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Error-prone bypass of DNA lesions during lagging-strand replication is a common source of germline and cancer mutations

Nature Genetics (2018) | Download Citation

Abstract

Studies in experimental systems have identified a multitude of mutational mechanisms including DNA replication infidelity and DNA damage followed by inefficient repair or replicative bypass. However, the relative contributions of these mechanisms to human germline mutation remain unknown. Here, we show that error-prone damage bypass on the lagging strand plays a major role in human mutagenesis. Transcription-coupled DNA repair removes lesions on the transcribed strand; lesions on the non-transcribed strand are preferentially converted into mutations. In human polymorphism we detect a striking similarity between mutation types predominant on the non-transcribed strand and on the strand lagging during replication. Moreover, damage-induced mutations in cancers accumulate asymmetrically with respect to the direction of replication, suggesting that DNA lesions are resolved asymmetrically. We experimentally demonstrate that replication delay greatly attenuates the mutagenic effect of ultraviolet irradiation, confirming that replication converts DNA damage into mutations. We estimate that at least 10% of human mutations arise due to DNA damage.

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Data availability

Experimental data generated in this study have been deposited in the Sequence Read Archive under accession SRP151915.

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Acknowledgements

We thank S. Mirkin, D. Gordenin, C. Cassa and D. Weghorn for useful comments on the manuscript; L. Sanz and F. Chédin for help with R-loop data; and B. Boulerice for proofreading. This study was supported by National Institutes of Health (NIH) grants R35GM127131, R01MH101244 and U01HG009088; N.A. was supported by the Russian Science Foundation grant 16–15–10273, S.I.N. was supported by grant Foundation ARC 2017, Foundation Gustave Roussy and Swiss Cancer League KFC-3985-08-2016.

Author information

Author notes

    • Evgeny E. Akkuratov

    Present address: Science for Life Laboratory, Department of Applied Physics, Royal Institute of Technology, Stockholm, Sweden

  1. These authors contributed equally: Vladimir B. Seplyarskiy, Evgeny E. Akkuratov, Natalia Akkuratova.

Affiliations

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

    • Vladimir B. Seplyarskiy
    •  & Shamil R. Sunyaev
  2. Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA

    • Vladimir B. Seplyarskiy
    •  & Shamil R. Sunyaev
  3. Institute for Information Transmission Problems (Kharkevich Institute), Russian Academy of Sciences, Moscow, Russia

    • Vladimir B. Seplyarskiy
    •  & Georgii A. Bazykin
  4. Institute of Translational Biomedicine, St. Petersburg State University, St. Petersburg, Russia

    • Evgeny E. Akkuratov
    •  & Natalia Akkuratova
  5. Skolkovo Institute of Science and Technology, Skolkovo, Russia

    • Maria A. Andrianova
    •  & Georgii A. Bazykin
  6. Inserm U981, Gustave Roussy Cancer Campus, Université Paris Saclay, Villejuif, France

    • Sergey I. Nikolaev
  7. Department of Dermatology and Venereology, Université Paris 7, St. Louis Hospital, Paris, France

    • Sergey I. Nikolaev
  8. Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden

    • Igor Adameyko
  9. Center for Brain Research, Medical University of Vienna, Vienna, Austria

    • Igor Adameyko

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Contributions

V.B.S., G.A.B. and S.R.S. designed the study. V.B.S. performed the data analyses. V.B.S., E.E.A., N.A. and I.A. designed and performed experiments. M.A.A. performed data preprocessing and helped with results presentation. S.I.N. retrieved genomic data for squamous cell carcinoma. V.B.S. and S.R.S. drafted the manuscript. All authors contributed to the final version of the paper.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Shamil R. Sunyaev.

Integrated supplementary information

  1. Supplementary Figure 1 Concordance of R-asymmetries across different contexts between SNPs and de novo mutations.

    The sparsity of currently available data on de novo mutations forces us to rely on the human polymorphism data as a proxy. R-asymmetry was calculated for six mutation types and one adjacent nucleotide (5′ in the left panel and 3′ in the right panel). We used one adjacent nucleotide rather than two because of insufficient data. CpG>TpG mutations were excluded; in the left panel, CpG>GpG and CpG>ApG mutations were also excluded because of the low numbers of de novo mutations of these types. De novo mutations were obtained from Francioli et al. and Wong et al. The P values for the correlations are 1.4 × 10–3 for the left panel and 3.3 × 10–4 for the right panel.

