Estimating the human mutation rate using autozygosity in a founder population (original) (raw)

Nature Genetics volume 44, pages 1277–1281 (2012)Cite this article

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Abstract

Knowledge of the rate and pattern of new mutation is critical to the understanding of human disease and evolution. We used extensive autozygosity in a genealogically well-defined population of Hutterites to estimate the human sequence mutation rate over multiple generations. We sequenced whole genomes from 5 parent-offspring trios and identified 44 segments of autozygosity. Using the number of meioses separating each pair of autozygous alleles and the 72 validated heterozygous single-nucleotide variants (SNVs) from 512 Mb of autozygous DNA, we obtained an SNV mutation rate of 1.20 × 10−8 (95% confidence interval 0.89–1.43 × 10−8) mutations per base pair per generation. The mutation rate for bases within CpG dinucleotides (9.72 × 10−8) was 9.5-fold that of non-CpG bases, and there was strong evidence (P = 2.67 × 10−4) for a paternal bias in the origin of new mutations (85% paternal). We observed a non-uniform distribution of heterozygous SNVs (both newly identified and known) in the autozygous segments (P = 0.001), which is suggestive of mutational hotspots or sites of long-range gene conversion.

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References

  1. Haldane, J.B.S. The rate of spontaneous muation of a human gene. J. Genet. 31, 317–326 (1935).
    Article Google Scholar
  2. Kondrashov, A.S. Direct estimates of human per nucleotide mutation rates at 20 loci causing Mendelian diseases. Hum. Mutat. 21, 12–27 (2003).
    Article CAS PubMed Google Scholar
  3. Drake, J.W., Charlesworth, B., Charlesworth, D. & Crow, J.F. Rates of spontaneous mutation. Genetics 148, 1667–1686 (1998).
    CAS PubMed PubMed Central Google Scholar
  4. Lynch, M. Rate, molecular spectrum, and consequences of human mutation. Proc. Natl. Acad. Sci. USA 107, 961–968 (2010).
    Article CAS PubMed PubMed Central Google Scholar
  5. Conrad, D.F. et al. Variation in genome-wide mutation rates within and between human families. Nat. Genet. 43, 712–714 (2011).
    Article CAS PubMed PubMed Central Google Scholar
  6. Roach, J.C. et al. Analysis of genetic inheritance in a family quartet by whole-genome sequencing. Science 328, 636–639 (2010).
    Article CAS PubMed PubMed Central Google Scholar
  7. Nachman, M.W. & Crowell, S.L. Estimate of the mutation rate per nucleotide in humans. Genetics 156, 297–304 (2000).
    CAS PubMed PubMed Central Google Scholar
  8. Chong, J.X. et al. A common spinal muscular atrophy deletion mutation is present on a single founder haplotype in the US Hutterites. Eur. J. Hum. Genet. 19, 1045–1051 (2011).
    Article CAS PubMed PubMed Central Google Scholar
  9. Cusanovich, D.A. et al. The combination of a genome-wide association study of lymphocyte count and analysis of gene expression data reveals novel asthma candidate genes. Hum. Mol. Genet. 21, 2111–2123 (2012).
    Article CAS PubMed PubMed Central Google Scholar
  10. Abney, M., Ober, C. & McPeek, M.S. Quantitative-trait homozygosity and association mapping and empirical genomewide significance in large, complex pedigrees: fasting serum-insulin level in the Hutterites. Am. J. Hum. Genet. 70, 920–934 (2002).
    Article CAS PubMed PubMed Central Google Scholar
  11. Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).
    Article PubMed PubMed Central Google Scholar
  12. McKenna, A. et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).
    Article CAS PubMed PubMed Central Google Scholar
  13. The 1000 Genomes Project Consortium. A map of human genome variation from population-scale sequencing. Nature 467, 1061–1073 (2010).
  14. Han, L. & Abney, M. Identity by descent estimation with dense genome-wide genotype data. Genet. Epidemiol. 35, 557–567 (2011).
    Article PubMed PubMed Central Google Scholar
  15. Yang, Y. et al. Gene copy-number variation and associated polymorphisms of complement component C4 in human systemic lupus erythematosus (SLE): low copy number is a risk factor for and high copy number is a protective factor against SLE susceptibility in European Americans. Am. J. Hum. Genet. 80, 1037–1054 (2007).
    Article CAS PubMed PubMed Central Google Scholar
  16. Haldane, J.B. The mutation rate of the gene for haemophilia, and its segregation ratios in males and females. Ann. Eugen. 13, 262–271 (1947).
    Article CAS PubMed Google Scholar
  17. O'Roak, B.J. et al. Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations. Nature 485, 246–250 (2012).
    Article CAS PubMed PubMed Central Google Scholar
  18. Fledel-Alon, A. et al. Broad-scale recombination patterns underlying proper disjunction in humans. PLoS Genet. 5, e1000658 (2009).
    Article PubMed PubMed Central Google Scholar
  19. Kong, A. et al. Rate of de novo mutations and the importance of father's age to disease risk. Nature 488, 471–475 (2012).
    Article CAS PubMed PubMed Central Google Scholar
  20. Khalak, H.G. et al. Autozygome maps dispensable DNA and reveals potential selective bias against nullizygosity. Genet. Med. 14, 515–519 (2012).
    Article CAS PubMed Google Scholar
  21. Awadalla, P. et al. Direct measure of the de novo mutation rate in autism and schizophrenia cohorts. Am. J. Hum. Genet. 87, 316–324 (2010).
    Article CAS PubMed PubMed Central Google Scholar
  22. Sun, J.X. et al. A direct characterization of human mutation based on microsatellites. Nat. Genet. 44, 1161–1165 (2012).
    Article CAS PubMed PubMed Central Google Scholar
  23. Chen, J.M., Cooper, D.N., Chuzhanova, N., Ferec, C. & Patrinos, G.P. Gene conversion: mechanisms, evolution and human disease. Nat. Rev. Genet. 8, 762–775 (2007).
    Article CAS PubMed Google Scholar
  24. Schrider, D.R., Hourmozdi, J.N. & Hahn, M.W. Pervasive multinucleotide mutational events in eukaryotes. Curr. Biol. 21, 1051–1054 (2011).
    Article CAS PubMed PubMed Central Google Scholar
  25. Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754–1760 (2009).
    Article CAS PubMed PubMed Central Google Scholar
  26. DePristo, M.A. et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 43, 491–498 (2011).
    Article CAS PubMed PubMed Central Google Scholar
  27. Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).
    Article CAS PubMed PubMed Central Google Scholar
  28. Porreca, G.J. et al. Multiplex amplification of large sets of human exons. Nat. Methods 4, 931–936 (2007).
    Article CAS PubMed Google Scholar
  29. Turner, E.H., Lee, C., Ng, S.B., Nickerson, D.A. & Shendure, J. Massively parallel exon capture and library-free resequencing across 16 genomes. Nat. Methods 6, 315–316 (2009).
    Article CAS PubMed PubMed Central Google Scholar

