Biology subjects

Eyre-Walker, A.

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

5 recordsLinked to original sources

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↗