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Germline de novo mutation clusters arise during oocyte aging in genomic regions with high double-strand-break incidence

Nature Genetics volume 50, pages 487–492 (2018)Cite this article

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Abstract

Clustering of mutations has been observed in cancer genomes as well as for germline de novo mutations (DNMs). We identified 1,796 clustered DNMs (cDNMs) within whole-genome-sequencing data from 1,291 parent–offspring trios to investigate their patterns and infer a mutational mechanism. We found that the number of clusters on the maternal allele was positively correlated with maternal age and that these clusters consisted of more individual mutations with larger intermutational distances than those of paternal clusters. More than 50% of maternal clusters were located on chromosomes 8, 9 and 16, in previously identified regions with accelerated maternal mutation rates. Maternal clusters in these regions showed a distinct mutation signature characterized by C>G transversions. Finally, we found that maternal clusters were associated with processes involving double-strand-breaks (DSBs), such as meiotic gene conversions and de novo deletion events. This result suggested accumulation of DSB-induced mutations throughout oocyte aging as the mechanism underlying the formation of maternal mutation clusters.

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Fig. 1: Differences between maternal and paternal cDNMs.
Fig. 2: Patterns of cDNMs across the chromosomes.
Fig. 3: cDNMs and sites likely to be affected by DSBs.

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Acknowledgements

This study was funded by the Inova Health System with support from Fairfax County and philanthropic support from the Odeen family. We thank the Inova Translational Medicine Institute staff for supporting the study. We also thank the families who participated in the genomic studies that made this research possible. This work was partly financially supported by grants from the Netherlands Organization for Scientific Research (916-14-043 to C.G. and 918-15-667 to J.A.V.) and the European Research Council (ERC Starting grant DENOVO 281964 to J.A.V.).

This study used data generated by the Genome of the Netherlands Project. A full list of the investigators is available from http://www.nlgenome.nl/. Funding for the project was provided by the Netherlands Organization for Scientific Research under award number 184021007, dated July 9, 2009 and made available as a Rainbow Project of the Biobanking and Biomolecular Research Infrastructure Netherlands (BBMRI-NL). The sequencing was carried out in collaboration with the Beijing Institute for Genomics (BGI).

Author information

Author notes

  1. These authors contributed equally: Jakob M. Goldmann, Vladimir B. Seplyarskiy and Wendy S.W. Wong.

  2. These authors jointly supervised this work: Christian Gilissen and John E. Niederhuber.

Authors and Affiliations

  1. Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, the Netherlands

    Jakob M. Goldmann

  2. Division of Genetics, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Vladimir B. Seplyarskiy

  3. Institute for Information Transmission Problems of the Russian Academy of Sciences (Kharkevich Institute), Moscow, Russia

    Vladimir B. Seplyarskiy

  4. Inova Translational Medicine Institute (ITMI), Inova Health Systems, Falls Church, VA, USA

    Wendy S. W. Wong, Thierry Vilboux, Dale L. Bodian, John F. Deeken & John E. Niederhuber

  5. Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands

    Pieter B. Neerincx

  6. Genomics Coordination Center, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands

    Pieter B. Neerincx

  7. Department of Pediatrics, Inova Children’s Hospital, Inova Health System, Falls Church, VA, USA

    Benjamin D. Solomon

  8. Department of Pediatrics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA

    Benjamin D. Solomon

  9. Department of Human Genetics, Donders Centre for Neuroscience, Radboud University Medical Center, Nijmegen, the Netherlands

    Joris A. Veltman & Christian Gilissen

  10. Institute of Genetic Medicine, International Centre for Life, Newcastle University, Newcastle upon Tyne, UK

    Joris A. Veltman

  11. Johns Hopkins University School of Medicine, Baltimore, MD, USA

    John E. Niederhuber

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Contributions

C.G. and J.E.N. designed the study. J.M.G., V.B.S. and W.S.W.W. performed the data analyses. W.S.W.W. carried out QC and de novo mutation calling. T.V. performed Sanger validation. B.D.S., J.F.D. and J.E.N. supervised the data collection, sequencing and writing of the manuscript. D.L.B. assisted in data analyses and interpretation. J.M.G., V.B.S., W.S.W.W., J.A.V. and C.G. drafted the manuscript. P.B.N. acquired part of the replication data. All authors contributed to the final version of the paper.

Corresponding authors

Correspondence to Christian Gilissen or John E. Niederhuber.

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Integrated supplementary information

Supplementary Figure 1 Linear models of age effects.

(a) Linear models for the numbers of clustered and unclustered DNMs. (b) Linear models for the numbers of cluster events. Grey shades indicate standard errors.

Supplementary Figure 2 Parental ages by the number of clusters per individual.

(a) Primary cohort and (b) replication cohort. Boxplot whiskers depict distance from quartile to a maximum of 1.58 times the interquartile range. Numbers indicate number of individuals per group. While the maternal age increases with the number of clusters, the paternal age does not.

Supplementary Figure 3 Differences between maternal and paternal cDNMs in the replication cohort.

