Quantification of GC-biased gene conversion in the human genome

Glémin, Sylvain; Arndt, Peter F.; Messer, Philipp W.; Petrov, Dmitri A.; Galtier, Nicolas; Duret, Laurent

doi:10.1101/gr.185488.114

Cited by 139 publications

(199 citation statements)

References 69 publications

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“…We assumed that such processes also affected the nonsynonymous uSFS and would lead to upwardly biased estimates of positive selection parameters if not corrected. In a similar manner to that described by Glémin et al (2015), which follows the approach of Eyre-Walker et al(2006), we therefore corrected elements of the nonsynonymous uSFS N j using the deviations of the observed elements S j from the fitted elements E j of the synonymous uSFS:We assessed goodness of fit by comparing fitted uSFSs to observed uSFSs using a x 2 statistic, but because the numbers of sites in derived class j and ancestral class n 2 j are nonindependent, we did not perform formal significance tests. Conditioning on the values of the parameters fitted to the synonymous SFS, parameters specifying the effects and relative frequencies of deleterious and advantageous mutations were fitted by ML to the corrected nonsynonymous uSFS.…”

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confidence: 60%

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Inferring the Frequency Spectrum of Derived Variants to Quantify Adaptive Molecular Evolution in Protein-Coding Genes of Drosophila melanogaster

Keightley

Campos²,

Booker³

et al. 2016

Genetics

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Many approaches for inferring adaptive molecular evolution analyze the unfolded site frequency spectrum (SFS), a vector of counts of sites with different numbers of copies of derived alleles in a sample of alleles from a population. Accurate inference of the high-copy-number elements of the SFS is difficult, however, because of misassignment of alleles as derived vs. ancestral. This is a known problem with parsimony using outgroup species. Here we show that the problem is particularly serious if there is variation in the substitution rate among sites brought about by variation in selective constraint levels. We present a new method for inferring the SFS using one or two outgroups that attempts to overcome the problem of misassignment. We show that two outgroups are required for accurate estimation of the SFS if there is substantial variation in selective constraints, which is expected to be the case for nonsynonymous sites in protein-coding genes. We apply the method to estimate unfolded SFSs for synonymous and nonsynonymous sites in a population of Drosophila melanogaster from phase 2 of the Drosophila Population Genomics Project. We use the unfolded spectra to estimate the frequency and strength of advantageous and deleterious mutations and estimate that 50% of amino acid substitutions are positively selected but that ,0.5% of new amino acid mutations are beneficial, with a scaled selection strength of N e s 12.KEYWORDS adaptation; distribution of fitness effects; Drosophila; site frequency spectrum (SFS) M OST protein sequences are strongly conserved between closely related species, which suggests that most amino acid-changing mutations are selectively removed from populations (Graur and Li 2000). The nature of the selective forces acting on the mutations that become fixed between species is central to a variety of questions in population genetics. These include understanding the maintenance of variation within species, determining the causes of variation in nucleotide diversity across the genome, and discerning the nature of evolutionary adaptation. Evidence for pervasive selection in the genome comes from observations of positive correlations between nucleotide diversity at putatively neutrally evolving sites and the rate of recombination (Begun and Aquadro 1992) and negative correlations between local genomic diversity and the presence of functional elements (such as protein-coding exons or conserved noncoding elements) (Cai et al. 2009;Hernandez et al. 2011;Lohmueller et al. 2011;Halligan et al. 2013;Enard et al. 2014;Deinum et al. 2015). These correlations are likely to be caused by natural selection acting on functional sites in the genome reducing diversity at linked sites, but the precise nature of the selective forces involved is unresolved because both selective sweeps owing to positive selection and background selection caused by purifying selection can contribute to these patterns.One approach to discriminating between the contributions of neutral, deleterious, and advantageous substituti...

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confidence: 60%

“…Inference of the uSFS is potentially compromised, however, by misassignment of the ancestral state, and this tends to affect high-frequency elements of the SFS disproportionately (Fay and Wu 2000;Baudry and Depaulis 2003;Hernandez et al 2007;Glémin et al 2015). Current methods for inferring the uSFS rely on a single outgroup (Hernandez et al 2007).…”

mentioning

confidence: 99%

Inferring the Frequency Spectrum of Derived Variants to Quantify Adaptive Molecular Evolution in Protein-Coding Genes of Drosophila melanogaster

Keightley

Campos²,

Booker³

et al. 2016

Genetics

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“…Moreover, the patterns of substitution within the phylogeny indicate that GC-biased gene conversion has remained a consistent, localized force around MNase HS regions. This situation differs from that in humans, where the high conversion sites are inconsistent between populations and species (18), likely because of the rapid evolution of PRDM9 motifs (30). Because GC-biased gene conversion imposes a fitness-independent selective force, slightly deleterious alleles may become fixed if their selective disadvantages are sufficiently less extreme than their conversion advantages (31).…”

