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A structural variation reference for medical and population genetics

Authors :
Harold Z. Wang
Yii-Der Ida Chen
Elise Valkanas
Michael E. Talkowski
Kent D. Taylor
Xuefang Zhao
Henry J. Lin
Konrad J. Karczewski
Ryan L. Collins
Eric Banks
Benjamin M. Neale
Lauren Margolin
Christopher W. Whelan
Valentin Ruano-Rubio
Laura D. Gauthier
Stacey Gabriel
Harrison Brand
Namrata Gupta
Jessica Alföldi
Ruchi Munshi
Yongqing Huang
Daniel G. MacArthur
Laurent C. Francioli
Chad Nusbaum
Eric S. Lander
Mark J. Daly
Nicholas A. Watts
Anthony A. Philippakis
Matthew Solomonson
Sekar Kathiresan
Genome Aggregation Database Production Team
Wendy S. Post
Jack Fu
Alexander Baumann
Kristen M. Laricchia
Amit Khera
Ted Brookings
Anne H. O’Donnell-Luria
Jerome I. Rotter
Matthew R. Stone
Chelsea Lowther
Christine Stevens
Caroline N. Cusick
Ted Sharpe
Grace Tiao
Stephen S. Rich
Mark Walker
Tampere University
Clinical Medicine
Department of Clinical Chemistry
Centre of Excellence in Complex Disease Genetics
HUS Abdominal Center
Department of Medicine
Clinicum
Gastroenterologian yksikkö
Institute for Molecular Medicine Finland
HUS Psychiatry
Department of Psychiatry
Department of Public Health
Helsinki Institute of Life Science HiLIFE
Aarno Palotie / Principal Investigator
Genomics of Neurological and Neuropsychiatric Disorders
Samuli Olli Ripatti / Principal Investigator
Complex Disease Genetics
Biostatistics Helsinki
Biosciences
HUS Neurocenter
Department of Neurosciences
Neurologian yksikkö
Source :
Nature, vol 581, iss 7809, Nature
Publication Year :
2020
Publisher :
eScholarship, University of California, 2020.

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.<br />A large empirical assessment of sequence-resolved structural variants from 14,891 genomes across diverse global populations in the Genome Aggregation Database (gnomAD) provides a reference map for disease-association studies, population genetics, and diagnostic screening.

Details

Database :
OpenAIRE
Journal :
Nature, vol 581, iss 7809, Nature
Accession number :
edsair.doi.dedup.....a5850f851436ab9954eeebae9e54903b