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A structural variation reference for medical and population genetics
Structural variants (SVs) rearrange large segments of DNA(1) and can have profound consequences in evolution and human disease(2,3). As national biobanks, disease-association studies, and clinical genetic testing have grown increasingly reliant on genome sequencing, population references such as the...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7334194/ https://www.ncbi.nlm.nih.gov/pubmed/32461652 http://dx.doi.org/10.1038/s41586-020-2287-8 |
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author | Collins, Ryan L. Brand, Harrison Karczewski, Konrad J. Zhao, Xuefang Alföldi, Jessica Francioli, Laurent C. Khera, Amit V. Lowther, Chelsea Gauthier, Laura D. Wang, Harold Watts, Nicholas A. Solomonson, Matthew O’Donnell-Luria, Anne Baumann, Alexander Munshi, Ruchi Walker, Mark Whelan, Christopher W. Huang, Yongqing Brookings, Ted Sharpe, Ted Stone, Matthew R. Valkanas, Elise Fu, Jack Tiao, Grace Laricchia, Kristen M. Ruano-Rubio, Valentin Stevens, Christine Gupta, Namrata Cusick, Caroline Margolin, Lauren Taylor, Kent D. Lin, Henry J. Rich, Stephen S. Post, Wendy S. Chen, Yii-Der Ida Rotter, Jerome I. Nusbaum, Chad Philippakis, Anthony Lander, Eric Gabriel, Stacey Neale, Benjamin M. Kathiresan, Sekar Daly, Mark J. Banks, Eric MacArthur, Daniel G. Talkowski, Michael E. |
author_facet | Collins, Ryan L. Brand, Harrison Karczewski, Konrad J. Zhao, Xuefang Alföldi, Jessica Francioli, Laurent C. Khera, Amit V. Lowther, Chelsea Gauthier, Laura D. Wang, Harold Watts, Nicholas A. Solomonson, Matthew O’Donnell-Luria, Anne Baumann, Alexander Munshi, Ruchi Walker, Mark Whelan, Christopher W. Huang, Yongqing Brookings, Ted Sharpe, Ted Stone, Matthew R. Valkanas, Elise Fu, Jack Tiao, Grace Laricchia, Kristen M. Ruano-Rubio, Valentin Stevens, Christine Gupta, Namrata Cusick, Caroline Margolin, Lauren Taylor, Kent D. Lin, Henry J. Rich, Stephen S. Post, Wendy S. Chen, Yii-Der Ida Rotter, Jerome I. Nusbaum, Chad Philippakis, Anthony Lander, Eric Gabriel, Stacey Neale, Benjamin M. Kathiresan, Sekar Daly, Mark J. Banks, Eric MacArthur, Daniel G. Talkowski, Michael E. |
author_sort | Collins, Ryan L. |
collection | PubMed |
description | Structural variants (SVs) rearrange large segments of DNA(1) and can have profound consequences in evolution and human disease(2,3). As national biobanks, disease-association studies, and clinical genetic testing have grown increasingly reliant on genome sequencing, population references such as the Genome Aggregation Database (gnomAD)(4) have become integral in the interpretation of single-nucleotide variants (SNVs)(5). However, there are no reference maps of SVs from high-coverage genome sequencing comparable to those for SNVs. Here we present a reference of sequence-resolved SVs constructed from 14,891 genomes across diverse global populations (54% non-European) in gnomAD. We discovered a rich and complex landscape of 433,371 SVs, from which we estimate that SVs are responsible for 25–29% of all rare protein-truncating events per genome. We found strong correlations between natural selection against damaging SNVs and rare SVs that disrupt or duplicate protein-coding sequence, which suggests that genes that are highly intolerant to loss-of-function are also sensitive to increased dosage(6). We also uncovered modest selection against noncoding SVs in cis-regulatory elements, although selection against protein-truncating SVs was stronger than all noncoding effects. Finally, we identified very large (over one megabase), rare SVs in 3.9% of samples, and estimate that 0.13% of individuals may carry an SV that meets the existing criteria for clinically important incidental findings(7). This SV resource is freely distributed via the gnomAD browser(8) and will have broad utility in population genetics, disease-association studies, and diagnostic screening. |
format | Online Article Text |
