4.8 Article

A Systematic Survey of Loss-of-Function Variants in Human Protein-Coding Genes

Journal

SCIENCE
Volume 335, Issue 6070, Pages 823-828

Publisher

AMER ASSOC ADVANCEMENT SCIENCE
DOI: 10.1126/science.1215040

Keywords

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Funding

  1. Wellcome Trust [098051, 090532/Z/09/Z]
  2. Australian National Health and Medical Research Council
  3. Swiss National Science Foundation
  4. Louis Jeantet Foundation
  5. NIH-National Institute of Mental Health
  6. Netherlands Organisation for Scientific Research (NWO) [639.021.125]
  7. National Basic Research Program of China (973 program) [2011CB809200]
  8. National Natural Science Foundation of China [30725008, 30890032, 30811130531]
  9. Chinese 863 program [2006AA02A302, 2009AA022707]
  10. Shenzhen Municipal Government of China [JC200903190767A, JC200903190772A, ZYC200903240076A, CXB200903110066A, ZYC200903240077A, ZYC200903240080A]
  11. Danish Natural Science Research Council
  12. Shenzhen Municipal Government
  13. Local Government of Yantian District of Shenzhen
  14. Biotechnology and Biological Sciences Research Council [BB/I02593X/1] Funding Source: researchfish
  15. British Heart Foundation [RG/09/012/28096] Funding Source: researchfish
  16. BBSRC [BB/I02593X/1] Funding Source: UKRI

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Genome-sequencing studies indicate that all humans carry many genetic variants predicted to cause loss of function (LoF) of protein-coding genes, suggesting unexpected redundancy in the human genome. Here we apply stringent filters to 2951 putative LoF variants obtained from 185 human genomes to determine their true prevalence and properties. We estimate that human genomes typically contain similar to 100 genuine LoF variants with similar to 20 genes completely inactivated. We identify rare and likely deleterious LoF alleles, including 26 known and 21 predicted severe disease-causing variants, as well as common LoF variants in nonessential genes. We describe functional and evolutionary differences between LoF-tolerant and recessive disease genes and a method for using these differences to prioritize candidate genes found in clinical sequencing studies.

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