Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Parent-of-origin-specific signatures of de novo mutations

An Author Correction to this article was published on 05 October 2018

This article has been updated

Abstract

De novo mutations (DNMs) originating in gametogenesis are an important source of genetic variation. We use a data set of 7,216 autosomal DNMs with resolved parent of origin from whole-genome sequencing of 816 parent–offspring trios to investigate differences between maternally and paternally derived DNMs and study the underlying mutational mechanisms. Our results show that the number of DNMs in offspring increases not only with paternal age, but also with maternal age, and that some genome regions show enrichment for maternally derived DNMs. We identify parent-of-origin-specific mutation signatures that become more pronounced with increased parental age, pointing to different mutational mechanisms in spermatogenesis and oogenesis. Moreover, we find DNMs that are spatially clustered to have a unique mutational signature with no significant differences between parental alleles, suggesting a different mutational mechanism. Our findings provide insights into the molecular mechanisms that underlie mutagenesis and are relevant to disease and evolution in humans1.

This is a preview of subscription content

Access options

Buy article

Get time limited or full article access on ReadCube.

$32.00

All prices are NET prices.

Figure 1: Correlation of paternal and maternal age with the number of DNMs with resolved parent of origin.
Figure 2: Regions enriched for maternally and paternally derived DNMs.
Figure 3: Differences in paternal and maternal mutation profiles and correlation with parental age at conception.
Figure 4: Mutation profiles of clustered DNMs.

Change history

  • 05 October 2018

    In the version of this article published, the P values for the enrichment of single mutation categories were inadvertently not corrected for multiple testing. After multiple-testing correction, only two of the six mutation categories mentioned are still statistically significant. To reflect this, the text "More specifically, paternally derived DNMs are enriched in transitions in A[.]G contexts, especially ACG>ATG and ATG>ACG (Bonferroni-corrected P = 1.3 × 10−2 and P = 1 × 10−3, respectively). Additionally, we observed overrepresentation of ATA>ACA mutations (Bonferroni-corrected P = 4.28 × 10−2) for DNMs of paternal origin. Among maternally derived DNMs, CCA>CTA, GCA>GTA and TCT>TGT mutations were significantly overrepresented (Bonferroni-corrected P = 4 × 10−4, P = 5 × 10−4, P = 1 × 10−3, respectively)" should read "More specifically, CCA>CTA and GCA>GTA mutations were significantly overenriched on the maternal allele (Bonferroni-corrected P = 0.0192 and P = 0.048, respectively)." Additionally, the last sentence to the legend for Fig. 3b should read "Green boxes highlight the mutation categories that differ significantly” instead of “Green boxes highlight the mutation categories that differ more than 1% of mutation load with a bootstrapping P value <0.05." Corrected versions of Fig. 3b and Supplementary Table 25 appear with the Author Correction.

References

  1. Veltman, J.A. & Brunner, H.G. De novo mutations in human genetic disease. Nat. Rev. Genet. 13, 565–575 (2012).

    CAS  Article  Google Scholar 

  2. Kong, A. et al. Rate of de novo mutations and the importance of father's age to disease risk. Nature 488, 471–475 (2012).

    CAS  Article  Google Scholar 

  3. Michaelson, J.J. et al. Whole-genome sequencing in autism identifies hot spots for de novo germline mutation. Cell 151, 1431–1442 (2012).

    CAS  Article  Google Scholar 

  4. Campbell, C.D. & Eichler, E.E. Properties and rates of germline mutations in humans. Trends Genet. 29, 575–584 (2013).

    CAS  Article  Google Scholar 

  5. Roach, J.C. et al. Analysis of genetic inheritance in a family quartet by whole-genome sequencing. Science 328, 636–639 (2010).

    CAS  Article  Google Scholar 

  6. Makova, K.D. & Hardison, R.C. The effects of chromatin organization on variation in mutation rates in the genome. Nat. Rev. Genet. 16, 213–223 (2015).

    CAS  Article  Google Scholar 

  7. Crow, J.F. The origins, patterns and implications of human spontaneous mutation. Nat. Rev. Genet. 1, 40–47 (2000).

    CAS  Article  Google Scholar 

  8. Drmanac, R. et al. Human genome sequencing using unchained base reads on self-assembling DNA nanoarrays. Science 327, 78–81 (2010).

    CAS  Article  Google Scholar 

  9. Wong, W.S. et al. New observations on maternal age effect on germline de novo mutations. Nat. Commun. 7, 10486 (2016).

    CAS  Article  Google Scholar 

  10. Forster, P. et al. Elevated germline mutation rate in teenage fathers. Proc. R. Soc. Lond. B 282, 20142898 (2015).

    Article  Google Scholar 

  11. Ségurel, L., Wyman, M.J. & Przeworski, M. Determinants of mutation rate variation in the human germline. Annu. Rev. Genomics Hum. Genet. 15, 47–70 (2014).