(a) The fraction of probands with maternal and paternal clustered mutations (y-axis), grouped by parental age quantiles. Error bars indicate the binomial 95% confidence intervals. (b) The number of paternal and maternal cDNMs (y-axis) stratified by the distance to the nearest other cDNM (x-axis). (c) The size of paternal and maternal age effect of clusters with at least one phased cDNM (y-axis) by inter-mutational distance (x-axis). Whiskers indicate the 95% confidence interval. (d) Age of fathers at conception and (e) age of the mothers at conception (y-axis) by the number of mutations in the offspring’s largest mutation cluster originating from the respective parent (x-axis). We considered only clusters where at least one cDNM is on the allele from the respective parent (paternal allele for d and maternal allele for e). Numbers indicate the size of each group. Boxplot compartments: box: interquartile range; line: median; whiskers: extreme values <1.5 × interquartile ranges from box borders).

Supplementary Figure 4

Numbers of phased unclustered DNMs and cDNMs per chromosome in the primary cohort.

Supplementary Figure 5 Patterns of cDNMs across the chromosomes in the replication cohort.

(a) The fraction of phased cDNMs per chromosome. Error bars indicate the binomial 95% confidence intervals. (b) The nucleotide substitution spectrum of maternal and paternal clusters and unclustered DNMs. Error bars indicate the binomial 95% confidence intervals. (c) The nucleotide substitution spectrum of cDNMs by location. Error bars indicate the binomial 95% confidence intervals.

Supplementary Figure 6 cDNM-enriched regions on chromosomes 8 and 9.

Overview of regions enriched for maternal cluster mutations. X-axis and ideograms indicate chromosomal position. The red and blue histograms indicate the number of maternal cDNMs and paternal cDNMs identified in this study, respectively. The pale red and pale blue histograms indicate the number of maternal and paternal unclustered DNMs. The lowest track indicates normalized cSNP C>G score, which is predictive for maternal DNMs. (a) Full chromosome 8. (b) Region with increased maternal mutation rate on chromosome 9 (chr9: 0-10,000,000).

Supplementary Figure 7 cDNM-enriched regions in the replication cohort.

Overview of regions enriched for maternal cluster mutations. X-axis and ideograms indicate chromosomal position. The red and blue histograms indicate the number of maternal cDNMs and paternal cDNMs identified in this study, respectively. The pale red and pale blue histograms indicate the number of maternal and paternal unclustered DNMs. The lowest track indicates normalized cSNP C>G score, which is predictive for maternal DNMs. (a) Full chromosome 16. (b) Full chromosome 8. (c) Region with increased maternal mutation rate on chromosome 9 (chr9: 0-10,000,000). (d) Region with increased maternal mutation rate on chromosome 2 (chr2: 0-10,000,000).

Supplementary Figure 8

Relation between cSNP C>G score and the number of phased clusters in genomic bins of 1 Mb.

Supplementary Figure 9

DNMs within 100 kb of the two de novo deletion events in the replication cohort.

Supplementary Figure 10 Recombination scores of cDNM regions.

Recombination scores (as defined by Kong et al.20) of cDNM regions. (a) Recombination scores of genomic regions harboring unclustered DNM and cDNM in primary cohort. (b) Recombination scores of genomic regions harboring unclustered DNM and cDNM in replication cohort. (c) Recombination scores of genomic regions harbouring cSNPs. The numbers indicate one-sided p-values for a difference between the groups, based on Wilcoxon rank sum test.

Supplementary Figure 11 Fitting of cancer signatures.

(a) Fitting to unclustered DNMs and cDNMs. (b) Fitting to maternal cDNMs and paternal cDNMs. The solid error bars indicate the standard deviation of resampled mutations’ contributions; the dashed error bars indicate 95% confidence intervals of the resampled mutations’ contributions.

Supplementary Figure 12 Principal component analysis of sequencing-quality statistics.

The quality control variables are described in Supplementary Table 18. (a) First two principal components plotted against each other and colored by software version of data analysis pipeline. Spearman-correlation coefficient of PC1 and average coverage: −0.893. (b) Variance explained by principal components. (c) Principal components two and three plotted against each other and colored by estimated ancestry of sequenced individual.

Supplementary Figure 13

Number of callable bases by sequencing batch.

Supplementary Figure 14

Number of filtered DNMs versus average genome coverage in the proband.

Supplementary Figure 15 C>G mutations in cSNPs.

(a) cSNPs depleted by CpG>CpT mutations, but enriched by remaining C>G mutations, reproducing hallmarks of cDNM spectra. (b) Fraction of non-CpG C>G nucleotide substitutions in cSNP spectra decreases with inter-mutational distances, showing a lower fraction of real clusters at higher distances.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–15, Supplementary Note and Supplementary Tables 1–4, 7–12, 14–25

Life Sciences Reporting Summary

Supplementary Table 5: cDNMs

List of clustered DNMs

Supplementary Table 6: Clusters per trio

Number of clusters per trio

Supplementary Table 13: cSNPs

List of cSNPs

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Goldmann, J.M., Seplyarskiy, V.B., Wong, W.S.W. et al. Germline de novo mutation clusters arise during oocyte aging in genomic regions with high double-strand-break incidence. Nat Genet 50, 487–492 (2018). https://doi.org/10.1038/s41588-018-0071-6

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