N6-methyladenosine regulates the stability of RNA:DNA hybrids in human cells

Abstract

R-loops are nucleic acid structures formed by an RNA:DNA hybrid and unpaired single-stranded DNA that represent a source of genomic instability in mammalian cells1,2,3,4. Here we show that N6-methyladenosine (m6A) modification, contributing to different aspects of messenger RNA metabolism5,6, is detectable on the majority of RNA:DNA hybrids in human pluripotent stem cells. We demonstrate that m6A-containing R-loops accumulate during G2/M and are depleted at G0/G1 phases of the cell cycle, and that the m6A reader promoting mRNA degradation, YTHDF2 (ref. 7), interacts with R-loop-enriched loci in dividing cells. Consequently, YTHDF2 knockout leads to increased R-loop levels, cell growth retardation and accumulation of γH2AX, a marker for DNA double-strand breaks, in mammalian cells. Our results suggest that m6A regulates accumulation of R-loops, implying a role for this modification in safeguarding genomic stability.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: m6A marks the RNA components of RNA:DNA hybrids in hPSCs.
Fig. 2: m6A is present on the majority of RNA:DNA hybrids in hPSCs.
Fig. 3: RNA:DNA hybrids exhibit cell cycle-specific dynamics in hPSCs.
Fig. 4: m6A reader proteins interact with RNA:DNA hybrids.
Fig. 5: YTHDF2 depletion leads to accumulation of R-loops, increased accretion of m6A on RNA:DNA hybrids and cell growth retardation.
Fig. 6: YTHDF2 depletion leads to elevated levels of H2AX phosphorylation in human and mouse cells.

Data availability

The confocal raw data that support the findings of this study are available from the corresponding author on request, due to size considerations. The deep-sequencing data have been deposited in the NCBI Sequence Read Archive with the Bioproject ID: PRJNA474076. The annotated bed files have been deposited in the following online repository: https://bitbucket.org/ADAC_UoN/adac1075-bed-files/src. Source data for Fig. 4, Extended Data Fig. 9 and Supplementary Fig. 9 are provided with the paper.

Code availability

The in-house scripts used for the analysis can be found in the following online repository: https://bitbucket.org/ADAC_UoN/adac0175-code/src.

References

  1. 1.

    Chédin, F. Nascent connections: R-loops and chromatin patterning. Trends Genet. 32, 828–838 (2016).

  2. 2.

    Sanz, L. A. et al. Prevalent, dynamic, and conserved R-loop structures associate with specific epigenomic signatures in mammals. Mol. Cell 63, 167–178 (2016).

  3. 3.

    Lu, W. T. et al. Drosha drives the formation of DNA:RNA hybrids around DNA break sites to facilitate DNA repair. Nat. Commun. 9, 532 (2018).

  4. 4.

    Santos-Pereira, J. M. & Aguilera, A. R-loops: new modulators of genome dynamics and function. Nat. Rev. Genet. 16, 583–597 (2015).

  5. 5.

    Yue, Y., Liu, J. & He, C. RNA N6-methyladenosine methylation in post-transcriptional gene expression regulation. Genes Dev. 29, 343–355 (2015).

  6. 6.

    Roundtree, I. A., Evans, M. E., Pan, T. & He, C. Dynamic RNA modifications in gene expression regulation. Cell 169, 1187–1200 (2017).

  7. 7.

    Wang, X. et al. N6-methyladenosine-dependent regulation of messenger RNA stability. Nature 7481, 117–120 (2014).

  8. 8.

    Zhang, G. et al. N6-methyladenine DNA modification in Drosophila. Cell 161, 893–906 (2015).

  9. 9.

    Greer, E. L. et al. DNA methylation on N6-adenine in C. elegans. Cell 161, 868–878 (2015).

  10. 10.

    Fu, Y. et al. N6-methyldeoxyadenosine marks active transcription start sites in Chlamydomonas. Cell 161, 879–892 (2015).

  11. 11.

    Mondo, S. J. et al. Widespread adenine N6-methylation of active genes in fungi. Nat. Genet. 49, 964–968 (2017).

  12. 12.

