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Elife. 2018 Aug 23;7. pii: e36317. doi: 10.7554/eLife.36317.

Background selection and biased gene conversion affect more than 95% of the human genome and bias demographic inferences.

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Computational and Molecular Population Genetics, Institute of Ecology and Evolution, University of Bern, Bern, Switzerland.
Swiss Institute of Bioinformatics, Lausanne, Switzerland.
Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland.
Contributed equally


Disentangling the effect on genomic diversity of natural selection from that of demography is notoriously difficult, but necessary to properly reconstruct the history of species. Here, we use high-quality human genomic data to show that purifying selection at linked sites (i.e. background selection, BGS) and GC-biased gene conversion (gBGC) together affect as much as 95% of the variants of our genome. We find that the magnitude and relative importance of BGS and gBGC are largely determined by variation in recombination rate and base composition. Importantly, synonymous sites and non-transcribed regions are also affected, albeit to different degrees. Their use for demographic inference can lead to strong biases. However, by conditioning on genomic regions with recombination rates above 1.5 cM/Mb and mutation types (C↔G, A↔T), we identify a set of SNPs that is mostly unaffected by BGS or gBGC, and that avoids these biases in the reconstruction of human history.


GC-biased gene conversion; background selection; demography; genetics; genomic diversity; genomics; human; recombination

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