The landscape of tolerated genetic variation in humans and primates.

TitleThe landscape of tolerated genetic variation in humans and primates.
Publication TypeJournal Article
Year of Publication2023
AuthorsGao, H, Hamp, T, Ede, J, Schraiber, JG, McRae, J, Singer-Berk, M, Yang, Y, Dietrich, A, Fiziev, P, Kuderna, L, Sundaram, L, Wu, Y, Adhikari, A, Field, Y, Chen, C, Batzoglou, S, Aguet, F, Lemire, G, Reimers, R, Balick, D, Janiak, MC, Kuhlwilm, M, Orkin, JD, Manu, S, Valenzuela, A, Bergman, J, Rouselle, M, Silva, FEnnes, Agueda, L, Blanc, J, Gut, M, de Vries, D, Goodhead, I, Harris, RA, Raveendran, M, Jensen, A, Chuma, IS, Horvath, J, Hvilsom, C, Juan, D, Frandsen, P, de Melo, FR, Bertuol, F, Byrne, H, Sampaio, I, Farias, I, Amaral, JValsecchi, Messias, M, da Silva, MNF, Trivedi, M, Rossi, R, Hrbek, T, Andriaholinirina, N, Rabarivola, CJ, Zaramody, A, Jolly, CJ, Phillips-Conroy, J, Wilkerson, G, Abee, C, Simmons, JH, Fernandez-Duque, E, Kanthaswamy, S, Shiferaw, F, Wu, D, Zhou, L, Shao, Y, Zhang, G, Keyyu, JD, Knauf, S, Le, MD, Lizano, E, Merker, S, Navarro, A, Batallion, T, Nadler, T, Khor, CChuen, Lee, J, Tan, P, Lim, WKhong, Kitchener, AC, Zinner, D, Gut, I, Melin, A, Guschanski, K, Schierup, MHeide, Beck, RMD, Umapathy, G, Roos, C, Boubli, JP, Lek, M, Sunyaev, S, O'Donnell, A, Rehm, H, Xu, J, Rogers, J, Marques-Bonet, T, Farh, KKai-How
Date Published2023 May 02

UNLABELLED: Personalized genome sequencing has revealed millions of genetic differences between individuals, but our understanding of their clinical relevance remains largely incomplete. To systematically decipher the effects of human genetic variants, we obtained whole genome sequencing data for 809 individuals from 233 primate species, and identified 4.3 million common protein-altering variants with orthologs in human. We show that these variants can be inferred to have non-deleterious effects in human based on their presence at high allele frequencies in other primate populations. We use this resource to classify 6% of all possible human protein-altering variants as likely benign and impute the pathogenicity of the remaining 94% of variants with deep learning, achieving state-of-the-art accuracy for diagnosing pathogenic variants in patients with genetic diseases.

ONE SENTENCE SUMMARY: Deep learning classifier trained on 4.3 million common primate missense variants predicts variant pathogenicity in humans.

Alternate JournalbioRxiv
PubMed ID37205491
PubMed Central IDPMC10187174
Grant ListR01 HG010898 / HG / NHGRI NIH HHS / United States
P30 AG012836 / AG / NIA NIH HHS / United States
R24 HD044964 / HD / NICHD NIH HHS / United States
T32 GM007748 / GM / NIGMS NIH HHS / United States
P40 OD024628 / OD / NIH HHS / United States