Widespread signatures of natural selection across human complex traits and functional genomic categories
Open accessAbstract
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.
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Background selection appears to play a primary role in shaping the highly polygenic architecture of human traits and diseases.
“In particular, background selection (i.e., the selective removal of deleterious alleles across the genome) appears to play a primary role in shaping the highly polygenic architecture of human traits and diseases [1, 7–9].”
From Denisovan and Neanderthal archaic introgression differentially impacted the genetics of complex traits in modern populations (2022) · cites this paper as [8]
The Discussion (page unavailable) says that negative selection removes large-effect causal variants and linked SNPs, identifying this as background selection, and that selection strength affects polygenicity. It also says polygenicity is driven by both selection strength and mutational target size; it does not establish background selection as the primary driver of the highly polygenic architecture of human traits and diseases. (LLM, conf=0.84)
Experimental — accuracy not yet measuredGenomic features related to natural selection are enriched for loci associated with complex traits.
“Genomic features related to natural selection are enriched for loci associated with complex traits [1, 7–9].”
From Denisovan and Neanderthal archaic introgression differentially impacted the genetics of complex traits in modern populations (2022) · cites this paper as [8]
In the European-ancestry sample, SNP-based heritability was estimated to be 0.24 with SE 0.007.
“In the EUR sample, the SNP-based heritability (h2SNP) (i.e. proportion of variance in liability attributable to all measured SNPs) was estimated13 to be 0.24 (SE 0.007).”
From Mapping genomic loci implicates genes and synaptic biology in schizophrenia (2022) · cites this paper as [13]
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References 58 · Cited by 144
Research works printed but not linked: 1
- [49]Marquez-Luna, C. et al. Modeling functional enrichment improves polygenic prediction accuracy in UK Biobank and 23andMe data sets. Preprint at bioRxiv10.1101/375337 (2020).
- Authors
- Zeng, J., Xue, A., Jiang, L., Lloyd-Jones, L. R., Wu, Y., Wang, H., Zheng, Z., Yengo, L., Kemper, K. E., Goddard, M. E., Wray, N. R., Visscher, P. M., & Yang, J.
- Affiliations
- The University of Queensland (AU)
- The University of Melbourne (AU)
- Corresponding author
- Zeng, Jian
- Yang, Jian
- ORCID
- Venue
- Nature Communications
- Published
- 2021-02-19
- Volume
- 12
- Issue
- 1
- Pages
- 1164-1164
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC7896067
- OpenAlex
- W3131856571
- Cited by
- 144
- References
- 58
- Citations by year
- 2026: 30 · 2025: 34 · 2024: 28 · 2023: 21 · 2022: 15 · 2021: 13 · 2020: 3
- FWCI
- 10.86
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Minerva Access (University of Melbourne) (submittedVersion, cc-by)
- Funders
- Department of Education and Training | Australian Research Council (FT180100186)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
- Keywords
- natural selection, selection signatures, complex traits, genetic architecture, selection coefficients, common diseases, functional genomic annotation, coding sequences, GWAS summary statistics, evolutionary simulation
- MeSH terms
- Bayes Theorem, Humans, Models, Biological, Phenotype, Selection, Genetic, Genetic Variation, Genome, Evolution, Molecular, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Genomics, Genome-Wide Association Study
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