    Liu, J. et al. Abundant DNA 6mA methylation during early embryogenesis of zebrafish and pig. Nat. Commun. 7, 13052 (2016).

  13. 13.

    Yao, B. et al. DNA N6-methyladenine is dynamically regulated in the mouse brain following environmental stress. Nat. Commun. 8, 1122 (2017).

  14. 14.

    Schiffers, S. et al. Quantitative LC–MS provides no evidence for m(6) dA or m(4) dC in the genome of mouse embryonic stem cells and tissues. Angew Chem. Int. Ed. Engl. 56, 11268–11271 (2017).

  15. 15.

    Wheldon, L. M. et al. Transient accumulation of 5-carboxylcytosine indicates involvement of active demethylation in lineage specification of neural stem cells. Cell Rep. 7, 1353–1361 (2014).

  16. 16.

    Santos, F. & Dean, W. Using immunofluorescence to observe methylation changes in mammalian preimplantation embryos. Methods Mol. Biol. 325, 129–137 (2006).

  17. 17.

    Rieder, C. L. & Palazzo, R. E. Colcemid and the mitotic cycle. J. Cell Sci. 102, 387–392 (1992).

  18. 18.

    Pfaffeneder, T. et al. The discovery of 5-formylcytosine in embryonic stem cell DNA. Angew Chem. Int. Ed. Engl. 50, 7008–7012 (2011).

  19. 19.

    Chan, Y. A. et al. Genome-wide profiling of yeast DNA:RNA hybrid prone sites with DRIP-chip. PLoS Genet. 10, e1004288 (2014).

  20. 20.

    Boguslawski, S. J. et al. Characterization of monoclonal antibody to DNA.RNA and its application to immunodetection of hybrids. J. Immunol. Methods 89, 123–130 (1986).

  21. 21.

    Mita, P. et al. LINE-1 protein localization and functional dynamics during the cell cycle. eLife 7, e30058 (2018).

  22. 22.

    Cristini, A., Groh, M., Kristiansen, M. S. & Gromak, N. RNA/DNA Hybrid interactome identifies DXH9 as a molecular player in transcriptional termination and R-loop-associated DNA damage. Cell Rep. 23, 1891–1905 (2018).

  23. 23.

    Wang, X. et al. N(6)-methyladenosine modulates messenger RNA translation efficiency. Cell 161, 1388–1399 (2015).

  24. 24.

    Alarcón, C. R. et al. HNRNPA2B1 is a mediator of m(6)A-dependent nuclear RNA processing events. Cell 162, 1299–12308 (2015).

  25. 25.

    Carette, J. E. et al. Haploid genetic screens in human cells identify host factors used by pathogens. Science 5957, 1231–1235 (2009).

  26. 26.

    Li, M. et al. Ythdf2-mediated m(6)A mRNA clearance modulates neural development in mice. Genome Biol. 19, 69 (2018).

  27. 27.

    Bonner, W. M. et al. GammaH2AX and cancer. Nat. Rev. Cancer. 8, 957–967 (2008).

  28. 28.

    Paulsen, R. D. et al. A genome-wide siRNA screen reveals diverse cellular processes and pathways that mediate genome stability. Mol. Cell 35, 228–239 (2009).

  29. 29.

    Salas-Armenteros, I. et al. Human THO-Sin3A interaction reveals new mechanisms to prevent R-loops that cause genome instability. EMBO J. 36, 3532–3547 (2017).

  30. 30.

    Bayona-Feliu, A., Casas-Lamesa, A., Reina, O., Bernués, J. & Azorín, F. Linker histone H1 prevents R-loop accumulation and genome instability in heterochromatin. Nat. Commun. 8, 283 (2017).

  31. 31.

    Benitez-Guijarro, M. et al. RNase H2, mutated in Aicardi–Goutières syndrome, promotes LINE-1 retrotransposition. EMBO J. 37, e98506 (2018).

  32. 32.

    Pozarowski, P. & Darzynkiewicz, Z. Analysis of cell cycle by flow cytometry. Methods Mol. Biol. 281, 301–311 (2004).

  33. 33.

