Literature DB >> 34849862

Sporadic occurrence of recent selective sweeps from standing variation in humans as revealed by an approximate Bayesian computation approach.

Guillaume Laval1, Etienne Patin1, Pierre Boutillier2, Lluis Quintana-Murci1,3.   

Abstract

During their dispersals over the last 100,000 years, modern humans have been exposed to a large variety of environments, resulting in genetic adaptation. While genome-wide scans for the footprints of positive Darwinian selection have increased knowledge of genes and functions potentially involved in human local adaptation, they have globally produced evidence of a limited contribution of selective sweeps in humans. Conversely, studies based on machine learning algorithms suggest that recent sweeps from standing variation are widespread in humans, an observation that has been recently questioned. Here, we sought to formally quantify the number of recent selective sweeps in humans, by leveraging approximate Bayesian computation and whole-genome sequence data. Our computer simulations revealed suitable ABC estimations, regardless of the frequency of the selected alleles at the onset of selection and the completion of sweeps. Under a model of recent selection from standing variation, we inferred that an average of 68 (from 56 to 79) and 140 (from 94 to 198) sweeps occurred over the last 100,000 years of human history, in African and Eurasian populations, respectively. The former estimation is compatible with human adaptation rates estimated since divergence with chimps, and reveals numbers of sweeps per generation per site in the range of values estimated in Drosophila. Our results confirm the rarity of selective sweeps in humans and show a low contribution of sweeps from standing variation to recent human adaptation.
© The Author(s) 2021. Published by Oxford University Press on behalf of Genetics Society of America. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  ABC; human adaptation; selective sweeps

Mesh:

Year:  2021        PMID: 34849862      PMCID: PMC8664576          DOI: 10.1093/genetics/iyab161

Source DB:  PubMed          Journal:  Genetics        ISSN: 0016-6731            Impact factor:   4.402


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