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Acknowledgements

We are grateful to M. Przeworski for thoughtful comments on the manuscript. We thank C. Lee, B. Paeper, J. Smith and M. Rieder for assistance with sequence data generation and J. Huddleston for technical advice. We are grateful to T. Brown for assistance with manuscript preparation. C.D.C. was supported by a US National Institutes of Health (NIH) Ruth L. Kirschstein National Research Service Award (NRSA; F32HG006070). P.H.S. is supported by a Howard Hughes Medical Institute International Student Research Fellowship. This work was supported by an American Asthma Foundation Senior Investigator Award to E.E.E., by US NIH grants R01 HD21244 and R01 HL085197 to C.O. and by US NIH grant R01 HG002899 to M.A. E.E.E. is an Investigator of the Howard Hughes Medical Institute.

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Authors and Affiliations

  1. Department of Genome Sciences, University of Washington, Seattle, Washington, USA
    Catarina D Campbell, Maika Malig, Arthur Ko, Beth L Dumont, Laura Vives, Brian J O'Roak, Peter H Sudmant, Jay Shendure & Evan E Eichler
  2. Department of Human Genetics, The University of Chicago, Chicago, Illinois, USA
    Jessica X Chong, Lide Han, Mark Abney & Carole Ober
  3. Department of Obstetrics and Gynecology, The University of Chicago, Chicago, Illinois, USA
    Carole Ober
  4. Howard Hughes Medical Institute, Seattle, Washington, USA
    Evan E Eichler

Authors

  1. Catarina D Campbell
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  2. Jessica X Chong
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  3. Maika Malig
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  4. Arthur Ko
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  5. Beth L Dumont
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  6. Lide Han
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  7. Laura Vives
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  8. Brian J O'Roak
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  9. Peter H Sudmant
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  10. Jay Shendure
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  11. Mark Abney
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  12. Carole Ober
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  13. Evan E Eichler
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Contributions

C.D.C., J.X.C., C.O. and E.E.E. designed the study. C.D.C. performed the genome sequencing analysis, molecular inversion probe (MIP)-targeted resequencing analysis and mutation rate calculations. J.X.C. performed analyses to determine the ancestry of the autozygous segments. M.M. performed and analyzed validation experiments, including Sanger sequencing, microarray hybridization and MIP capture. A.K. and P.H.S. performed read-depth copy-number analysis. B.L.D. identified and analyzed the clusters of heterozygous SNVs in the autozygous segments. L.H. and M.A. performed autozygosity analysis with SNP microarray data. L.V. and B.J.O. created the sequencing libraries. B.J.O. designed the MIP oligonucleotides. L.V., along with M.M., performed MIP capture. E.E.E., C.O., M.A. and J.S. supervised the project. C.D.C. and E.E.E. wrote the manuscript with input and approval from all coauthors.

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Correspondence toEvan E Eichler.

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Competing interests

E.E.E. is on the scientific advisory boards for Pacific Biosciences, SynapDx and DNAnexus.

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Campbell, C., Chong, J., Malig, M. et al. Estimating the human mutation rate using autozygosity in a founder population.Nat Genet 44, 1277–1281 (2012). https://doi.org/10.1038/ng.2418

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