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

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Cite this article as: eLife 2018;7:e36317 doi: 10.7554/eLife.36317

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Abstract

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.

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Author details

Fanny Pouyet

Institute of Ecology and Evolution, University of Bern, Berne, Switzerland

For correspondence
fanny.pouyet@iee.unibe.ch

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0001-5614-6998
Simon Aeschbacher

Institute of Ecology and Evolution, University of Bern, Bern, Switzerland

Competing interests
The authors declare that no competing interests exist.
Alexandre Thiéry

Institute of Ecology and Evolution, University of Bern, Bern, Switzerland

Competing interests
The authors declare that no competing interests exist.
Laurent Excoffier

Institute of Ecology and Evolution, University of Bern, Bern, Switzerland

For correspondence
laurent.excoffier@iee.unibe.ch

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0002-7507-6494

Funding

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (310030B-166605)

Laurent Excoffier

University of Berkeley (Visiting Miller Professorship)

Laurent Excoffier

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

Krishna Veeramah, Stony Brook University, United States

Publication history

Received: March 1, 2018
Accepted: August 17, 2018
Accepted Manuscript published: August 20, 2018 (version 1)
Accepted Manuscript updated: August 23, 2018 (version 2)
Version of Record published: October 9, 2018 (version 3)

Copyright

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.