• Nature · Jan 2013

    Analysis of 6,515 exomes reveals the recent origin of most human protein-coding variants.

    • Wenqing Fu, Timothy D O'Connor, Goo Jun, Hyun Min Kang, Goncalo Abecasis, Suzanne M Leal, Stacey Gabriel, Mark J Rieder, David Altshuler, Jay Shendure, Deborah A Nickerson, Michael J Bamshad, NHLBI Exome Sequencing Project, and Joshua M Akey.
    • Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA. wqfu@u.washington.edu
    • Nature. 2013 Jan 10;493(7431):216-20.

    AbstractEstablishing the age of each mutation segregating in contemporary human populations is important to fully understand our evolutionary history and will help to facilitate the development of new approaches for disease-gene discovery. Large-scale surveys of human genetic variation have reported signatures of recent explosive population growth, notable for an excess of rare genetic variants, suggesting that many mutations arose recently. To more quantitatively assess the distribution of mutation ages, we resequenced 15,336 genes in 6,515 individuals of European American and African American ancestry and inferred the age of 1,146,401 autosomal single nucleotide variants (SNVs). We estimate that approximately 73% of all protein-coding SNVs and approximately 86% of SNVs predicted to be deleterious arose in the past 5,000-10,000 years. The average age of deleterious SNVs varied significantly across molecular pathways, and disease genes contained a significantly higher proportion of recently arisen deleterious SNVs than other genes. Furthermore, European Americans had an excess of deleterious variants in essential and Mendelian disease genes compared to African Americans, consistent with weaker purifying selection due to the Out-of-Africa dispersal. Our results better delimit the historical details of human protein-coding variation, show the profound effect of recent human history on the burden of deleterious SNVs segregating in contemporary populations, and provide important practical information that can be used to prioritize variants in disease-gene discovery.

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