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

2018 ◽  
Author(s):  
David Castellano ◽  
Adam Eyre-Walker ◽  
Kasper Munch
Keyword(s):  
Gene Conversion ◽  
Mutation Rate ◽  
Genetic Drift ◽  
Recombination Rate ◽  
Small Populations ◽  
Conserved Sequences ◽  
Positive Correlation ◽  
Dna Diversity ◽  
Biased Gene Conversion ◽  
The Impact

AbstractDNA 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.

scholarly journals Impact of Mutation Rate and Selection at Linked Sites on DNA Variation across the Genomes of Humans and Other Homininae

2019 ◽  
Vol 12 (1) ◽  
pp. 3550-3561 ◽  
Author(s):  
David Castellano ◽  
Adam Eyre-Walker ◽  
Kasper Munch
Keyword(s):  
Mutation Rate ◽  
Recombination Rate ◽  
Regional Variation ◽  
Rate Variation ◽  
Species Variation ◽  
Effective Population ◽  
Conserved Sequences ◽  
Positive Correlation ◽  
Dna Diversity ◽  
A Genome

Abstract DNA diversity varies across the genome of many species. Variation in diversity across a genome might arise from regional variation in the mutation rate, variation in the intensity and mode of natural selection, and regional variation in the recombination rate. We show that both noncoding and nonsynonymous diversity are positively correlated to a measure of the mutation rate and the recombination rate and negatively correlated to the density of conserved sequences in 50 kb windows across the genomes of humans and nonhuman homininae. Interestingly, we find that although noncoding diversity is equally affected by these three genomic variables, nonsynonymous diversity is mostly dominated by the density of conserved sequences. 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 suggest that selection at linked sites also affect levels of diversity. This is supported by the observation that the ratio of the number of nonsynonymous to noncoding polymorphisms is negatively correlated to a measure of the effective population size across the genome. We show these patterns persist even when we restrict our analysis to GC-conservative mutations, demonstrating that the patterns are not driven by GC biased gene conversion. In conclusion, our comparative analyses describe how recombination rate, gene density, and mutation rate interact to produce the patterns of DNA diversity that we observe along the hominine genomes.

scholarly journals The Red Queen model of recombination hot-spot evolution: a theoretical investigation

2017 ◽  
Vol 372 (1736) ◽  
pp. 20160463 ◽  
Author(s):  
Thibault Latrille ◽  
Laurent Duret ◽  
Nicolas Lartillot
Keyword(s):  
Gene Conversion ◽  
Recombination Rate ◽  
Evolutionary Dynamics ◽  
Genetic Model ◽  
Hot Spot ◽  
Rate Variation ◽  
Red Queen ◽  
Biased Gene Conversion ◽  
Red Queen Model ◽  
The Red Queen

In humans and many other species, recombination events cluster in narrow and short-lived hot spots distributed across the genome, whose location is determined by the Zn-finger protein PRDM9. To explain these fast evolutionary dynamics, an intra-genomic Red Queen model has been proposed, based on the interplay between two antagonistic forces: biased gene conversion, mediated by double-strand breaks, resulting in hot-spot extinction, followed by positive selection favouring new PRDM9 alleles recognizing new sequence motifs. Thus far, however, this Red Queen model has not been formalized as a quantitative population-genetic model, fully accounting for the intricate interplay between biased gene conversion, mutation, selection, demography and genetic diversity at the PRDM9 locus. Here, we explore the population genetics of the Red Queen model of recombination. A Wright–Fisher simulator was implemented, allowing exploration of the behaviour of the model (mean equilibrium recombination rate, diversity at the PRDM9 locus or turnover rate) as a function of the parameters (effective population size, mutation and erosion rates). In a second step, analytical results based on self-consistent mean-field approximations were derived, reproducing the scaling relations observed in the simulations. Empirical fit of the model to current data from the mouse suggests both a high mutation rate at PRDM9 and strong biased gene conversion on its targets. This article is part of the themed issue ‘Evolutionary causes and consequences of recombination rate variation in sexual organisms’.

