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The contribution of gene flow, selection, and genetic drift to five thousand years of human allele frequency change
Genomic time-series from experimental evolution studies and ancient DNA datasets offer us a chance to more directly observe the interplay of various evolutionary forces. Here we show how the genome-wide variance in allele frequency change between two time points can be decomposed into the contributi...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10370008/ https://www.ncbi.nlm.nih.gov/pubmed/37503227 http://dx.doi.org/10.1101/2023.07.11.548607 |
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author | Simon, Alexis Coop, Graham |
author_facet | Simon, Alexis Coop, Graham |
author_sort | Simon, Alexis |
collection | PubMed |
description | Genomic time-series from experimental evolution studies and ancient DNA datasets offer us a chance to more directly observe the interplay of various evolutionary forces. Here we show how the genome-wide variance in allele frequency change between two time points can be decomposed into the contributions of gene flow, genetic drift, and linked selection. In closed populations, the contribution of linked selection is identifiable because it creates covariances between time intervals, and genetic drift does not. However, repeated gene flow between populations can also produce directionality in allele frequency change, creating covariances. We show how to accurately separate the fraction of variance in allele frequency change due to admixture and linked selection in a population receiving gene flow. We use two human ancient DNA datasets, spanning around 5,000 years, as time transects to quantify the contributions to the genome-wide variance in allele frequency change. We find that a large fraction of genome-wide allele frequency change is due to gene flow. In both cases, after correcting for known major gene flow events in those populations, we do not observe a signal of genome-wide linked selection. Thus despite the known role of selection in shaping long-term polymorphism levels, and an increasing number of examples of strong selection on single loci and polygenic scores from ancient DNA, it appears to be gene flow and drift, and not selection, that are the main determinants of recent genome-wide allele frequency change. Our approach should be applicable to the growing number of contemporary and ancient temporal population genomics datasets. |
format | Online Article Text |
id | pubmed-10370008 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-103700082023-07-27 The contribution of gene flow, selection, and genetic drift to five thousand years of human allele frequency change Simon, Alexis Coop, Graham bioRxiv Article Genomic time-series from experimental evolution studies and ancient DNA datasets offer us a chance to more directly observe the interplay of various evolutionary forces. Here we show how the genome-wide variance in allele frequency change between two time points can be decomposed into the contributions of gene flow, genetic drift, and linked selection. In closed populations, the contribution of linked selection is identifiable because it creates covariances between time intervals, and genetic drift does not. However, repeated gene flow between populations can also produce directionality in allele frequency change, creating covariances. We show how to accurately separate the fraction of variance in allele frequency change due to admixture and linked selection in a population receiving gene flow. We use two human ancient DNA datasets, spanning around 5,000 years, as time transects to quantify the contributions to the genome-wide variance in allele frequency change. We find that a large fraction of genome-wide allele frequency change is due to gene flow. In both cases, after correcting for known major gene flow events in those populations, we do not observe a signal of genome-wide linked selection. Thus despite the known role of selection in shaping long-term polymorphism levels, and an increasing number of examples of strong selection on single loci and polygenic scores from ancient DNA, it appears to be gene flow and drift, and not selection, that are the main determinants of recent genome-wide allele frequency change. Our approach should be applicable to the growing number of contemporary and ancient temporal population genomics datasets. Cold Spring Harbor Laboratory 2023-07-11 /pmc/articles/PMC10370008/ /pubmed/37503227 http://dx.doi.org/10.1101/2023.07.11.548607 Text en https://creativecommons.org/licenses/by-nc/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (https://creativecommons.org/licenses/by-nc/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Simon, Alexis Coop, Graham The contribution of gene flow, selection, and genetic drift to five thousand years of human allele frequency change |
title | The contribution of gene flow, selection, and genetic drift to five thousand years of human allele frequency change |
title_full | The contribution of gene flow, selection, and genetic drift to five thousand years of human allele frequency change |
title_fullStr | The contribution of gene flow, selection, and genetic drift to five thousand years of human allele frequency change |
title_full_unstemmed | The contribution of gene flow, selection, and genetic drift to five thousand years of human allele frequency change |
title_short | The contribution of gene flow, selection, and genetic drift to five thousand years of human allele frequency change |
title_sort | contribution of gene flow, selection, and genetic drift to five thousand years of human allele frequency change |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10370008/ https://www.ncbi.nlm.nih.gov/pubmed/37503227 http://dx.doi.org/10.1101/2023.07.11.548607 |
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