    Article  Google Scholar 

  12. Schuster-Böckler, B. & Lehner, B. Chromatin organization is a major influence on regional mutation rates in human cancer cells. Nature 488, 504–507 (2012).

    Article  Google Scholar 

  13. Smith, D.I., Zhu, Y., McAvoy, S. & Kuhn, R. Common fragile sites, extremely large genes, neural development and cancer. Cancer Lett. 232, 48–57 (2006).

    CAS  Article  Google Scholar 

  14. White, S. et al. A multi-exon deletion within WWOX is associated with a 46,XY disorder of sex development. Eur. J. Hum. Genet. 20, 348–351 (2012).

    CAS  Article  Google Scholar 

  15. Francioli, L.C. et al. Genome-wide patterns and properties of de novo mutations in humans. Nat. Genet. 47, 822–826 (2015).

    CAS  Article  Google Scholar 

  16. Alexandrov, L.B. et al. Signatures of mutational processes in human cancer. Nature 500, 415–421 (2013).

    CAS  Article  Google Scholar 

  17. Rahbari, R. et al. Timing, rates and spectra of human germline mutation. Nat. Genet. 48, 126–133 (2016).

    CAS  Article  Google Scholar 

  18. Titus, S. et al. Impairment of BRCA1-related DNA double-strand break repair leads to ovarian aging in mice and humans. Sci. Transl. Med. 5, 172ra21 (2013).

    Article  Google Scholar 

  19. Chan, K. & Gordenin, D.A. Clusters of multiple mutations: incidence and molecular mechanisms. Annu. Rev. Genet. 49, 243–267 (2015).

    CAS  Article  Google Scholar 

  20. Bodian, D.L. et al. Utility of whole-genome sequencing for detection of newborn screening disorders in a population cohort of 1,696 neonates. Genet. Med. 221–230 (2016).

    Article  Google Scholar 

  21. Bodian, D.L. et al. Germline variation in cancer-susceptibility genes in a healthy, ancestrally diverse cohort: implications for individual genome sequencing. PLoS One 9, e94554 (2014).

    Article  Google Scholar 

  22. Carnevali, P. et al. Computational techniques for human genome resequencing using mated gapped reads. J. Comput. Biol. 19, 279–292 (2012).

    CAS  Article  Google Scholar 

  23. 1000 Genomes Project Consortium. et al. A map of human genome variation from population-scale sequencing. Nature 467, 1061–1073 (2010).

  24. Gilissen, C. et al. Genome sequencing identifies major causes of severe intellectual disability. Nature 511, 344–347 (2014).

    CAS  Article  Google Scholar 

  25. Glusman, G., Caballero, J., Mauldin, D.E., Hood, L. & Roach, J.C. Kaviar: an accessible system for testing SNV novelty. Bioinformatics 27, 3216–3217 (2011).

    CAS  Article  Google Scholar 

  26. ENCODE Project Consortium. A user's guide to the encyclopedia of DNA elements (ENCODE). PLoS Biol. 9, e1001046 (2011).

  27. Acuna-Hidalgo, R. et al. Post-zygotic point mutations are an underrecognized source of de novo genomic variation. Am. J. Hum. Genet. 97, 67–74 (2015).

    CAS  Article  Google Scholar 

  28. Peters, B.A. et al. Accurate whole-genome sequencing and haplotyping from 10 to 20 human cells. Nature 487, 190–195 (2012).

    CAS  Article  Google Scholar 

  29. Cingolani, P. et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly (Austin) 6, 80–92 (2012).

    CAS  Article  Google Scholar 

  30. Paila, U., Chapman, B.A., Kirchner, R. & Quinlan, A.R. GEMINI: integrative exploration of genetic variation and genome annotations. PLoS Comput. Biol. 9, e1003153 (2013).

    CAS  Article  Google Scholar 

  31. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2008).

  32. pvclust: Hierarchical Clustering with P-Values via Multiscale Bootstrap Resampling (2015).

  33. Hellmann, I. et al. Why do human diversity levels vary at a megabase scale? Genome Res. 15, 1222–1231 (2005).

    CAS  Article  Google Scholar 

  34. Quinlan, A.R. & Hall, I.M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).

    CAS  Article  Google Scholar 

  35. Rosenbloom, K.R. et al. The UCSC Genome Browser database: 2015 update. Nucleic Acids Res. 43, D670–D681 (2015).

    CAS  Article  Google Scholar 

  36. Koren, A. et al. Differential relationship of DNA replication timing to different forms of human mutation and variation. Am. J. Hum. Genet. 91, 1033–1040 (2012).