scholarly journals Evidence for strong fixation bias at 4-fold degenerate sites across genes in the great tit genome

2018 ◽  
Author(s):  
Toni I. Gossmann ◽  
Mathias Bockwoldt ◽  
Lilith Diringer ◽  
Friedrich Schwarz ◽  
Vic-Fabienne Schumann
Keyword(s):  
Gene Conversion ◽  
Sequence Data ◽  
Bird Species ◽  
Gc Content ◽  
Great Tit ◽  
Genomic Features ◽  
Conversion Rates ◽  
Biased Gene Conversion ◽  
The Impact ◽  
Fixation Bias

ABSTRACTIt is well established that GC content varies across the genome in many species and that GC biased gene conversion, one form of meiotic recombination, is likely to contribute to this heterogeneity. Bird genomes provide an extraordinary system to study the impact of GC biased gene conversion owed to their specific genomic features. They are characterised by a high karyotype conservation with substantial heterogeneity in chromosome sizes, with up to a dozen large macrochromosomes and many smaller microchromosomes common across all bird species. This heterogeneity in chromosome morphology is also reflected by other genomic features, such as smaller chromosomes being gene denser, more compact and more GC rich relative to their macrochromosomal counterparts - illustrating that the intensity of GC biased gene conversion varies across the genome. Here we study whether it is possible to infer heterogeneity in GC biased gene conversion rates across the genome using a recently published method that accounts for GC biased gene conversion when estimating branch lengths in a phylogenetic context. To infer the strength of GC biased gene conversion we contrast branch length estimates across the genome both taking and not taking non-stationary GC composition into account. Using simulations we show that this approach works well when GC fixation bias is strong and note that the number of substitutions along a branch is consistently overestimated when GC biased gene conversion is not accounted for. We use this predictable feature to infer the strength of GC dynamics across the great tit genome by applying our new test statistic to data at 4-fold degenerate sites from three bird species - great tit, zebra finch and chicken - three species that are among the best annotated bird genomes to date. We show that using a simple one-dimensional binning we fail to capture a signal of fixation bias as observed in our simulations. However, using a multidimensional binning strategy, we find evidence for heterogeneity in the strength of fixation bias, including AT fixation bias. This highlights the difficulties when combining sequence data across different regions in the genome.

scholarly journals Evolutionary Consequences of DNA Methylation on the GC Content in Vertebrate Genomes

2015 ◽  
Vol 5 (3) ◽  
pp. 441-447 ◽  
Author(s):  
Carina F Mugal ◽  
Peter F Arndt ◽  
Lena Holm ◽  
Hans Ellegren
Keyword(s):  
Dna Methylation ◽  
Gene Conversion ◽  
Local Equilibrium ◽  
Gc Content ◽  
Strong Impact ◽  
Whole Genome ◽  
Cpg Dinucleotides ◽  
Genome Methylation ◽  
Biased Gene Conversion ◽  
The Impact

Abstract The genomes of many vertebrates show a characteristic variation in GC content. To explain its origin and evolution, mainly three mechanisms have been proposed: selection for GC content, mutation bias, and GC-biased gene conversion. At present, the mechanism of GC-biased gene conversion, i.e., short-scale, unidirectional exchanges between homologous chromosomes in the neighborhood of recombination-initiating double-strand breaks in favor for GC nucleotides, is the most widely accepted hypothesis. We here suggest that DNA methylation also plays an important role in the evolution of GC content in vertebrate genomes. To test this hypothesis, we investigated one mammalian (human) and one avian (chicken) genome. We used bisulfite sequencing to generate a whole-genome methylation map of chicken sperm and made use of a publicly available whole-genome methylation map of human sperm. Inclusion of these methylation maps into a model of GC content evolution provided significant support for the impact of DNA methylation on the local equilibrium GC content. Moreover, two different estimates of equilibrium GC content, one that neglects and one that incorporates the impact of DNA methylation and the concomitant CpG hypermutability, give estimates that differ by approximately 15% in both genomes, arguing for a strong impact of DNA methylation on the evolution of GC content. Thus, our results put forward that previous estimates of equilibrium GC content, which neglect the hypermutability of CpG dinucleotides, need to be reevaluated.