Section: Discussionmentioning

confidence: 88%

Open chromatin reveals the functional maize genome

Rodgers-Melnick

Vera

Bass

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

266

276

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Cellular processes mediated through nuclear DNA must contend with chromatin. Chromatin structural assays can efficiently integrate information across diverse regulatory elements, revealing the functional noncoding genome. In this study, we use a differential nuclease sensitivity assay based on micrococcal nuclease (MNase) digestion to discover open chromatin regions in the maize genome. We find that maize MNase-hypersensitive (MNase HS) regions localize around active genes and within recombination hotspots, focusing biased gene conversion at their flanks. Although MNase HS regions map to less than 1% of the genome, they consistently explain a remarkably large amount (∼40%) of heritable phenotypic variance in diverse complex traits. MNase HS regions are therefore on par with coding sequences as annotations that demarcate the functional parts of the maize genome. These results imply that less than 3% of the maize genome (coding and MNase HS regions) may give rise to the overwhelming majority of phenotypic variation, greatly narrowing the scope of the functional genome.A ll cellular processes involving the nuclear DNA, including transcription, recombination, and replication, must contend with local chromatin states. Each of these processes can affect phenotypic variation, either directly or through constraints on natural selection. To date, humans and several model systems with small genomes have had their chromatin landscapes wellcharacterized (1-4). However, with a limited number of wellstudied large, complex genomes, many general principles relating chromatin structure to genome regulation remain unknown. Here, we examine the large genome of maize (Zea mays L.), a model crop species. The importance of maize within international agriculture motivates our central question: Which portions of the genome contribute to quantitative trait variation? Several features of maize biology, such as the capacity for large controlled crosses, rapid decay of linkage disequilibrium (LD), high genetic diversity, and substantial spacing between genes, make it an excellent experimental system for pursuing this question.Fine-scale characterization of the chromatin structural landscape requires an assay that can distinguish accessible (open) from condensed chromatin at the nucleosomal to subnucleosomal scales. In general, chromatin accessibility may be assayed through in situ digestion of the nuclear DNA with a non-sequence-specific nuclease, followed by quantification of the resulting DNA fragments (5). Micrococcal nuclease (MNase) cleaves DNA between nucleosomes, revealing genome-wide nucleosome occupancy (6, 7). However, differential sensitivity to MNase digestion also reveals chromatin accessibility, with genomic regions of open chromatin preferentially recovered under light-digestion relative to heavydigestion conditions (8). In maize, a differential MNase sensitivity assay with microarray quantification [differential nuclease sensitivity (DNS)-chip] demonstrated that MNase hypersensitive (MNase HS) regions are positively assoc...

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“…2F). We hypothesize this observation may be due to the interaction of recombination rate heterogeneity between populations, strength of gBGC, and genomic contexts (Galtier et al 2009;Glemin et al 2015), but additional work is necessary to fully interpret patterns of deleterious variation at P → U gBGC synonymous sites. A schematic summary of the context-dependent effects observed in estimates of f for synonymous SNVs is shown in Figure 2G.…”

Section: Influence Of Codon Bias and Chromatin Accessibility On The Bmentioning

confidence: 99%

A flexible method for estimating the fraction of fitness influencing mutations from large sequencing data sets

Moon

Akey

2016

Genome Res.

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A continuing challenge in the analysis of massively large sequencing data sets is quantifying and interpreting non-neutrally evolving mutations. Here, we describe a flexible and robust approach based on the site frequency spectrum to estimate the fraction of deleterious and adaptive variants from large-scale sequencing data sets. We applied our method to approximately 1 million single nucleotide variants (SNVs) identified in high-coverage exome sequences of 6515 individuals. We estimate that the fraction of deleterious nonsynonymous SNVs is higher than previously reported; quantify the effects of genomic context, codon bias, chromatin accessibility, and number of protein-protein interactions on deleterious protein-coding SNVs; and identify pathways and networks that have likely been influenced by positive selection. Furthermore, we show that the fraction of deleterious nonsynonymous SNVs is significantly higher for Mendelian versus complex disease loci and in exons harboring dominant versus recessive Mendelian mutations. In summary, as genome-scale sequencing data accumulate in progressively larger sample sizes, our method will enable increasingly high-resolution inferences into the characteristics and determinants of non-neutral variation.

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Quantification of GC-biased gene conversion in the human genome

Cited by 139 publications

References 69 publications

Inferring the Frequency Spectrum of Derived Variants to Quantify Adaptive Molecular Evolution in Protein-Coding Genes of Drosophila melanogaster

Inferring the Frequency Spectrum of Derived Variants to Quantify Adaptive Molecular Evolution in Protein-Coding Genes of Drosophila melanogaster

Open chromatin reveals the functional maize genome

A flexible method for estimating the fraction of fitness influencing mutations from large sequencing data sets

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