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.

scholarly journals Biased gene conversion drives codon usage in human and precludes selection on translation efficiency

2016 ◽  
Author(s):  
Fanny Pouyet ◽  
Dominique Mouchiroud ◽  
Laurent Duret ◽  
Marie Sémon
Keyword(s):  
Gene Expression ◽  
Codon Usage ◽  
Gene Conversion ◽  
Large Scale ◽  
Synonymous Codon ◽  
Gc Content ◽  
Intragenic Recombination ◽  
Translation Efficiency ◽  
Functional Categories ◽  
Biased Gene Conversion

AbstractIn humans, as in other mammals, synonymous codon usage (SCU) varies widely among genes. In particular, genes involved in cell differentiation or in proliferation display a distinct codon usage, suggesting that SCU is adaptively constrained to optimize translation efficiency in distinct cellular states. However, in mammals, SCU is known to correlate with large-scale fluctuations of GC-content along chromosomes, caused by meiotic recombination, via the non-adaptive process of GC-biased gene conversion (gBGC). To disentangle and to quantify the different factors driving SCU in humans, we analyzed the relationships between functional categories, base composition, recombination, and gene expression. We first demonstrate that SCU is predominantly driven by large-scale variation in GC-content and is not linked to constraints on tRNA abundance, which excludes an effect of translational selection. In agreement with the gBGC model, we show that differences in SCU among functional categories are explained by variation in intragenic recombination rate, which, in turn, is strongly negatively correlated to gene expression levels during meiosis. Our results indicate that variation in SCU among functional categories (including variation associated to differentiation or proliferation) result from differences in levels of meiotic transcription, which interferes with the formation of crossovers and thereby affects gBGC intensity within genes. Overall, the gBGC model explains 70% of the variance in SCU among genes. We argue that the strong heterogeneity of SCU induced by gBGC in mammalian genomes precludes any optimization of the tRNA pool to the demand in codon usage.

scholarly journals Evidence of Selection on Silent Site Base Composition in Mammals: Potential Implications for the Evolution of Isochores and Junk DNA

Genetics ◽  
1999 ◽  
Vol 152 (2) ◽  
pp. 675-683 ◽  
Author(s):  
Adam Eyre-Walker
Keyword(s):  
Gene Conversion ◽  
Base Composition ◽  
Large Scale ◽  
Cpg Island ◽  
Mammalian Species ◽  
Genetic Data ◽  
Mutation Bias ◽  
Junk Dna ◽  
Biased Gene Conversion ◽  
Large Sections

Abstract It has been suggested that mutation bias is the major determinant of base composition bias at synonymous, intron, and flanking DNA sites in mammals. Here I test this hypothesis using population genetic data from the major histocompatibility genes of several mammalian species. The results of two tests are inconsistent with the mutation hypothesis in coding, noncoding, CpG-island, and non-CpG-island DNA, but are consistent with selection or biased gene conversion. It is argued that biased gene conversion is unlikely to affect silent site base composition in mammals. The results therefore suggest that selection is acting upon silent site G + C content. This may have broad implications, since silent site base composition reflects large-scale variation in G + C content along mammalian chromosomes. The results therefore suggest that selection may be acting upon the base composition of isochores and large sections of junk DNA.

scholarly journals Non-neutral processes drive the nucleotide composition of non-coding sequences in Drosophila

2008 ◽  
Vol 4 (4) ◽  
pp. 438-441 ◽  
Author(s):  
Penelope R Haddrill ◽  
Brian Charlesworth
Keyword(s):  
Gene Conversion ◽  
X Chromosome ◽  
Base Composition ◽  
Gc Content ◽  
Nucleotide Composition ◽  
Mutational Bias ◽  
Base Pairs ◽  
Coding Sequences ◽  
Biased Gene Conversion ◽  
Gc Contents

