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Quantification of frequency-dependent genetic architectures in 25 UK Biobank traits reveals action of negative selection
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 eff...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6377669/ https://www.ncbi.nlm.nih.gov/pubmed/30770844 http://dx.doi.org/10.1038/s41467-019-08424-6 |
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author | Schoech, Armin P. Jordan, Daniel M. Loh, Po-Ru Gazal, Steven O’Connor, Luke J. Balick, Daniel J. Palamara, Pier F. Finucane, Hilary K. Sunyaev, Shamil R. Price, Alkes L. |
author_facet | Schoech, Armin P. Jordan, Daniel M. Loh, Po-Ru Gazal, Steven O’Connor, Luke J. Balick, Daniel J. Palamara, Pier F. Finucane, Hilary K. Sunyaev, Shamil R. Price, Alkes L. |
author_sort | Schoech, Armin P. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6377669 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-63776692019-02-19 Quantification of frequency-dependent genetic architectures in 25 UK Biobank traits reveals action of negative selection Schoech, Armin P. Jordan, Daniel M. Loh, Po-Ru Gazal, Steven O’Connor, Luke J. Balick, Daniel J. Palamara, Pier F. Finucane, Hilary K. Sunyaev, Shamil R. Price, Alkes L. Nat Commun Article 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. Nature Publishing Group UK 2019-02-15 /pmc/articles/PMC6377669/ /pubmed/30770844 http://dx.doi.org/10.1038/s41467-019-08424-6 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Schoech, Armin P. Jordan, Daniel M. Loh, Po-Ru Gazal, Steven O’Connor, Luke J. Balick, Daniel J. Palamara, Pier F. Finucane, Hilary K. Sunyaev, Shamil R. Price, Alkes L. Quantification of frequency-dependent genetic architectures in 25 UK Biobank traits reveals action of negative selection |
title | Quantification of frequency-dependent genetic architectures in 25 UK Biobank traits reveals action of negative selection |
title_full | Quantification of frequency-dependent genetic architectures in 25 UK Biobank traits reveals action of negative selection |
title_fullStr | Quantification of frequency-dependent genetic architectures in 25 UK Biobank traits reveals action of negative selection |
title_full_unstemmed | Quantification of frequency-dependent genetic architectures in 25 UK Biobank traits reveals action of negative selection |
title_short | Quantification of frequency-dependent genetic architectures in 25 UK Biobank traits reveals action of negative selection |
title_sort | quantification of frequency-dependent genetic architectures in 25 uk biobank traits reveals action of negative selection |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6377669/ https://www.ncbi.nlm.nih.gov/pubmed/30770844 http://dx.doi.org/10.1038/s41467-019-08424-6 |
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