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Widespread signatures of natural selection across human complex traits and functional genomic categories

Author

Listed:
  • Jian Zeng

    (The University of Queensland)

  • Angli Xue

    (The University of Queensland)

  • Longda Jiang

    (The University of Queensland)

  • Luke R. Lloyd-Jones

    (The University of Queensland)

  • Yang Wu

    (The University of Queensland)

  • Huanwei Wang

    (The University of Queensland)

  • Zhili Zheng

    (The University of Queensland)

  • Loic Yengo

    (The University of Queensland)

  • Kathryn E. Kemper

    (The University of Queensland)

  • Michael E. Goddard

    (University of Melbourne
    Department of Economic Development, Jobs, Transport and Resources)

  • Naomi R. Wray

    (The University of Queensland
    The University of Queensland)

  • Peter M. Visscher

    (The University of Queensland)

  • Jian Yang

    (The University of Queensland
    Westlake University
    Westlake Laboratory of Life Sciences and Biomedicine)

Abstract

Understanding how natural selection has shaped genetic architecture of complex traits is of importance in medical and evolutionary genetics. Bayesian methods have been developed using individual-level GWAS data to estimate multiple genetic architecture parameters including selection signature. Here, we present a method (SBayesS) that only requires GWAS summary statistics. We analyse data for 155 complex traits (n = 27k–547k) and project the estimates onto those obtained from evolutionary simulations. We estimate that, on average across traits, about 1% of human genome sequence are mutational targets with a mean selection coefficient of ~0.001. Common diseases, on average, show a smaller number of mutational targets and have been under stronger selection, compared to other traits. SBayesS analyses incorporating functional annotations reveal that selection signatures vary across genomic regions, among which coding regions have the strongest selection signature and are enriched for both the number of associated variants and the magnitude of effect sizes.

Suggested Citation

  • Jian Zeng & Angli Xue & Longda Jiang & Luke R. Lloyd-Jones & Yang Wu & Huanwei Wang & Zhili Zheng & Loic Yengo & Kathryn E. Kemper & Michael E. Goddard & Naomi R. Wray & Peter M. Visscher & Jian Yang, 2021. "Widespread signatures of natural selection across human complex traits and functional genomic categories," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-21446-3
    DOI: 10.1038/s41467-021-21446-3
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    Cited by:

    1. Ghislain Rocheleau & Shoa L. Clarke & Gaëlle Auguste & Natalie R. Hasbani & Alanna C. Morrison & Adam S. Heath & Lawrence F. Bielak & Kruthika R. Iyer & Erica P. Young & Nathan O. Stitziel & Goo Jun &, 2024. "Rare variant contribution to the heritability of coronary artery disease," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    2. Clara Albiñana & Zhihong Zhu & Nis Borbye-Lorenzen & Sanne Grundvad Boelt & Arieh S. Cohen & Kristin Skogstrand & Naomi R. Wray & Joana A. Revez & Florian Privé & Liselotte V. Petersen & Cynthia M. Bu, 2023. "Genetic correlates of vitamin D-binding protein and 25-hydroxyvitamin D in neonatal dried blood spots," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    3. Michael Wainberg & Natalie J. Forde & Salim Mansour & Isabel Kerrebijn & Sarah E. Medland & Colin Hawco & Shreejoy J. Tripathy, 2024. "Genetic architecture of the structural connectome," Nature Communications, Nature, vol. 15(1), pages 1-20, December.

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