scholarly journals Quantifying GC-biased gene conversion in great ape genomes using polymorphism-aware models

2018 ◽  
Author(s):  
Rui Borges ◽  
Gergely Szöllősi ◽  
Carolin Kosiol
Keyword(s):  
Gene Conversion ◽  
Population Data ◽  
Great Apes ◽  
Genetic Distances ◽  
Mutation Rates ◽  
Great Ape ◽  
Genome Wide ◽  
Biased Gene Conversion ◽  
Allelic Selection ◽  
The Impact

AbstractAs multi-individual population-scale data is becoming available, more-complex modeling strategies are needed to quantify the genome-wide patterns of nucleotide usage and associated mechanisms of evolution. Recently, the multivariate neutral Moran model was proposed. However, it was shown insufficient to explain the distribution of alleles in great apes. Here, we propose a new model that includes allelic selection. Our theoretical results constitute the basis of a new Bayesian framework to estimate mutation rates and selection coefficients from population data. We employ the new framework to a great ape dataset at we found patterns of allelic selection that match those of genome-wide GC-biased gene conversion (gBCG). In particular, we show that great apes have patterns of allelic selection that vary in intensity, a feature that we correlated with the great apes’ distinct demographies. We also demonstrate that the AT/GC toggling effect decreases the probability of a substitution, promoting more polymorphisms in the base composition of great ape genomes. We further assess the impact of CG-bias in molecular analysis and we find that mutation rates and genetic distances are estimated under bias when gBGC is not properly accounted. Our results contribute to the discussion on the tempo and mode of gBGC evolution, while stressing the need for gBGC-aware models in population genetics and phylogenetics.

scholarly journals Quantification of GC-biased gene conversion in the human genome

2014 ◽  
Author(s):  
Sylvain Glemin ◽  
Peter F Arndt ◽  
Philipp W Messer ◽  
Dmitri Petrov ◽  
Nicolas Galtier ◽  
...  
Keyword(s):  
Spatial Heterogeneity ◽  
Human Genome ◽  
Gene Conversion ◽  
Excision Repair ◽  
Large Fraction ◽  
Frequency Spectra ◽  
Cpg Sites ◽  
Recombination Hotspots ◽  
Biased Gene Conversion ◽  
The Impact

Many lines of evidence indicate GC-biased gene conversion (gBGC) has a major impact on the evolution of mammalian genomes. However, up to now, this process had not been properly quantified. In principle, the strength of gBGC can be measured from the analysis of derived allele frequency spectra. However, 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, especially at hypermutable sites, and spatial heterogeneity in gBGC strength. Here we propose a new method to quantify gBGC from DAF spectra, incorporating polarization errors and taking spatial heterogeneity into account. This method is very general in that it does not require any prior knowledge about the source of polarization errors and also provides information about mutation patterns. We apply this approach 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. We further find that the impact of gBGC is concentrated primarily within recombination hotspots: genome-wide, the strength of gBGC is in the nearly neutral area, but 2% of the human genome is subject to strong gBGC, with population-scaled gBGC coefficients above 5. 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.

scholarly journals Large scale variation in the rate of de novo mutation, base composition, divergence and diversity in humans

2017 ◽  
Author(s):  
Thomas Smith ◽  
Peter Arndt ◽  
Adam Eyre-Walker
Keyword(s):  
Gene Conversion ◽  
Mutation Rate ◽  
Base Composition ◽  
Large Scale ◽  
De Novo ◽  
Gc Content ◽  
De Novo Mutation ◽  
Biased Gene Conversion ◽  
Different Types ◽  
Scale Variation

AbstractIt 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.Author 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.

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