Establishing the age of each mutation segregating in contemporary human populations is important to fully understand our evolutionary history1,2 and will help to facilitate the development of new approaches for disease-gene discovery3. Large-scale surveys of human genetic variation have reported signatures of recent explosive population growth4,5,6, 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.
Subscribe to Journal
Get full journal access for 1 year
only $3.90 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
Filtered sets of annotated variants and their allele frequencies are available at (http://evs.gs.washington.edu/EVS/) and genotypes and phenotypes from a large subset of individuals are also available through dbGaP (http://www.ncbi.nlm.nih.gov/gap) using the following accession information: NHLBI GO-ESP: Women’s Health Initiative Exome Sequencing Project (WHI) – WHISP, WHISP_Subject_Phenotypes, pht002246.v2.p2, phs000281.v2.p2; NHLBI GO-ESP: Heart Cohorts Exome Sequencing Project (JHS), ESP_HeartGO_JHS_LDLandEOMI_Subject_Phenotypes, pht002539.v1.p1, phs000402.v1.p1; NHLBI GO-ESP: Heart Cohorts Exome Sequencing Project (FHS), HeartGO_FHS_LDLandEOMI_PhenotypeDataFile, pht002476.v1.p1, phs000401.v1.p1; NHLBI GO-ESP: Heart Cohorts Exome Sequencing Project (CHS), HeartGO_CHS_LDL_PhenotypeDataFile, pht002536.v1.p1, phs000400.v1.p1; NHLBI GO-ESP: Heart Cohorts Exome Sequencing Project (ARIC), ESP_ARIC_LDLandEOMI_Sample, pht002466.v1.p1, phs000398.v1.p1;NHLBIGO-ESP: Lung Cohorts Exome Sequencing Project (Cystic Fibrosis), ESP_LungGO_CF_PA_Culture_Data, pht002227.v1.p1, phs000254.v1.p1; NHLBI GO-ESP: Early-Onset Myocardial Infarction (Broad EOMI), ESP_Broad_EOMI_Subject_Phenotypes, pht001437.v1.p1, phs000279.v1.p1; NHLBI GO-ESP: Lung Cohorts Exome Sequencing Project (Pulmonary Arterial Hypertension), PAH_Subject_Phenotypes_Baseline_Measures, pht002277.v1.p1, phs000290.v1.p1; NHLBI GO-ESP: Lung Cohorts Exome Sequencing Project (Lung Health Study of Chronic Obstructive Pulmonary Disease), LHS_COPD_Subject_Phenotypes_Baseline_Measures, pht002272.v1.p1, phs000291.v1.p1.
Kimura, M. & Ota, T. The age of a neutral mutant persisting in a finite population. Genetics 75, 199–212 (1973)
Tishkoff, S. A. & Verrelli, B. C. Patterns of human genetic diversity: implications for human evolutionary history and disease. Annu. Rev. Genomics Hum. Genet. 4, 293–340 (2003)
Slatkin, M. & Rannala, B. Estimating allele age. Annu. Rev. Genomics Hum. Genet. 1, 225–249 (2000)
Keinan, A. & Clark, A. G. Recent explosive human population growth has resulted in an excess of rare genetic variants. Science 336, 740–743 (2012)
Nelson, M. R. et al. An abundance of rare functional variants in 202 drug target genes sequenced in 14,002 people. Science 337, 100–104 (2012)
Tennessen, J. A. et al. Evolution and functional impact of rare coding variation from deep sequencing of human exomes. Science 337, 64–69 (2012)
Griffiths, R. C. & Tavaré, S. The age of a mutation in a general coalescent tree. Commun. Stat. Stoch. Models 14, 273–295 (1998)
Coventry, A. et al. Deep resequencing reveals excess rare recent variants consistent with explosive population growth. Nature Commun. 1, 131 (2010)
Gravel, S. et al. Demographic history and rare allele sharing among human populations. Proc. Natl Acad. Sci. USA 108, 11983–11988 (2011)
Gutenkunst, R. N., Hernandez, R. D., Williamson, S. H. & Bustamante, C. D. Inferring the joint demographic history of multiple populations from multidimensional SNP frequency data. PLoS Genet. 5, e1000695 (2009)
Schaffner, S. F. et al. Calibrating a coalescent simulation of human genome sequence variation. Genome Res. 15, 1576–1583 (2005)
