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The Impact of Purifying and Background Selection on the Inference of Population History: Problems and Prospects

Current procedures for inferring population history generally assume complete neutrality—that is, they neglect both direct selection and the effects of selection on linked sites. We here examine how the presence of direct purifying selection and background selection may bias demographic inference by...

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Autores principales: Johri, Parul, Riall, Kellen, Becher, Hannes, Excoffier, Laurent, Charlesworth, Brian, Jensen, Jeffrey D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8233493/
https://www.ncbi.nlm.nih.gov/pubmed/33591322
http://dx.doi.org/10.1093/molbev/msab050
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author Johri, Parul
Riall, Kellen
Becher, Hannes
Excoffier, Laurent
Charlesworth, Brian
Jensen, Jeffrey D.
author_facet Johri, Parul
Riall, Kellen
Becher, Hannes
Excoffier, Laurent
Charlesworth, Brian
Jensen, Jeffrey D.
author_sort Johri, Parul
collection PubMed
description Current procedures for inferring population history generally assume complete neutrality—that is, they neglect both direct selection and the effects of selection on linked sites. We here examine how the presence of direct purifying selection and background selection may bias demographic inference by evaluating two commonly-used methods (MSMC and fastsimcoal2), specifically studying how the underlying shape of the distribution of fitness effects and the fraction of directly selected sites interact with demographic parameter estimation. The results show that, even after masking functional genomic regions, background selection may cause the mis-inference of population growth under models of both constant population size and decline. This effect is amplified as the strength of purifying selection and the density of directly selected sites increases, as indicated by the distortion of the site frequency spectrum and levels of nucleotide diversity at linked neutral sites. We also show how simulated changes in background selection effects caused by population size changes can be predicted analytically. We propose a potential method for correcting for the mis-inference of population growth caused by selection. By treating the distribution of fitness effect as a nuisance parameter and averaging across all potential realizations, we demonstrate that even directly selected sites can be used to infer demographic histories with reasonable accuracy.
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spelling pubmed-82334932021-06-28 The Impact of Purifying and Background Selection on the Inference of Population History: Problems and Prospects Johri, Parul Riall, Kellen Becher, Hannes Excoffier, Laurent Charlesworth, Brian Jensen, Jeffrey D. Mol Biol Evol Methods Current procedures for inferring population history generally assume complete neutrality—that is, they neglect both direct selection and the effects of selection on linked sites. We here examine how the presence of direct purifying selection and background selection may bias demographic inference by evaluating two commonly-used methods (MSMC and fastsimcoal2), specifically studying how the underlying shape of the distribution of fitness effects and the fraction of directly selected sites interact with demographic parameter estimation. The results show that, even after masking functional genomic regions, background selection may cause the mis-inference of population growth under models of both constant population size and decline. This effect is amplified as the strength of purifying selection and the density of directly selected sites increases, as indicated by the distortion of the site frequency spectrum and levels of nucleotide diversity at linked neutral sites. We also show how simulated changes in background selection effects caused by population size changes can be predicted analytically. We propose a potential method for correcting for the mis-inference of population growth caused by selection. By treating the distribution of fitness effect as a nuisance parameter and averaging across all potential realizations, we demonstrate that even directly selected sites can be used to infer demographic histories with reasonable accuracy. Oxford University Press 2021-02-16 /pmc/articles/PMC8233493/ /pubmed/33591322 http://dx.doi.org/10.1093/molbev/msab050 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methods
Johri, Parul
Riall, Kellen
Becher, Hannes
Excoffier, Laurent
Charlesworth, Brian
Jensen, Jeffrey D.
The Impact of Purifying and Background Selection on the Inference of Population History: Problems and Prospects
title The Impact of Purifying and Background Selection on the Inference of Population History: Problems and Prospects
title_full The Impact of Purifying and Background Selection on the Inference of Population History: Problems and Prospects
title_fullStr The Impact of Purifying and Background Selection on the Inference of Population History: Problems and Prospects
title_full_unstemmed The Impact of Purifying and Background Selection on the Inference of Population History: Problems and Prospects
title_short The Impact of Purifying and Background Selection on the Inference of Population History: Problems and Prospects
title_sort impact of purifying and background selection on the inference of population history: problems and prospects
topic Methods
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8233493/
https://www.ncbi.nlm.nih.gov/pubmed/33591322
http://dx.doi.org/10.1093/molbev/msab050
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