  2. Supplementary Figure 2 R-asymmetry and T-asymmetry patterns in human polymorphism for pentanucleotide contexts.

    Relationship between R-asymmetry and T-asymmetry for pentanucleotide contexts; all contexts containing CpG sites are excluded.

  3. Supplementary Figure 3 T-asymmetry and R-asymmetry are correlated in tumor samples (each dot represents one tumor).

    Relationship between R-asymmetry and T-asymmetry for tumor samples; only damage-induced mutations are considered (C>T for melanoma, G>T for LUAD and LUSC, and A>G for liver cancer).

  4. Supplementary Figure 4 Lagging-strand bias is absent among G>T mutations in MUTYH-deficient cancer samples.

    Error bars correspond to 95% confidence intervals, calculated as the ratio of two binomial proportions based on likelihood scores (riskscoreci() function in R).

  5. Supplementary Figure 5 Effect of XPC status on the level of R-asymmetry.

    R-asymmetry for skin cancers. Bars corresponding to patients with xeroderma pigmentosum due to loss-of-function mutation in the XPC gene are colored red; bars corresponding to patients with intact XPC are colored turquoise. The P values is for two-sided Mann–Whitney U test.

  6. Supplementary Figure 6 T-asymmetry of UV-induced damage.

    T-asymmetry of repaired CPD damage (left) and remaining CPD damage (right) as a function of time since UV irradiation.

  7. Supplementary Figure 7 CpG>TpG mutations are biased toward high values of R-asymmetry, and dependence of R-asymmetry on methylation.

    a, Relationship between R-asymmetry and T-asymmetry in the human germ line shows that CpG>TpG mutations (highlighted by red circles) have higher values of T-asymmetry as compared to the expectations based on the values of T-asymmetry. b, CpG>TpG mutations within CpG islands are shown in gray; CpG>TpG mutations in CpG islands are shown in black. The propensity of DNA regions to be replicated as a lagging or a leading strand is shown on the x axis, and log R-asymmetry is shown on the y axis.

  8. Supplementary Figure 8

    T-asymmetry is not elevated in regions prone to R-loops as compared with flanking regions within the same transcript.

  9. Supplementary Figure 9 XPC deficiency is associated with the prevalence of TCT>T mutations.

    Fraction of C>T mutations in all trinucleotide contexts among all mutations. SCC, squamous carcinoma.

  10. Supplementary Figure 10 Quality control for the Damage-seq data.

    a, Values of T-asymmetry. b, Ratio of normalized Damage-seq read density in intergenic regions and genes. c, R-asymmetry. Bars correspond to different replicates.

  11. Supplementary Figure 11 Double staining with Hoechst (green) and EdU (magenta) for each group on the first and second day.

    ah, Groups were stained on the first (ad) and second (eh) day. a,e, Control groups; b,f, UV-irradiated groups; c,g, roscovitine-treated groups; d,h, UV-irradiated with roscovitine-treated groups. Scale, 50 µm.

  12. Supplementary Figure 12 Example of EdU staining in the control group on the first day.

    Scale, 50 µm.

  13. Supplementary Figure 13 Proliferation rate on the first and second day after UV irradiation.

    Proliferation was measured as the ratio between the number of EdU-incorporated cells and total cell number. Day 1 and day 2 represent 24 and 48 h after UV irradiation, respectively. Each box plot represents 15 different areas on 3 coverslips (5 areas for each coverslip).

  14. Supplementary Figure 14 Number of mutations and mutational spectra for all replicates obtained in the experiment.

    Three of five bar plots were already shown in Fig. 5.

Supplementary information

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    Supplementary Figures 1–14, Supplementary Tables 1–3 and Supplementary Notes 1 and 2

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DOI

https://doi.org/10.1038/s41588-018-0285-7