The nature of the forces affecting base composition is a key question in genome evolution. There is uncertainty as to whether differences in the GC contents of non-coding sequences reflect differences in mutational bias, or in the intensity of selection or biased gene conversion. We have used a polymorphism dataset for non-coding sequences on the X chromosome of Drosophila simulans to examine this question. The proportion of GC→AT versus AT→GC polymorphic mutations in a locus is correlated with its GC content. This implies the action of forces that favour GC over AT base pairs, which are apparently strongest in GC-rich sequences.

scholarly journals Base composition changes indicate biased gene conversion is a major factor in the evolution of the Fam53A gene

2010 ◽  
Vol 24 (S1) ◽  
Author(s):  
Andrew David Bergemann ◽  
Joy S. Reidenberg ◽  
Jeffrey T. Laitman ◽  
Lucy Skrabanek ◽  
Isabel Genecin
Keyword(s):  
Gene Conversion ◽  
Base Composition ◽  
Biased Gene Conversion ◽  
Composition Changes

scholarly journals Direct estimate of the spontaneous mutation rate uncovers the effects of drift and recombination in theChlamydomonas reinhardtiiplastid genome

2015 ◽  
Author(s):  
Rob W Ness ◽  
Susanne A Kraemer ◽  
Nick Colegrave ◽  
Peter D Keightley
Keyword(s):  
Mutation Rate ◽  
Genetic Drift ◽  
Plastid Genome ◽  
De Novo ◽  
Spontaneous Mutation ◽  
Genome Structure ◽  
Nuclear Genome ◽  
De Novo Mutation ◽  
Direct Estimate ◽  
Plastid Genomes

Plastids perform crucial cellular functions, including photosynthesis, across a wide variety of eukaryotes. Since endosymbiosis, plastids have maintained independent genomes that now display a wide diversity of gene content, genome structure, gene regulation mechanisms, and transmission modes. The evolution of plastid genomes depends on an input ofde novomutation, but our knowledge of mutation in the plastid is limited to indirect inference from patterns of DNA divergence between species. Here, we use a mutation accumulation experiment, where selection acting on mutations is rendered ineffective, combined with whole-plastid genome sequencing to directly characterize de novo mutation inChlamydomonas reinhardtii. We show that the mutation rates of the plastid and nuclear genomes are similar, but that the base spectra of mutations differ significantly. We integrate our measure of the mutation rate with a population genomic dataset of 20 individuals, and show that the plastid genome is subject to substantially stronger genetic drift than the nuclear genome. We also show that high levels of linkage disequilibrium in the plastid genome are not due to restricted recombination, but are instead a consequence of increased genetic drift. One likely explanation for increased drift in the plastid genome is that there are stronger effects of genetic hitchhiking. The presence of recombination in the plastid is consistent with laboratory studies inC. reinhardtiiand demonstrates that although the plastid genome is thought to be uniparentally inherited, it recombines in nature at a rate similar to the nuclear genome.

Empirical investigation of mutation rate for herbicide resistance

Weed Science ◽  
2019 ◽  
Vol 67 (4) ◽  
pp. 361-368 ◽  
Author(s):  
Federico A. Casale ◽  
Darci A. Giacomini ◽  
Patrick J. Tranel
Keyword(s):  
Mutation Rate ◽  
Herbicide Resistance ◽  
De Novo ◽  
Selection Process ◽  
Theoretical Calculations ◽  
Acetolactate Synthase ◽  
De Novo Mutation ◽  
De Novo Mutations ◽  
Sources Of Resistance ◽  
Resistant Mutants

