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Weghorn D, Balick DJ, Cassa C, Kosmicki JA, Daly MJ, Beier DR, Sunyaev SR. Applicability of the Mutation-Selection Balance Model to Population Genetics of Heterozygous Protein-Truncating Variants in Humans. Mol Biol Evol 2020; 36:1701-1710. [PMID: 31004148 DOI: 10.1093/molbev/msz092] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
The fate of alleles in the human population is believed to be highly affected by the stochastic force of genetic drift. Estimation of the strength of natural selection in humans generally necessitates a careful modeling of drift including complex effects of the population history and structure. Protein-truncating variants (PTVs) are expected to evolve under strong purifying selection and to have a relatively high per-gene mutation rate. Thus, it is appealing to model the population genetics of PTVs under a simple deterministic mutation-selection balance, as has been proposed earlier (Cassa et al. 2017). Here, we investigated the limits of this approximation using both computer simulations and data-driven approaches. Our simulations rely on a model of demographic history estimated from 33,370 individual exomes of the Non-Finnish European subset of the ExAC data set (Lek et al. 2016). Additionally, we compared the African and European subset of the ExAC study and analyzed de novo PTVs. We show that the mutation-selection balance model is applicable to the majority of human genes, but not to genes under the weakest selection.
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Affiliation(s)
- Donate Weghorn
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.,Department of Biomedical Informatics, Harvard Medical School, Boston, MA.,Centre for Genomic Regulation and Universitat Pompeu Fabra, Barcelona, Spain
| | - Daniel J Balick
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.,Department of Biomedical Informatics, Harvard Medical School, Boston, MA
| | - Christopher Cassa
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.,Department of Biomedical Informatics, Harvard Medical School, Boston, MA
| | - Jack A Kosmicki
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA.,Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
| | - Mark J Daly
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA.,Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
| | - David R Beier
- Center for Developmental Biology and Regenerative Medicine, Seattle Children's Research Institute, Seattle, WA.,Department of Pediatrics, University of Washington School of Medicine, Seattle, WA
| | - Shamil R Sunyaev
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.,Department of Biomedical Informatics, Harvard Medical School, Boston, MA
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