GC-Biased Gene Conversion in Yeast Is Specifically Associated with Crossovers: Molecular Mechanisms and Evolutionary Significance

Lesecque, Yann; Mouchiroud, Dominique; Duret, Laurent

doi:10.1093/molbev/mst056

Cited by 97 publications

(109 citation statements)

References 65 publications

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“…The fact that we do not observe such a pattern strongly argues against this hypothesis. This observation is in accordance with recent results demonstrating that in yeast, gBGC is not caused by BER (Lesecque et al 2013). The prominent repair pathway during recombination is the mismatch repair (MMR) system (Surtees et al 2004).…”

Section: No Difference In Gbgc Strength Between Cpg and Non-cpg Sitessupporting

confidence: 93%

“…The prominent repair pathway during recombination is the mismatch repair (MMR) system (Surtees et al 2004). In yeast, the analysis of gene conversion tracts indicates that gBGC is most probably caused by MMR (Lesecque et al 2013). Our observations suggest that this might also be the case in humans.…”

Section: No Difference In Gbgc Strength Between Cpg and Non-cpg Sitesmentioning

confidence: 99%

“…gBGC is a recombination-associated process favoring G:C (S for strong, hereafter) over A:T (W for weak, hereafter) bases during the repair of mismatches that occur within heteroduplex DNA during meiotic recombination (Marais 2003;Lesecque et al 2013). From a population genetics point of view, gBGC is equivalent to natural selection in favor of S alleles, increasing their frequency and probability of fixation (Nagylaki 1983).…”

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confidence: 99%

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Quantification of GC-biased gene conversion in the human genome

et al. 2015

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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 nonAfrican 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.

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Section: No Difference In Gbgc Strength Between Cpg and Non-cpg Sitessupporting

confidence: 93%

Section: No Difference In Gbgc Strength Between Cpg and Non-cpg Sitesmentioning

confidence: 99%

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confidence: 99%

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Quantification of GC-biased gene conversion in the human genome

et al. 2015

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“…If noncrossover pathways are the favored resolution of DSBs in the chromosome centers (Saito et al 2013), and if noncrossover gene conversions disproportionately exhibit GC-biased transmission, BGC could be a mechanism that generates the observed GC domain structure. In yeast, BGC is actually restricted to crossover-associated gene conversion tracts (Lesecque et al 2013), but the relationship between BGC and recombination pathway clearly evolves and varies among species (Capra and Pollard 2011;Poh et al 2012). Recent dissection of the partially redundant Holiday junction resolvases in C. elegans (Saito et al 2013;O'Neil et al 2013;Agostinho et al 2013) leads us to the hypothesis that slx-1, which is disproportionately responsible for noncrossover gene conversion in chromosome centers (Saito et al 2013), may be more prone to BGC than the other resolvases.…”

Section: Discussionmentioning

confidence: 99%

Crossover Heterogeneity in the Absence of Hotspots inCaenorhabditis elegans

Kaur

Rockman

2014

Genetics

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Crossovers play mechanical roles in meiotic chromosome segregation, generate genetic diversity by producing new allelic combinations, and facilitate evolution by decoupling linked alleles. In almost every species studied to date, crossover distributions are dramatically nonuniform, differing among sexes and across genomes, with spatial variation in crossover rates on scales from whole chromosomes to subkilobase hotspots. To understand the regulatory forces dictating these heterogeneous distributions a crucial first step is the fine-scale characterization of crossover distributions. Here we define the wild-type distribution of crossovers along a region of the C. elegans chromosome II at unprecedented resolution, using recombinant chromosomes of 243 hermaphrodites and 226 males. We find that well-characterized large-scale domains, with little fine-scale rate heterogeneity, dominate this region's crossover landscape. Using the Gini coefficient as a summary statistic, we find that this region of the C. elegans genome has the least heterogeneous fine-scale crossover distribution yet observed among model organisms, and we show by simulation that the data are incompatible with a mammalian-type hotspot-rich landscape. The large-scale structural domains-the low-recombination center and the high-recombination arm-have a discrete boundary that we localize to a small region. This boundary coincides with the armcenter boundary defined both by nuclear-envelope attachment of DNA in somatic cells and GC content, consistent with proposals that these features of chromosome organization may be mechanical causes and evolutionary consequences of crossover recombination. MEIOTIC recombination creates novel combinations of parental alleles and is a powerful force shaping the genetic variation observed within a population. The frequency of recombination has a profound impact on the efficacy of natural selection in both purging deleterious mutations and in the formation of beneficial allelic combinations (Hill and Robertson 1966;Cutter and Payseur 2013). However, the intensity of recombination in different parts of a genome is rarely constant. Heterogeneity in the meiotic recombination rate has been observed across chromosome lengths and at finer scales of a few kilobase in diverse organisms.In Caenorhabditis elegans, meiotic recombination rates show a striking and reproducible chromosome-wide pattern of variation. Genetic maps of the five autosomes and X chromosome show that each has a low-recombination central domain flanked by high-recombination arm domains (Barnes et al. 1995;Rockman and Kruglyak 2009). This domain structure has dramatic effects on genetic variation and evolution (Cutter and Payseur 2003;Rockman et al. 2010;Andersen et al. 2012), but the underlying causes generating this pattern are not completely understood.The domain structure relates to unusual characteristics of the C. elegans chromosomes. The chromosomes lack localized centromeres and exhibit holocentric segregation during mitosis, with kinetochore pro...

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“…GC-biased gene conversion (gBGC) associated with meiotic recombination leads to the preferential fixation of GC in AT/GC heterozygotes and is a major determinant of base composition. Direct experimental evidence is currently limited to S. cerevisiae, with a significant 1.3% excess of transmitted GC alleles thought to result from a bias in the mismatch repair machinery [8][9][10][11]. However, evidence for its effects is observed across a wide range of taxa [12][13][14][15][16], leading to a widespread association between GC content and crossover rates [8,13,[17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Evidence for GC-biased gene conversion as a driver of between-lineage differences in avian base composition

et al. 2014

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Background: While effective population size (N e ) and life history traits such as generation time are known to impact substitution rates, their potential effects on base composition evolution are less well understood. GC content increases with decreasing body mass in mammals, consistent with recombination-associated GC biased gene conversion (gBGC) more strongly impacting these lineages. However, shifts in chromosomal architecture and recombination landscapes between species may complicate the interpretation of these results. In birds, interchromosomal rearrangements are rare and the recombination landscape is conserved, suggesting that this group is well suited to assess the impact of life history on base composition.Results: Employing data from 45 newly and 3 previously sequenced avian genomes covering a broad range of taxa, we found that lineages with large populations and short generations exhibit higher GC content. The effect extends to both coding and non-coding sites, indicating that it is not due to selection on codon usage. Consistent with recombination driving base composition, GC content and heterogeneity were positively correlated with the rate of recombination. Moreover, we observed ongoing increases in GC in the majority of lineages.

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GC-Biased Gene Conversion in Yeast Is Specifically Associated with Crossovers: Molecular Mechanisms and Evolutionary Significance

Cited by 97 publications

References 65 publications

Quantification of GC-biased gene conversion in the human genome

Quantification of GC-biased gene conversion in the human genome

Crossover Heterogeneity in the Absence of Hotspots inCaenorhabditis elegans

Evidence for GC-biased gene conversion as a driver of between-lineage differences in avian base composition

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