Gibson, G. Rare and common variants: twenty arguments. Nature Rev. Genet. 13, 135–145 (2012)
Kumar, P., Henikoff, S. & Ng, P. C. Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nature Protocols 4, 1073–1081 (2009)
Adzhubei, I. A. et al. A method and server for predicting damaging missense mutations. Nature Methods 7, 248–249 (2010)
Chun, S. & Fay, J. C. Identification of deleterious mutations within three human genomes. Genome Res. 19, 1553–1561 (2009)
Schwarz, J. M., Rodelsperger, C., Schuelke, M. & Seelow, D. MutationTaster evaluates disease-causing potential of sequence alterations. Nature Methods 7, 575–576 (2010)
Davydov, E. V. et al. Identifying a high fraction of the human genome to be under selective constraint using GERP++. PLOS Comput. Biol. 6, e1001025 (2010)
Pollard, K. S., Hubisz, M. J., Rosenbloom, K. R. & Siepel, A. Detection of nonneutral substitution rates on mammalian phylogenies. Genome Res. 20, 110–121 (2010)
Becker, K. G., Barnes, K. C., Bright, T. J. & Wang, S. A. The genetic association database. Nature Genet. 36, 431–432 (2004)
Pyun, J. A., Cha, D. H. & Kwack, K. LAMC1 gene is associated with premature ovarian failure. Maturitas 71, 402–406 (2012)
Liu, Q. et al. Amyloid precursor protein regulates brain apolipoprotein E and cholesterol metabolism through lipoprotein receptor LRP1. Neuron 56, 66–78 (2007)
Jia, E. Z. et al. Association of the mutation for the human carboxypeptidase E gene exon 4 with the severity of coronary artery atherosclerosis. Mol. Biol. Rep. 36, 245–254 (2009)
Valdmanis, P. N. et al. Mutations in the KIAA0196 gene at the SPG8 locus cause hereditary spastic paraplegia. Am. J. Hum. Genet. 80, 152–161 (2007)
Blekhman, R. et al. Natural selection on genes that underlie human disease susceptibility. Curr. Biol. 18, 883–889 (2008)
Liao, B. Y., Scott, N. M. & Zhang, J. Impacts of gene essentiality, expression pattern, and gene compactness on the evolutionary rate of mammalian proteins. Mol. Biol. Evol. 23, 2072–2080 (2006)
Lohmueller, K. E. et al. Proportionally more deleterious genetic variation in European than in African populations. Nature 451, 994–997 (2008)
Hawks, J., Wang, E. T., Cochran, G. M., Harpending, H. C. & Moyzis, R. K. Recent acceleration of human adaptive evolution. Proc. Natl Acad. Sci. USA 104, 20753–20758 (2007)
We acknowledge the support of the National Heart, Lung and Blood Institute (NHLBI), the contributions of the research institutions that participated in this study, the study investigators, field staff and study participants who created this resource for biomedical research, and the Population Genetics Project Team of the NHLBI. We thank J. Wilson and R. Do for critical feedback on the manuscript. Funding for the GO (Grand Opportunity) Exome Sequencing Project was provided by NHLBI grants RC2 HL-103010 (Heart GO), RC2 HL-102923 (Lung GO) and RC2 HL-102924 (WHISP). The exome sequencing was was supported by NHLBI grants RC2 HL-102925 (Broad GO) and RC2 HL-102926 (Seattle GO).
The authors declare no competing financial interests.
This file contains Supplementary Text and Data, Supplementary References, Supplementary Tables 1-4 and Supplementary Figures 1-15 (see Table of Contents for more details). (PDF 3066 kb)
About this article
Cite this article
Fu, W., O’Connor, T., Jun, G. et al. Analysis of 6,515 exomes reveals the recent origin of most human protein-coding variants. Nature 493, 216–220 (2013). https://doi.org/10.1038/nature11690
Nature Reviews Genetics (2021)
Journal of Experimental Medicine (2021)
Nature Communications (2021)
Nucleic Acids Research (2021)
Journal of Medical Genetics (2020)