Assessing the evolutionary impact of amino acid mutations in the human genome.

Quantifying the distribution of fitness effects among newly arising mutations in the human genome is key to resolving important debates in medical and evolutionary genetics. Here, we present a method for inferring this distribution using Single Nucleotide Polymorphism (SNP) data from a population wi...

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Main Authors: Adam R Boyko, Scott H Williamson, Amit R Indap, Jeremiah D Degenhardt, Ryan D Hernandez, Kirk E Lohmueller, Mark D Adams, Steffen Schmidt, John J Sninsky, Shamil R Sunyaev, Thomas J White, Rasmus Nielsen, Andrew G Clark, Carlos D Bustamante
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2008-05-01
Series:PLoS Genetics
Online Access:https://journals.plos.org/plosgenetics/article/file?id=10.1371/journal.pgen.1000083&type=printable
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author Adam R Boyko
Scott H Williamson
Amit R Indap
Jeremiah D Degenhardt
Ryan D Hernandez
Kirk E Lohmueller
Mark D Adams
Steffen Schmidt
John J Sninsky
Shamil R Sunyaev
Thomas J White
Rasmus Nielsen
Andrew G Clark
Carlos D Bustamante
author_facet Adam R Boyko
Scott H Williamson
Amit R Indap
Jeremiah D Degenhardt
Ryan D Hernandez
Kirk E Lohmueller
Mark D Adams
Steffen Schmidt
John J Sninsky
Shamil R Sunyaev
Thomas J White
Rasmus Nielsen
Andrew G Clark
Carlos D Bustamante
author_sort Adam R Boyko
collection DOAJ
description Quantifying the distribution of fitness effects among newly arising mutations in the human genome is key to resolving important debates in medical and evolutionary genetics. Here, we present a method for inferring this distribution using Single Nucleotide Polymorphism (SNP) data from a population with non-stationary demographic history (such as that of modern humans). Application of our method to 47,576 coding SNPs found by direct resequencing of 11,404 protein coding-genes in 35 individuals (20 European Americans and 15 African Americans) allows us to assess the relative contribution of demographic and selective effects to patterning amino acid variation in the human genome. We find evidence of an ancient population expansion in the sample with African ancestry and a relatively recent bottleneck in the sample with European ancestry. After accounting for these demographic effects, we find strong evidence for great variability in the selective effects of new amino acid replacing mutations. In both populations, the patterns of variation are consistent with a leptokurtic distribution of selection coefficients (e.g., gamma or log-normal) peaked near neutrality. Specifically, we predict 27-29% of amino acid changing (nonsynonymous) mutations are neutral or nearly neutral (|s|<0.01%), 30-42% are moderately deleterious (0.01%<|s|<1%), and nearly all the remainder are highly deleterious or lethal (|s|>1%). Our results are consistent with 10-20% of amino acid differences between humans and chimpanzees having been fixed by positive selection with the remainder of differences being neutral or nearly neutral. Our analysis also predicts that many of the alleles identified via whole-genome association mapping may be selectively neutral or (formerly) positively selected, implying that deleterious genetic variation affecting disease phenotype may be missed by this widely used approach for mapping genes underlying complex traits.
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spelling doaj-art-7d2e6d340ec24e4a8b1cfd2d5ef74e322025-08-20T03:22:38ZengPublic Library of Science (PLoS)PLoS Genetics1553-73901553-74042008-05-0145e100008310.1371/journal.pgen.1000083Assessing the evolutionary impact of amino acid mutations in the human genome.Adam R BoykoScott H WilliamsonAmit R IndapJeremiah D DegenhardtRyan D HernandezKirk E LohmuellerMark D AdamsSteffen SchmidtJohn J SninskyShamil R SunyaevThomas J WhiteRasmus NielsenAndrew G ClarkCarlos D BustamanteQuantifying the distribution of fitness effects among newly arising mutations in the human genome is key to resolving important debates in medical and evolutionary genetics. Here, we present a method for inferring this distribution using Single Nucleotide Polymorphism (SNP) data from a population with non-stationary demographic history (such as that of modern humans). Application of our method to 47,576 coding SNPs found by direct resequencing of 11,404 protein coding-genes in 35 individuals (20 European Americans and 15 African Americans) allows us to assess the relative contribution of demographic and selective effects to patterning amino acid variation in the human genome. We find evidence of an ancient population expansion in the sample with African ancestry and a relatively recent bottleneck in the sample with European ancestry. After accounting for these demographic effects, we find strong evidence for great variability in the selective effects of new amino acid replacing mutations. In both populations, the patterns of variation are consistent with a leptokurtic distribution of selection coefficients (e.g., gamma or log-normal) peaked near neutrality. Specifically, we predict 27-29% of amino acid changing (nonsynonymous) mutations are neutral or nearly neutral (|s|<0.01%), 30-42% are moderately deleterious (0.01%<|s|<1%), and nearly all the remainder are highly deleterious or lethal (|s|>1%). Our results are consistent with 10-20% of amino acid differences between humans and chimpanzees having been fixed by positive selection with the remainder of differences being neutral or nearly neutral. Our analysis also predicts that many of the alleles identified via whole-genome association mapping may be selectively neutral or (formerly) positively selected, implying that deleterious genetic variation affecting disease phenotype may be missed by this widely used approach for mapping genes underlying complex traits.https://journals.plos.org/plosgenetics/article/file?id=10.1371/journal.pgen.1000083&type=printable
spellingShingle Adam R Boyko
Scott H Williamson
Amit R Indap
Jeremiah D Degenhardt
Ryan D Hernandez
Kirk E Lohmueller
Mark D Adams
Steffen Schmidt
John J Sninsky
Shamil R Sunyaev
Thomas J White
Rasmus Nielsen
Andrew G Clark
Carlos D Bustamante
Assessing the evolutionary impact of amino acid mutations in the human genome.
PLoS Genetics
title Assessing the evolutionary impact of amino acid mutations in the human genome.
title_full Assessing the evolutionary impact of amino acid mutations in the human genome.
title_fullStr Assessing the evolutionary impact of amino acid mutations in the human genome.
title_full_unstemmed Assessing the evolutionary impact of amino acid mutations in the human genome.
title_short Assessing the evolutionary impact of amino acid mutations in the human genome.
title_sort assessing the evolutionary impact of amino acid mutations in the human genome
url https://journals.plos.org/plosgenetics/article/file?id=10.1371/journal.pgen.1000083&type=printable
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