    CAS  Article  Google Scholar 

  37. Kundaje, A. et al. Integrative analysis of 111 reference human epigenomes. Nature 518, 317–330 (2015).

    CAS  Article  Google Scholar 

  38. Visser, I.S.M. depmixS4: an R package for hidden Markov models. J. Stat. Softw. 36, 1–21 (2010).

    Article  Google Scholar 

  39. Roberts, S.A. et al. An APOBEC cytidine deaminase mutagenesis pattern is widespread in human cancers. Nat. Genet. 45, 970–976 (2013).

    CAS  Article  Google Scholar 

  40. Pettersen, H.S. et al. AID expression in B-cell lymphomas causes accumulation of genomic uracil and a distinct AID mutational signature. DNA Repair (Amst.) 25, 60–71 (2015).

    CAS  Article  Google Scholar 

  41. Qian, J. et al. B cell super-enhancers and regulatory clusters recruit AID tumorigenic activity. Cell 159, 1524–1537 (2014).

    CAS  Article  Google Scholar 

  42. Conrad, D.F. et al. Variation in genome-wide mutation rates within and between human families. Nat. Genet. 43, 712–714 (2011).

    CAS  Article  Google Scholar 

Download references

Acknowledgements

We thank all the clinical, laboratory, information technology, and informatics staff for their support on this research project, especially R. Haridas and R. Smith for Sanger sequencing. We would like to thank D. Aguiar and S. Istrail for helpful discussions on their HapCompass software. We would also like to express our gratitude to the participating individuals and their families. The ITMI was supported by the Inova Health System, a nonprofit healthcare system in Northern Virginia. This work was partly financially supported by grants from the Netherlands Organization for Scientific Research (918-15-667 to J.A.V., 916-14-043 to C.G., and SH-271-13 to C.G. and J.A.V.), the European Research Council (ERC Starting grant DENOVO 281964 to J.A.V.), the German Academic Exchange Service DAAD (postdoctoral grant to A.B.S.), and the German Research Foundation DFG (Postdoc grant to A.B.S.).

Author information

Authors and Affiliations

Authors

Contributions

J.A.V., C.G., and J.E.N. designed the study. J.M.G., W.S.W.W., and M.P. performed the data analyses. M.P., L.E.L.M.V., and A.H. provided and analyzed preliminary data and assisted in writing the final manuscript. J.G.V., B.D.S., and J.E.N. supervised the data collection, sequencing and writing of the manuscript. D.B., A.B.S., G.G., and J.C.R. assisted in data analyses and interpretation. T.F. assisted in data processing. J.M.G., W.S.W.W., and C.G. drafted the manuscript. All authors contributed to the final version of the paper.

Corresponding authors

Correspondence to Christian Gilissen or John E Niederhuber.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Tables 1–13,16–20, 23, 24, 26–35, Supplementary Figures 1–11, and Supplementary Note (PDF 3467 kb)

Supplementary Table 14

Number of phased and unphased mutations per trio. First column lists the trio identifiers, second column the number of DNMs per trio; third and fourth columns give the number of paternal and maternal mutations, respectively. Fifth and sixth columns indicate the age category of father and mother for the analysis in Figure 2a. Seventh and eighth columns give the age category of the paternal and maternal mutations in the clustering analysis in Figure 3c. See Supplementary Table 26 for the ranges of the age categories. (XLSX 32 kb)

Supplementary Table 15

List of identified SNV DNMs and their phase. (XLSX 1251 kb)

Supplementary Table 21

The genomic coordinates and the phmm states of the 2,659 nonoverlapping 1-Mb windows. The phmm assigned mutation rate states and the genomic coordinates of the 2,659 nonoverlapping 1-Mb windows with callable bases >50%. (XLSX 129 kb)

Supplementary Table 22

The genomic features and de novo mutation rates in each category for each of the 2,634 nonoverlapping 1-Mb windows with callable bases >50% and no missing values are denoted in the supplementary file. (XLSX 629 kb)

Supplementary Table 25

Nucleotide substitutions and contexts by gender. List of all 96 mutation categories as defined by their nucleotide substitutions and surrounding nucleotides. Second and third columns indicate the fractions of paternal and maternal DNMs that falls into that category, respectively. Fourth column indicates the difference between paternal and maternal fractions (visualized in Fig. 3b). Fifth column indicates the log2 of the paternal/maternal ratio. Sixth column gives multiple-testing corrected P-value of true difference between maternal and paternal fraction. (XLSX 15 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Goldmann, J., Wong, W., Pinelli, M. et al. Parent-of-origin-specific signatures of de novo mutations. Nat Genet 48, 935–939 (2016). https://doi.org/10.1038/ng.3597

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ng.3597

Further reading

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing