Evidence map›Paper›PMID 23201682›Full record

ArticleNature2013

Analysis of 6,515 exomes reveals the recent origin of most human protein-coding variants.

Wenqing Fu, Timothy D O'Connor, Goo Jun, Hyun Min Kang, Goncalo Abecasis, Suzanne M Leal, Stacey Gabriel, Mark J Rieder, David Altshuler, Jay Shendure and 4 more

Erratum issuedAbstract read
In one paragraph

Article in Nature, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 610 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
610citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

610 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. A Systematic Literature Review of Whole Exome and Genome Sequencing Population Studies of Genetic Susceptibility to Cancer.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020
    Pooled it
  3. Trial
  4. Article
  5. Article
  6. Article
  7. Integrated mapping resolves pathogenicity of 11Journal of the Endocrine Society · 2026
    Article
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  15. Article
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  18. Article
  19. Review
  20. The Performance ofHuman mutation · 2026
    Article

550 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors.

Wenqing FuDepartment of Genome Sciences, University of Washington, Seattle, Washington 98195, USA. wqfu@u.washington.edu
Timothy D O'Connor
Goo Jun
Hyun Min Kang
Goncalo Abecasis
Suzanne M Leal
Stacey Gabriel
Mark J Rieder
David Altshuler
Jay Shendure
Deborah A Nickerson
Michael J Bamshad
NHLBI Exome Sequencing Project
Joshua M Akey

Funding

Northwest Genomics CenterRC2HL102926 · NHLBI · UNIVERSITY OF WASHINGTON · PI GREEN, PHILIP P, NICKERSON, DEBORAH A · 2009 to 2009
$11.0M
Comprehensive Sequencing and Analysis of Variation in NHLBI CohortsRC2HL102925 · NHLBI · BROAD INSTITUTE, INC. · PI ALTSHULER, DAVID, GABRIEL, STACEY · 2009 to 2009
$10.2M
Robust Software Tools for Variant Identification and Functional AssessmentU01HG006513 · NHGRI · UNIVERSITY OF UTAH · PI ABECASIS, GONCALO, MARTH, GABOR T · 2012 to 2015
$4.2M
ARRA - NHLBI Lung Cohorts Sequencing ProjectRC2HL102923 · NHLBI · UNIVERSITY OF WASHINGTON · PI BAMSHAD, MICHAEL JOSEPH, BARNES, KATHLEEN C · 2009 to 2009
$2.6M
WHI Sequencing Project (WHISP)RC2HL102924 · NHLBI · OHIO STATE UNIVERSITY · PI CARLSON, CHRISTOPHER S, JACKSON, REBECCA D · 2009 to 2009
$2.1M
Human Exome Sequencing in Six Well-Phenotyped NHLBI CohortsRC2HL103010 · NHLBI · UNIVERSITY OF VIRGINIA · PI RICH, STEPHEN S. · 2009 to 2009
$817k
NHGRI NIH HHS U01 HG006513NHLBI NIH HHS RC2 HL-102923NHLBI NIH HHS RC2 HL102923NHLBI NIH HHS RC2 HL-102924NHLBI NIH HHS RC2 HL102924NHLBI NIH HHS RC2 HL102925NHLBI NIH HHS RC2HL-102925NHLBI NIH HHS RC2 HL-102926NHLBI NIH HHS RC2 HL102926NHLBI NIH HHS RC2 HL-103010NHLBI NIH HHS RC2 HL103010Wellcome Trust 090532
6 · The paper itself

Abstract

Establishing the age of each mutation segregating in contemporary human populations is important to fully understand our evolutionary history and will help to facilitate the development of new approaches for disease-gene discovery. Large-scale surveys of human genetic variation have reported signatures of recent explosive population growth, notable for an excess of rare genetic variants, suggesting that many mutations arose recently. To more quantitatively assess the distribution of mutation ages, we resequenced 15,336 genes in 6,515 individuals of European American and African American ancestry and inferred the age of 1,146,401 autosomal single nucleotide variants (SNVs). We estimate that approximately 73% of all protein-coding SNVs and approximately 86% of SNVs predicted to be deleterious arose in the past 5,000-10,000 years. The average age of deleterious SNVs varied significantly across molecular pathways, and disease genes contained a significantly higher proportion of recently arisen deleterious SNVs than other genes. Furthermore, European Americans had an excess of deleterious variants in essential and Mendelian disease genes compared to African Americans, consistent with weaker purifying selection due to the Out-of-Africa dispersal. Our results better delimit the historical details of human protein-coding variation, show the profound effect of recent human history on the burden of deleterious SNVs segregating in contemporary populations, and provide important practical information that can be used to prioritize variants in disease-gene discovery.

Indexed as

Evolution, MolecularAfricaAllelesBlack or African AmericanBlack PeopleEuropeExomeExonsGenetic VariationHumansOpen Reading FramesPolymorphism, Single NucleotideUnited StatesWhite People

Identifiers

PMID23201682
PMCPMC3676746

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.