生物
遗传学
外显子组
基因
外显子组测序
孟德尔遗传
损失函数
否定选择
表型
选择(遗传算法)
基因组
计算生物学
计算机科学
人工智能
作者
Christopher A. Cassa,Donate Weghorn,Daniel J. Balick,Daniel M. Jordan,David P. Nusinow,Kaitlin E. Samocha,Anne O’Donnell‐Luria,Daniel G. MacArthur,Mark J. Daly,David R. Beier,Shamil Sunyaev
出处
期刊:Nature Genetics
[Springer Nature]
日期:2017-04-03
卷期号:49 (5): 806-810
被引量:190
摘要
Shamil Sunyaev, David Beier and colleagues report an analysis of the fitness effects of heterozygous protein-truncating variants from the Exome Aggregation Consortium. They find that high heterozygous selection coefficients are enriched in Mendelian disease-associated genes and essential mouse genes, suggesting that this coefficient can be used to prioritize candidate disease-associated genes from clinical exome-sequencing data. The evolutionary cost of gene loss is a central question in genetics and has been investigated in model organisms and human cell lines1,2,3. In humans, tolerance of the loss of one or both functional copies of a gene is related to the gene's causal role in disease. However, estimates of the selection and dominance coefficients in humans have been elusive. Here we analyze exome sequence data from 60,706 individuals4 to make genome-wide estimates of selection against heterozygous loss of gene function. Using this distribution of selection coefficients for heterozygous protein-truncating variants (PTVs), we provide corresponding Bayesian estimates for individual genes. We find that genes under the strongest selection are enriched in embryonic lethal mouse knockouts, Mendelian disease-associated genes, and regulators of transcription. Screening by essentiality, we find a large set of genes under strong selection that are likely to have crucial functions but have not yet been thoroughly characterized.
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