AbstractIn a predictable natural selection process, herbicides select for adaptive alleles that allow weed populations to survive. These resistance alleles may be available immediately from the standing genetic variation within the population or may arise from immigration via pollen or seeds from other populations. Moreover, because all populations are constantly generating new mutant genotypes by de novo mutations, resistant mutants may arise spontaneously in any herbicide-sensitive weed population. Recognizing that the relative contribution of each of these three sources of resistance alleles influences what strategies should be applied to counteract herbicide-resistance evolution, we aimed to add experimental information to the resistance evolutionary framework. Specifically, the objectives of this experiment were to determine the de novo mutation rate conferring herbicide resistance in a natural plant population and to test the hypothesis that the mutation rate increases when plants are stressed by sublethal herbicide exposure. We used grain amaranth (Amaranthus hypochondriacus L.) and resistance to acetolactate synthase (ALS)-inhibiting herbicides as a model system to discover spontaneous herbicide-resistant mutants. After screening 70.8 million plants, however, we detected no spontaneous resistant genotypes, indicating the probability of finding a spontaneous ALS-resistant mutant in a given sensitive population is lower than 1.4 × 10−8. This empirically determined upper limit is lower than expected from theoretical calculations based on previous studies. We found no evidence that herbicide stress increased the mutation rate, but were not able to robustly test this hypothesis. The results found in this study indicate that de novo mutations conferring herbicide resistance might occur at lower frequencies than previously expected.

scholarly journals Ancestral Graph with Bias in Gene Conversion

2013 ◽  
Vol 50 (1) ◽  
pp. 239-255 ◽  
Author(s):  
Shuhei Mano
Keyword(s):  
Stochastic Model ◽  
Gene Conversion ◽  
Importance Sampling ◽  
Diffusion Approximation ◽  
Multigene Family ◽  
Dual Process ◽  
Fixation Probability ◽  
Biased Gene Conversion ◽  
Different Types ◽  
Ancestral Graph

Gene conversion is a genetic mechanism by which one gene is ‘copied and pasted’ onto another gene, where the direction can be biased between the different types. In this paper, a stochastic model for biased gene conversion within a d-unlinked multigene family and its diffusion approximation are developed for a finite Moran population. A connection with a d-island model is made. A formula for the fixation probability in the absence of mutation is given. A two-timescale argument is applied in the case of the strong conversion limit. The dual process is generally shown to be a biased voter model, which generates an ancestral bias graph for a given sample. An importance sampling algorithm for computing the likelihood of the sample is deduced.

scholarly journals Extensivede novomutation rate variation between individuals and across the genome ofChlamydomonas reinhardtii

2015 ◽  
Author(s):  
Rob W Ness ◽  
Andrew D Morgan ◽  
Radhakrishnan B Vasanthakrishnan ◽  
Nick Colegrave ◽  
Peter D Keightley
Keyword(s):  
Mutation Rate ◽  
Evolutionary Biology ◽  
De Novo ◽  
Spontaneous Mutation ◽  
Gc Content ◽  
Rate Variation ◽  
De Novo Mutations ◽  
Local Sequence ◽  
Wild Strains ◽  
Genomic Regions

Describing the process of spontaneous mutation is fundamental for understanding the genetic basis of disease, the threat posed by declining population size in conservation biology, and in much evolutionary biology. However, directly studying spontaneous mutation is difficult because of the rarity of de novo mutations. Mutation accumulation (MA) experiments overcome this by allowing mutations to build up over many generations in the near absence of natural selection. In this study, we sequenced the genomes of 85 MA lines derived from six genetically diverse wild strains of the green algaChlamydomonas reinhardtii. We identified 6,843 spontaneous mutations, more than any other study of spontaneous mutation. We observed seven-fold variation in the mutation rate among strains and that mutator genotypes arose, increasing the mutation rate dramatically in some replicates. We also found evidence for fine-scale heterogeneity in the mutation rate, driven largely by the sequence flanking mutated sites, and by clusters of multiple mutations at closely linked sites. There was little evidence, however, for mutation rate heterogeneity between chromosomes or over large genomic regions of 200Kbp. Using logistic regression, we generated a predictive model of the mutability of sites based on their genomic properties, including local GC content, gene expression level and local sequence context. Our model accurately predicted the average mutation rate and natural levels of genetic diversity of sites across the genome. Notably, trinucleotides vary 17-fold in rate between the most mutable and least mutable sites. Our results uncover a rich heterogeneity in the process of spontaneous mutation both among individuals and across the genome.

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.

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