| Title | The landscape of tolerated genetic variation in humans and primates. |
| Publication Type | Journal Article |
| Year of Publication | 2023 |
| Authors | Gao, H, Hamp, T, Ede, J, Schraiber, JG, McRae, J, Singer-Berk, M, Yang, Y, Dietrich, ASD, Fiziev, PP, Kuderna, LFK, 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, Rousselle, M, Silva, FEnnes, Agueda, L, Blanc, J, Gut, M, de Vries, D, Goodhead, I, Harris, RA, Raveendran, M, Jensen, A, Chuma, IS, Horvath, JE, 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, Bataillon, 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-Luria, A, Rehm, HL, Xu, J, Rogers, J, Marques-Bonet, T, Farh, KKai-How |
| Journal | Science |
| Volume | 380 |
| Issue | 6648 |
| Pagination | eabn8153 |
| Date Published | 2023 Jun 02 |
| ISSN | 1095-9203 |
| Keywords | Animals, Base Sequence, Gene Frequency, Genetic Variation, Humans, Primates, Whole Genome Sequencing |
| Abstract | 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 humans. We show that these variants can be inferred to have nondeleterious effects in humans 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. |
| DOI | 10.1126/science.abn8197 |
| Alternate Journal | Science |
| PubMed ID | 37262156 |
| Grant List | P40 OD024628 / OD / NIH HHS / United States R01 GM089753 / GM / NIGMS NIH HHS / United States |