Abstract
Germline mutations are a driving force behind genome evolution and genetic disease. We investigated genome-wide mutation rates and spectra in multi-sibling families. The mutation rate increased with paternal age in all families, but the number of additional mutations per year differed by more than twofold between families. Meta-analysis of 6,570 mutations showed that germline methylation influences mutation rates. In contrast to somatic mutations, we found remarkable consistency in germline mutation spectra between the sexes and at different paternal ages. In parental germ line, 3.8% of mutations were mosaic, resulting in 1.3% of mutations being shared by siblings. The number of these shared mutations varied significantly between families. Our data suggest that the mutation rate per cell division is higher during both early embryogenesis and differentiation of primordial germ cells but is reduced substantially during post-pubertal spermatogenesis. These findings have important consequences for the recurrence risks of disorders caused by de novo mutations.
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Acknowledgements
We thank D. Conrad and A. Ramu for their responsive development of the DeNovoGear software and A. Campbell and S. Kerr for their support in identifying relevant families. This research was funded by the Wellcome Trust (grant WT098051). Generation Scotland has received core funding from the Chief Scientist Office of the Scottish Government Health Directorates CZD/16/6 and the Scottish Funding Council HR03006. This study makes use of data generated by the UK10K Consortium, derived from samples from ALSPAC and TwinsUK. A full list of the investigators who contributed to the generation of the data is available from http://www.uk10k.org. Funding for UK10K was provided by the Wellcome Trust under award WT091310. Data can be accessed at the European Genome-phenome Archive (EGA) under accessions EGAS00001000108 and EGAS00001000090.
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R.R., A.W. and M.E.H. developed analytical methods and/or analyzed sequencing data. R.R. performed mutation rate estimation, family comparison, analysis of germline mosaicism and validation. A.W. performed meta-analysis of the DNMs for mutational spectrum and methylation status. S.J.L. and R.J.H. contributed toward phasing and the detection and validation of DNMs. L.B.A. performed mutational signature analysis. S.A.T. contributed to whole-genome data analysis. A.D., A.M., D.P. and B.S. provided blood samples for the Scottish Family Health Study. M.R.S. advised on mutational processes. The UK10K Consortium contributed sequences for meta-data analysis. R.R., A.W. and M.E.H. wrote the manuscript. M.E.H. supervised the project.
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Supplementary Figure 1 Schematic diagram depicting embryogenesis and gametogenesis.
Depending on the timing of mutations during embryonic development, different types of germline mosaicism can arise; star signs indicate different stages at which mutations can arise and the consequential types of mosaicism. Multiple arrows indicate separation of primordial germ cells (PGCs) from other tissues (suggesting that both blood and germ cell lineages are founded by multiple cells from the embryo). Germline mosaic variants, which were detectable in the parents’ blood, were likely established before mesoderm tissue separation from PGCs in the parents (dark green stars). One possible explanation for mosaic mutations that are only shared by siblings—we could not detect any excess of alternative alleles in the parents’ blood—is that the mutations occurred after separation of PGCs from mesoderm in the mosaic parents (red stars).
Supplementary Figure 2 Maternal versus paternal excess ALT allele.
Log-scaled P values (Bonferroni adjusted < 0.05) for all the germline mosaic sites.
Supplementary Figure 3 Validation sequencing depth of samples.
Dark green, depth at all sites; light green, depth at mosaic sites. We note that there are no noticeable trends concerning the depth for mothers, fathers and children.
Supplementary Figure 4 Derived allele frequency versus frequency of mutation types.
The proportion of C:G>T:A transitions (red), T:A>C:G (light blue) and transversions (dark blue) in DNMs (left panel), at differing derived allele frequencies (center panel) and in chimpanzee-human substitutions (right panel). Vertical lines represent 95% confidence intervals for DNM frequencies. The confidence intervals for the diversity and divergence data are too narrow to be marked.
Supplementary Figure 5 Difference between the mutational spectra of rare variants (5% of UK10K variants in the lowest DAF quantile, n = 3,217) on the X and Y chromosomes.
The greatest difference between the spectra of the two chromosomes was that C:G>A:T variants are more prevalent on the Y chromosome and transitions (C:G>T:A and T:A>C:G) are more prevalent on the X chromosome (Fig. 5b). This observation holds both before and after correcting for chromosome-specific base frequencies. However, the overall difference in mutational spectrum between the X and Y chromosomes is not significant (P = 0.10, χ2 test). This confirms our previous observation that, despite the differences in mutation rates, numbers of genome divisions and cellular contexts, the mutation spectra in the maternal and paternal germ lines are very similar.
Supplementary Figure 6 Mutational signatures for the catalog of 6,570 high-confidence DNMs.
Signatures 1 and 5 are responsible for the majority of DNMs. The mutational spectra of 1,643 of the total DNMs comprise signature 1, and 4,839 DNMs comprise signature 5.
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Supplementary Text and Figures
Supplementary Figures 1–6, Supplementary Tables 1–5 and Supplementary Note. (PDF 588 kb)
Supplementary Data Set 1
Validated DNMs, candidate mosaic SNVs and validated mosaic SNVs (XLSX 100 kb)
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Rahbari, R., Wuster, A., Lindsay, S. et al. Timing, rates and spectra of human germline mutation. Nat Genet 48, 126–133 (2016). https://doi.org/10.1038/ng.3469
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DOI: https://doi.org/10.1038/ng.3469
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