Young genes are small, encode proteins with a higher degree of intrinsic disorder, are expressed at lower levels, and are involved in species-specific adaptations. Since all these factors lead to increased protein evolutionary rates, they could be masking the effect of gene age. While controlling for these factors, we used population genomic datasets of Arabidopsis and Drosophila and estimated the rate of adaptive substitutions across genes from different phylostrata. We found that a genes evolutionary age significantly impacts the molecular rate of adaptation. Moreover, we observed that substitutions in young genes tend to have larger physicochemical effects. Our study, therefore, provides strong evidence that molecular evolution follows an adaptive walk model across a large evolutionary timescale.

evolutionary biology↗

bioRxiv2021

A new test suggests that balancing selection maintains hundreds of non-synonymous polymorphisms in the human genome

The role that balancing selection plays in the maintenance of genetic diversity remains unresolved. Here we introduce a new test, based on the McDonald-Kreitman test, in which the number of polymorphisms that are shared between populations is contrasted to those that are private at selected and neutral sites. We show that this simple test is robust to a variety of demographic changes, and that it can also give a direct estimate of the number of shared polymorphisms that are directly maintained by balancing selection. We apply our method to population genomic data from humans and conclude that more than a thousand non-synonymous polymorphisms are subject to balancing selection.

evolutionary biology↗

bioRxiv2020

Mitochondrial DNA Sequence Diversity in Mammals: a Correlation Between the Effective and Census Population Sizes

What determines the level of genetic diversity of a species remains one of the enduring problems of population genetics. Since, neutral diversity depends upon the product of the effective population size and mutation rate there is an expectation that diversity should be correlated to measures of census population size. This correlation is often observed for nuclear but not for mitochondrial DNA. Here we revisit the question of whether mitochondrial DNA sequence diversity is correlated to census population size by compiling the largest dataset to date from 639 mammalian species. In a multiple regression we find that nucleotide diversity is significantly correlated to both range size and mass-specific metabolic rate, but not a variety of other factors. We also find that a measure of the effective population size, the ratio of non-synonymous to synonymous diversity, is also significantly negatively correlated to both range and mass-specific metabolic rate. These results together suggest that species with larger ranges have larger effective population sizes. The slope of the relationship between diversity and range is such that doubling the range increases diversity by 12 to 20%, providing one of the first quantifications of the relationship between effective and census population sizes.

evolutionary biology↗

bioRxiv2018

Impact of mutation rate and selection at linked sites on fine-scale DNA variation across the homininae genome

DNA diversity varies across the genome of many species. Variation in diversity across a genome might arise for one of three reasons; regional variation in the mutation rate, selection and biased gene conversion. We show that both non-coding and non-synonymous diversity are correlated to a measure of the mutation rate, the recombination rate and the density of conserved sequences in 50KB windows across the genomes of humans and non-human homininae. We show these patterns persist even when we restrict our analysis to GC-conservative mutations, demonstrating that the patterns are not driven by biased gene conversion. The positive correlation between diversity and our measure of the mutation rate seems to be largely a direct consequence of regions with higher mutation rates having more diversity. However, the positive correlation with recombination rate and the negative correlation with the density of conserved sequences suggests that selection at linked sites affect levels of diversity. This is supported by the observation that the ratio of the number of non-synonymous to non-coding polymorphisms is negatively correlated to a measure of the effective population size across the genome. Furthermore, we find evidence that these genomic variables are better predictors of non-coding diversity in large homininae populations than in small populations, after accounting for statistical power. This is consistent with genetic drift decreasing the impact of selection at linked sites in small populations. In conclusion, our comparative analyses describe for the first time how recombination rate, gene density, mutation rate and genetic drift interact to produce the patterns of DNA diversity that we observe along and between homininae genomes.

evolutionary biology↗

bioRxiv2018

Does Adaptive Protein Evolution Proceed by Large or Small Steps at the Amino Acid Level?

