The landscape of tolerated genetic variation in humans and primates
Author:
Gao HongORCID, Hamp Tobias, Ede Jeffrey, Schraiber Joshua G., McRae Jeremy, Singer-Berk Moriel, Yang Yanshen, Dietrich Anastasia, Fiziev Petko, Kuderna Lukas, Sundaram Laksshman, Wu Yibing, Adhikari Aashish, Field Yair, Chen Chen, Batzoglou Serafim, Aguet Francois, Lemire Gabrielle, Reimers Rebecca, Balick Daniel, Janiak Mareike C., Kuhlwilm MartinORCID, Orkin Joseph D., Manu Shivakumara, Valenzuela AlejandroORCID, Bergman Juraj, Rouselle Marjolaine, Silva Felipe Ennes, Agueda Lidia, Blanc Julie, Gut Marta, Vries Dorien de, Goodhead Ian, Harris R. Alan, Raveendran Muthuswamy, Jensen Axel, Chuma Idriss S., Horvath Julie, Hvilsom Christina, Juan DavidORCID, Frandsen Peter, Melo Fabiano R. de, Bertuol Fabricio, Byrne Hazel, Sampaio Iracilda, Farias Izeni, Valsecchi do Amaral João, Messias Mariluce, Silva Maria N. F. da, Trivedi Mihir, Rossi Rogerio, Hrbek Tomas, Andriaholinirina Nicole, Rabarivola Clément J., Zaramody Alphonse, Jolly Clifford J., Phillips-Conroy Jane, Wilkerson Gregory, Abee Christian, Simmons Joe H., Fernandez-Duque Eduardo, Kanthaswamy ee, Shiferaw Fekadu, Wu Dongdong, Zhou Long, Shao Yong, Zhang Guojie, Keyyu Julius D., Knauf Sascha, Le Minh D., Lizano EstherORCID, Merker Stefan, Navarro Arcadi, Batallion Thomas, Nadler Tilo, Khor Chiea Chuen, Lee Jessica, Tan Patrick, Lim Weng Khong, Kitchener Andrew C., Zinner Dietmar, Gut IvoORCID, Melin Amanda, Guschanski KaterinaORCID, Schierup Mikkel Heide, Beck Robin M. D., Umapathy Govindhaswamy, Roos Christian, Boubli Jean P., Lek Monkol, Sunyaev Shamil, O’Donnell AnneORCID, Rehm HeidiORCID, Xu JinboORCID, Rogers JeffreyORCID, Marques-Bonet Tomas, Farh Kyle Kai-HowORCID
Abstract
AbstractPersonalized 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 SummaryDeep learning classifier trained on 4.3 million common primate missense variants predicts variant pathogenicity in humans.
Publisher
Cold Spring Harbor Laboratory
Cited by
1 articles.
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