Submitted by ja607 on
Title | Quantification of frequency-dependent genetic architectures in 25 UK Biobank traits reveals action of negative selection. |
Publication Type | Journal Article |
Year of Publication | 2019 |
Authors | Schoech, AP, Jordan, DM, Loh, P-R, Gazal, S, O'Connor, LJ, Balick, DJ, Palamara, PF, Finucane, HK, Sunyaev, SR, Price, AL |
Journal | Nat Commun |
Volume | 10 |
Issue | 1 |
Pagination | 790 |
Date Published | 2019 02 15 |
ISSN | 2041-1723 |
Keywords | Algorithms, Alleles, Biological Specimen Banks, Gene Frequency, Genome-Wide Association Study, Genotype, Humans, Models, Genetic, Polymorphism, Single Nucleotide, Quantitative Trait, Heritable, Selection, Genetic, United Kingdom |
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)], 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. |
DOI | 10.1038/s41467-019-08424-6 |
Alternate Journal | Nat Commun |
PubMed ID | 30770844 |
PubMed Central ID | PMC6377669 |
Grant List | MC_QA137853 / / Medical Research Council / United Kingdom R01 MH101244 / MH / NIMH NIH HHS / United States U01 HG009088 / HG / NHGRI NIH HHS / United States |