title: Quantification of GC-biased gene conversion in the human genome.
abstract: 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 non-African 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.
authors.affiliation: Institut des Sciences de l'Evolution (ISEM - UMR 5554 Université de Montpellier-CNRS-IRD-EPHE), 34095 Montpellier, France; Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University, SE-752 36 Uppsala, Sweden;
authors.forename: Sylvain
authors.initials: S
authors.lastname: Glémin
authors.affiliation: Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany;
authors.forename: Peter F
authors.initials: PF
authors.lastname: Arndt
authors.affiliation: Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York 14853, USA;
authors.forename: Philipp W
authors.initials: PW
authors.lastname: Messer
authors.affiliation: Department of Biology, Stanford University, Stanford, California 94305-5020, USA;
authors.forename: Dmitri
authors.initials: D
authors.lastname: Petrov
authors.affiliation: Institut des Sciences de l'Evolution (ISEM - UMR 5554 Université de Montpellier-CNRS-IRD-EPHE), 34095 Montpellier, France;
authors.forename: Nicolas
authors.initials: N
authors.lastname: Galtier
authors.affiliation: Laboratoire de Biométrie et Biologie Evolutive, UMR CNRS 5558, Université Lyon 1, 69622 Villeurbanne, France.
authors.forename: Laurent
authors.initials: L
authors.lastname: Duret
mesh_terms: D001482:Base Composition; D018899:CpG Islands; D005785:Gene Conversion; D005787:Gene Frequency; D015894:Genome, Human; D006801:Humans; D008957:Models, Genetic; D011110:Polymorphism, Genetic; D044469:Racial Groups / Q000235:genetics*