Quantification of frequency-dependent genetic architectures in 25 UK Biobank traits reveals action of negative selection View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-12

AUTHORS

Armin P. Schoech, Daniel M. Jordan, Po-Ru Loh, Steven Gazal, Luke J. O’Connor, Daniel J. Balick, Pier F. Palamara, Hilary K. Finucane, Shamil R. Sunyaev, Alkes L. Price

ABSTRACT

Understanding the role of rare variants is important in elucidating the genetic basis of human disease. Negative selection can cause rare variants to have larger per-allele effect sizes than common variants. Here, we develop a method to estimate the minor allele frequency (MAF) dependence of SNP effect sizes. We use a model in which per-allele effect sizes have variance proportional to [p(1 - p)]α, where p is the MAF and negative values of α imply larger effect sizes for rare variants. We estimate α for 25 UK Biobank diseases and complex traits. All traits produce negative α estimates, with best-fit mean of -0.38 (s.e. 0.02) across traits. Despite larger rare variant effect sizes, rare variants (MAF < 1%) explain less than 10% of total SNP-heritability for most traits analyzed. Using evolutionary modeling and forward simulations, we validate the α model of MAF-dependent trait effects and assess plausible values of relevant evolutionary parameters. More... »

PAGES

790

References to SciGraph publications

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s41467-019-08424-6

    DOI

    http://dx.doi.org/10.1038/s41467-019-08424-6

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1112165466

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/30770844


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