id | pubmed-7334194 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-73341942020-07-10 A structural variation reference for medical and population genetics Collins, Ryan L. Brand, Harrison Karczewski, Konrad J. Zhao, Xuefang Alföldi, Jessica Francioli, Laurent C. Khera, Amit V. Lowther, Chelsea Gauthier, Laura D. Wang, Harold Watts, Nicholas A. Solomonson, Matthew O’Donnell-Luria, Anne Baumann, Alexander Munshi, Ruchi Walker, Mark Whelan, Christopher W. Huang, Yongqing Brookings, Ted Sharpe, Ted Stone, Matthew R. Valkanas, Elise Fu, Jack Tiao, Grace Laricchia, Kristen M. Ruano-Rubio, Valentin Stevens, Christine Gupta, Namrata Cusick, Caroline Margolin, Lauren Taylor, Kent D. Lin, Henry J. Rich, Stephen S. Post, Wendy S. Chen, Yii-Der Ida Rotter, Jerome I. Nusbaum, Chad Philippakis, Anthony Lander, Eric Gabriel, Stacey Neale, Benjamin M. Kathiresan, Sekar Daly, Mark J. Banks, Eric MacArthur, Daniel G. Talkowski, Michael E. Nature Article Structural variants (SVs) rearrange large segments of DNA(1) and can have profound consequences in evolution and human disease(2,3). As national biobanks, disease-association studies, and clinical genetic testing have grown increasingly reliant on genome sequencing, population references such as the Genome Aggregation Database (gnomAD)(4) have become integral in the interpretation of single-nucleotide variants (SNVs)(5). However, there are no reference maps of SVs from high-coverage genome sequencing comparable to those for SNVs. Here we present a reference of sequence-resolved SVs constructed from 14,891 genomes across diverse global populations (54% non-European) in gnomAD. We discovered a rich and complex landscape of 433,371 SVs, from which we estimate that SVs are responsible for 25–29% of all rare protein-truncating events per genome. We found strong correlations between natural selection against damaging SNVs and rare SVs that disrupt or duplicate protein-coding sequence, which suggests that genes that are highly intolerant to loss-of-function are also sensitive to increased dosage(6). We also uncovered modest selection against noncoding SVs in cis-regulatory elements, although selection against protein-truncating SVs was stronger than all noncoding effects. Finally, we identified very large (over one megabase), rare SVs in 3.9% of samples, and estimate that 0.13% of individuals may carry an SV that meets the existing criteria for clinically important incidental findings(7). This SV resource is freely distributed via the gnomAD browser(8) and will have broad utility in population genetics, disease-association studies, and diagnostic screening. Nature Publishing Group UK 2020-05-27 2020 /pmc/articles/PMC7334194/ /pubmed/32461652 http://dx.doi.org/10.1038/s41586-020-2287-8 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Collins, Ryan L. Brand, Harrison Karczewski, Konrad J. Zhao, Xuefang Alföldi, Jessica Francioli, Laurent C. Khera, Amit V. Lowther, Chelsea Gauthier, Laura D. Wang, Harold Watts, Nicholas A. Solomonson, Matthew O’Donnell-Luria, Anne Baumann, Alexander Munshi, Ruchi Walker, Mark Whelan, Christopher W. Huang, Yongqing Brookings, Ted Sharpe, Ted Stone, Matthew R. Valkanas, Elise Fu, Jack Tiao, Grace Laricchia, Kristen M. Ruano-Rubio, Valentin Stevens, Christine Gupta, Namrata Cusick, Caroline Margolin, Lauren Taylor, Kent D. Lin, Henry J. Rich, Stephen S. Post, Wendy S. Chen, Yii-Der Ida Rotter, Jerome I. Nusbaum, Chad Philippakis, Anthony Lander, Eric Gabriel, Stacey Neale, Benjamin M. Kathiresan, Sekar Daly, Mark J. Banks, Eric MacArthur, Daniel G. Talkowski, Michael E. A structural variation reference for medical and population genetics |
title | A structural variation reference for medical and population genetics |
title_full | A structural variation reference for medical and population genetics |
title_fullStr | A structural variation reference for medical and population genetics |
title_full_unstemmed | A structural variation reference for medical and population genetics |
title_short | A structural variation reference for medical and population genetics |
title_sort | structural variation reference for medical and population genetics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7334194/ https://www.ncbi.nlm.nih.gov/pubmed/32461652 http://dx.doi.org/10.1038/s41586-020-2287-8 |
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