A structural variation reference for medical and population genetics
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Collins, Ryan | Brand, Harrison | Karczewski, Konrad | Zhao, Xuefang | Alföldi, Jessica | Francioli, Laurent | Khera, Amit | Lowther, Chelsea | Gauthier, Laura | Wang, Harold | Watts, Nicholas | Solomonson, Matthew | O’donnell-Luria, Anne | Baumann, Alexander | Munshi, Ruchi | Walker, Mark | Whelan, Christopher | Huang, Yongqing | Brookings, Ted | Sharpe, Ted | Stone, Matthew | Valkanas, Elise | Fu, Jack | Tiao, Grace | Laricchia, Kristen | Ruano-Rubio, Valentin | Stevens, Christine | Gupta, Namrata | Cusick, Caroline | Margolin, Lauren | Armean, Irina | Banks, Eric | Bergelson, Louis | Cibulskis, Kristian | Connolly, Kristen | Covarrubias, Miguel | Cummings, Beryl | Daly, Mark | Donnelly, Stacey | Farjoun, Yossi | Ferriera, Steven | Gabriel, Stacey | Gentry, Jeff | Jeandet, Thibault | Kaplan, Diane | Llanwarne, Christopher | Minikel, Eric | Neale, Benjamin | Novod, Sam | Petrillo, Nikelle | Poterba, Timothy | Roazen, David | Saltzman, Andrea | Samocha, Kaitlin | Schleicher, Molly | Seed, Cotton | Soto, Jose | Tibbetts, Kathleen | Tolonen, Charlotte | Vittal, Christopher | Wade, Gordon | Wang, Arcturus | Wang, Qingbo | Ware, James | Weisburd, Ben | Whiffin, Nicola | Salinas, Carlos | Ahmad, Tariq | Albert, Christine | Ardissino, Diego | Atzmon, Gil | Barnard, John | Beaugerie, Laurent | Benjamin, Emelia | Boehnke, Michael | Bonnycastle, Lori | Bottinger, Erwin | Bowden, Donald | Bown, Matthew | Chambers, John | Chan, Juliana | Chasman, Daniel | Cho, Judy | Chung, Mina | Cohen, Bruce | Correa, Adolfo | Dabelea, Dana | Darbar, Dawood | Duggirala, Ravindranath | Dupuis, Josée | Ellinor, Patrick | Elosua, Roberto | Erdmann, Jeanette | Esko, Tõnu | Färkkilä, Martti | Florez, Jose | Franke, Andre | Getz, Gad | Glaser, Benjamin | Glatt, Stephen | Goldstein, David | Gonzalez, Clicerio | Groop, Leif | Haiman, Christopher | Hanis, Craig | Harms, Matthew | Hiltunen, Mikko | Holi, Matti | Hultman, Christina | Kallela, Mikko | Kaprio, Jaakko | Kathiresan, Sekar | Kim, Bong-Jo | Kim, Young Jin | Kirov, George | Kooner, Jaspal | Koskinen, Seppo | Krumholz, Harlan | Kugathasan, Subra | Kwak, Soo Heon | Laakso, Markku | Lehtimäki, Terho | Loos, Ruth | Lubitz, Steven | Ma, Ronald | Macarthur, Daniel | Marrugat, Jaume | Mattila, Kari | Mccarroll, Steven | Mccarthy, Mark | Mcgovern, Dermot | Mcpherson, Ruth | Meigs, James | Melander, Olle | Metspalu, Andres | Nilsson, Peter | O’donovan, Michael | Ongur, Dost | Orozco, Lorena | Owen, Michael | Palmer, Colin | Palotie, Aarno | Park, Kyong Soo | Pato, Carlos | Pulver, Ann | Rahman, Nazneen | Remes, Anne | Rioux, John | Ripatti, Samuli | Roden, Dan | Saleheen, Danish | Salomaa, Veikko | Samani, Nilesh | Scharf, Jeremiah | Schunkert, Heribert | Shoemaker, Moore | Sklar, Pamela | Soininen, Hilkka | Sokol, Harry | Spector, Tim | Sullivan, Patrick | Suvisaari, Jaana | Tai, E. Shyong | Teo, Yik Ying | Tiinamaija, Tuomi | Tsuang, Ming | Turner, Dan | Tusie-Luna, Teresa | Vartiainen, Erkki | Vawter, Marquis | Watkins, Hugh | Weersma, Rinse | Wessman, Maija | Wilson, James | Xavier, Ramnik | Taylor, Kent | Lin, Henry | Rich, Stephen | Post, Wendy | Chen, Yii-Der Ida | Rotter, Jerome | Nusbaum, Chad | Philippakis, Anthony | Lander, Eric | Talkowski, Michael
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Abstract 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.
