DOI: 10.1126/science.1215040 ISSN:

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

Daniel G. MacArthur, Suganthi Balasubramanian, Adam Frankish, Ni Huang, James Morris, Klaudia Walter, Luke Jostins, Lukas Habegger, Joseph K. Pickrell, Stephen B. Montgomery, Cornelis A. Albers, Zhengdong D. Zhang, Donald F. Conrad, Gerton Lunter, Hancheng Zheng, Qasim Ayub, Mark A. DePristo, Eric Banks, Min Hu, Robert E. Handsaker, Jeffrey A. Rosenfeld, Menachem Fromer, Mike Jin, Xinmeng Jasmine Mu, Ekta Khurana, Kai Ye, Mike Kay, Gary Ian Saunders, Marie-Marthe Suner, Toby Hunt, If H. A. Barnes, Clara Amid, Denise R. Carvalho-Silva, Alexandra H. Bignell, Catherine Snow, Bryndis Yngvadottir, Suzannah Bumpstead, David N. Cooper, Yali Xue, Irene Gallego Romero, Jun Wang, Yingrui Li, Richard A. Gibbs, Steven A. McCarroll, Emmanouil T. Dermitzakis, Jonathan K. Pritchard, Jeffrey C. Barrett, Jennifer Harrow, Matthew E. Hurles, Mark B. Gerstein, Chris Tyler-Smith,
  • Multidisciplinary
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Defective Gene Detective

Identifying genes that give rise to diseases is one of the major goals of sequencing human genomes. However, putative loss-of-function genes, which are often some of the first identified targets of genome and exome sequencing, have often turned out to be sequencing errors rather than true genetic variants. In order to identify the true scope of loss-of-function genes within the human genome, MacArthur et al. (p. 823 ; see the Perspective by Quintana-Murci ) extensively validated the genomes from the 1000 Genomes Project, as well as an additional European individual, and found that the average person has about 100 true loss-of-function alleles of which approximately 20 have two copies within an individual. Because many known disease-causing genes were identified in “normal” individuals, the process of clinical sequencing needs to reassess how to identify likely causative alleles.

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