A longstanding question in evolutionary biology is the relative contribution of large and small effect mutations to the adaptive process. We have investigated this question in proteins by estimating the rate of adaptive evolution between all pairs of amino acids separated by one mutational step using a McDonald-Kreitman type approach and genome-wide data from several Drosophila species. We find that the rate of adaptive evolution is higher amongst amino acids that are more similar. This is partly due to the fact that the proportion of mutations that are adaptive is higher amongst more similar amino acids. We also find that the rate of neutral evolution between amino acids is higher amongst similar amino acids. Overall our results suggest that both the adaptive and non-adaptive evolution of proteins is dominated by substitutions between amino acids that are more similar.

evolutionary biology↗

bioRxiv2017

The Distribution of Bacterial Doubling Times in the Wild

Generation time varies widely across organisms and is an important factor in the life cycle, life history and evolution of organisms. Although the doubling time (DT), has been estimated for many bacteria in the lab, it is nearly impossible to directly measure it in the natural environment. However, an estimate can be obtained by measuring the rate at which bacteria accumulate mutations per year in the wild and the rate at which they mutate per generation in the lab. If we assume the mutation rate per generation is the same in the wild and in the lab, and that all mutations in the wild are neutral, an assumption that we show is not very important, then an estimate of the DT can be obtained by dividing the latter by the former. We estimate the DT for four species of bacteria for which we have both an accumulation and a mutation rate estimate. We also infer the distribution of DTs across all bacteria from the distribution of the accumulation and mutation rates. Both analyses suggest that DTs for bacteria in the wild are substantially greater than those in the lab, that they vary by orders of magnitude between different species of bacteria and that a substantial fraction of bacteria double very slowly in the wild.

microbiology↗

bioRxiv2017

Nearly Neutral Evolution Across the Drosophila melanogaster Genome

Under the nearly neutral theory of molecular evolution the proportion of effectively neutral mutations is expected to depend upon the effective population size (Ne). Here we investigate whether this is the case across the genome of Drosophila melanogaster using polymorphism data from North American and African lines. We show that the ratio of the number of non-synonymous and synonymous polymorphisms is negatively correlated to the number of synonymous polymorphisms, even when the non-independence is accounted for. The relationship is such that the proportion of effectively neutral non-synonymous mutations increases by ~45% as Ne is halved. However, we also show that this relationship is steeper than expected from an independent estimate of the distribution of fitness effects from the site frequency spectrum. We investigate a number of potential explanations for this and show, using simulation, that this is consistent with a model of genetic hitch-hiking: genetic hitch-hiking depresses diversity at neutral and weakly selected sites, but has little effect on the diversity of strongly selected sites.

evolutionary biology↗

bioRxiv2017

Large scale variation in the rate of de novo mutation in humans and its relationship to divergence and diversity.

It has long been suspected that the rate of mutation varies across the human genome at a large scale based on the divergence between humans and other species. It is now possible to directly investigate this question using the large number of de novo mutations (DNMs) that have been discovered in humans through the sequencing of trios. We show that there is variation in the mutation rate at the 100KB, 1MB and 10MB scale that cannot be explained by variation at smaller scales, however the level of this variation is modest at large scales - at the 1MB scale we infer that ~90% of regions have a mutation rate within 50% of the mean. Different types of mutation show similar levels of variation and appear to vary in concert which suggests the pattern of mutation is relatively constant across the genome and hence unlikely to generate variation in GC-content. We confirm this using two different analyses. We find that genomic features explain less than 50% of the explainable variance in the rate of DNM. As expected the rate of divergence between species and the level of diversity within humans are correlated to the rate of DNM. However, the correlations are weaker than if all the variation in divergence was due to variation in the mutation rate. We provide evidence that this is due the effect of biased gene conversion on the probability that a mutation will become fixed. We find no evidence that linked selection affects the relationship between divergence and DNM density. In contrast to divergence, we find that most of the variation in diversity can be explained by variation in the mutation rate. Finally, we show that the correlation between divergence and DNM density declines as increasingly divergent species are considered.\n\nAuthor summaryUsing a dataset of 40,000 de novo mutations we show that there is large-scale variation in the mutation rate at the 100KB and 1MB scale. We show that different types of mutation vary in concert and in a manner that is not expected to generate variation in base composition; hence mutation bias is not responsible for the large-scale variation in base composition that is observed across human chromosomes. As expected large-scale variation in the rate of divergence between species and the variation within species across the genome, are correlated to the rate of mutation, but the correlation between divergence and the mutation rate is not as strong as they could be. We show that biased gene conversion is responsible for weakening the correlation. In contrast we find that most of the variation across the genome in diversity can be explained by variation in the mutation rate. Finally, we show that the correlation between the rate of mutation in humans and the divergence between humans and other species, weakens as the species become more divergent.

genomics↗