A structural variation reference for medical and population genetics

Ryan L. Collins, Harrison Brand, Konrad J. Karczewski, Xuefang Zhao, Jessica Alföldi, Laurent C. Francioli, Amit V. Khera, Chelsea Lowther, Laura D. Gauthier, Harold Wang, Nicholas A. Watts, Matthew Solomonson, Anne O’Donnell-Luria, Alexander Baumann, Ruchi Munshi, Mark Walker, Christopher W. Whelan, Yongqing Huang, Ted Brookings, Ted Sharpe, Matthew R. Stone, Elise Valkanas, Jack Fu, Grace Tiao, Kristen M. Laricchia, Valentin Ruano-Rubio, Christine Stevens, Namrata Gupta, Caroline Cusick, Lauren Margolin, Kent D. Taylor, Henry J. Lin, Stephen S. Rich, Wendy S. Post, Yii- Der Ida Chen, Jerome I. Rotter, Chad Nusbaum, Anthony Philippakis, Eric Lander, Stacey Gabriel, Benjamin M. Neale, Sekar Kathiresan, Mark J. Daly, Eric Banks, Daniel G. MacArthur and Michael E. Talkowski ()
Additional contact information
Ryan L. Collins: Broad Institute of MIT and Harvard
Harrison Brand: Broad Institute of MIT and Harvard
Konrad J. Karczewski: Broad Institute of MIT and Harvard
Xuefang Zhao: Broad Institute of MIT and Harvard
Jessica Alföldi: Broad Institute of MIT and Harvard
Laurent C. Francioli: Broad Institute of MIT and Harvard
Amit V. Khera: Broad Institute of MIT and Harvard
Chelsea Lowther: Broad Institute of MIT and Harvard
Laura D. Gauthier: Broad Institute of MIT and Harvard
Harold Wang: Broad Institute of MIT and Harvard
Nicholas A. Watts: Broad Institute of MIT and Harvard
Matthew Solomonson: Broad Institute of MIT and Harvard
Anne O’Donnell-Luria: Broad Institute of MIT and Harvard
Alexander Baumann: Broad Institute of MIT and Harvard
Ruchi Munshi: Broad Institute of MIT and Harvard
Mark Walker: Broad Institute of MIT and Harvard
Christopher W. Whelan: Broad Institute of MIT and Harvard
Yongqing Huang: Broad Institute of MIT and Harvard
Ted Brookings: Broad Institute of MIT and Harvard
Ted Sharpe: Broad Institute of MIT and Harvard
Matthew R. Stone: Broad Institute of MIT and Harvard
Elise Valkanas: Broad Institute of MIT and Harvard
Jack Fu: Broad Institute of MIT and Harvard
Grace Tiao: Broad Institute of MIT and Harvard
Kristen M. Laricchia: Broad Institute of MIT and Harvard
Valentin Ruano-Rubio: Broad Institute of MIT and Harvard
Christine Stevens: Broad Institute of MIT and Harvard
Namrata Gupta: Broad Institute of MIT and Harvard
Caroline Cusick: Broad Institute of MIT and Harvard
Lauren Margolin: Broad Institute of MIT and Harvard
Kent D. Taylor: Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center
Henry J. Lin: Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center
Stephen S. Rich: University of Virginia
Wendy S. Post: Johns Hopkins University School of Medicine
Yii- Der Ida Chen: Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center
Jerome I. Rotter: Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center
Chad Nusbaum: Broad Institute of MIT and Harvard
Anthony Philippakis: Broad Institute of MIT and Harvard
Eric Lander: Broad Institute of MIT and Harvard
Stacey Gabriel: Broad Institute of MIT and Harvard
Benjamin M. Neale: Broad Institute of MIT and Harvard
Sekar Kathiresan: Broad Institute of MIT and Harvard
Mark J. Daly: Broad Institute of MIT and Harvard
Eric Banks: Broad Institute of MIT and Harvard
Daniel G. MacArthur: Broad Institute of MIT and Harvard
Michael E. Talkowski: Broad Institute of MIT and Harvard

Nature, 2020, vol. 581, issue 7809, 444-451

Abstract: Abstract Structural variants (SVs) rearrange large segments of DNA1 and can have profound consequences in evolution and human disease2,3. 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 dosage6. 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 findings7. This SV resource is freely distributed via the gnomAD browser8 and will have broad utility in population genetics, disease-association studies, and diagnostic screening.

Date: 2020
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Citations: View citations in EconPapers (17)

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DOI: 10.1038/s41586-020-2287-8

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