    Bubeck, D. et al. PCNA directs type 2 RNase H activity on DNA replication and repair substrates. Nucleic Acids Res. 39, 3652–3266 (2011).

  34. 34.

    Abakir, A., Wheldon, L., Johnson, A. D., Laurent, P. & Ruzov, A. Detection of modified forms of cytosine using sensitive immunohistochemistry. J. Vis. Exp. https://doi.org/10.3791/54416 (2016).

  35. 35.

    Hamperl, S., Bocek, M. J., Saldivar, J. C., Swigut, T. & Cimprich, K. A. Transcription–replication conflict orientation modulates R-loop levels and activates distinct DNA damage responses. Cell. 170, 774–786 (2017).

  36. 36.

    Ramsawhook, A. H. et al. Immunostaining for DNA modifications: computational analysis of confocal images. J. Vis. Exp. https://doi.org/10.3791/5631 (2017).

  37. 37.

    Gackowski, D. et al. Accurate, direct, and high-throughput analyses of a broad spectrum of endogenously generated DNA base modifications with isotope-dilution two-dimensional ultraperformance liquid chromatography with tandem mass spectrometry: possible clinical implication. Anal. Chem. 88, 12128–12136 (2016).

  38. 38.

    Groh, M., Lufino, M. M., Wade-Martins, R. & Gromak, N. R-loops associated with triplet repeat expansions promote gene silencing in Friedreich ataxia and fragile X syndrome. PLoS Genet. 10, e1004318 (2014).

  39. 39.

    Ginno, P. A., Lott, P. L., Christensen, H. C., Korf, I. & Chédin, F. R-loop formation is a distinctive characteristic of unmethylated human CpG island promoters. Mol. Cell 45, 814–825 (2012).

  40. 40.

    Weber, M. et al. Chromosome-wide and promoter-specific analyses identify sites of differential DNA methylation in normal and transformed human cells. Nat. Genet. 37, 853–862 (2005).

  41. 41.

    Jachowicz, J. W. et al. LINE-1 activation after fertilization regulates global chromatin accessibility in the early mouse embryo. Nat. Genet. 49, 1502–1510 (2017).

  42. 42.

    Jiang, H., Lei, R., Ding, S. W. & Zhu, S. Skewer: a fast and accurate adapter trimmer for next-generation sequencing paired-end reads. BMC Bioinformatics 15, 182 (2014).

  43. 43.

    Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009).

  44. 44.

    Li, H. et al. 1000 Genome Project Data Processing Subgroup. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).

  45. 45.

    Chang, V. Y., Federman, N., Martinez-Agosto, J., Tatishchev, S. F. & Nelson, S. F. Whole exome sequencing of pediatric gastric adenocarcinoma reveals an atypical presentation of Li–Fraumeni syndrome. Pediatr. Blood Cancer 60, 570–574 (2013).

  46. 46.

    Marinov, G. K., Kundaje, A., Park, P. J. & Wold, B. J. Large-scale quality analysis of published ChIP-seq data. G3 (Bethesda) 4, 209–223 (2014).

  47. 47.

    Zhang, Y. et al. Model-based analysis of ChIP-seq (MACS). Genome Biol. 9, R137 (2008).

  48. 48.

    Ross-Innes, C. S. et al. Differential oestrogen receptor binding is associated with clinical outcome in breast cancer. Nature 7381, 389–393 (2012).

Download references

Acknowledgements

We thank V. Wright, S. Malla, M. Loose, S. Rajani, D. Mosqueira, L. Lewis, R. Marcus, D. Onion, D. Bates and B. Coyle for technical help; D. Huangfu (Memorial Sloan Kettering Cancer Center) for the hPSC promoters dataset; and S. Peña Perez for animal care. This work was supported by a Medical Research Council IMPACT DTP PhD Studentship (grant no. MR/N013913/1) to A.A and by the Biotechnology and Biological Sciences Research Council (grant no. BB/N005759/1) to A.R. N.G.’s laboratory is supported by a Royal Society University Research Fellowship and a John Fell award (grant no. BVD07340) to N.G. J.L.G.-P.’s laboratory is supported by MINECO-FEDER (grant no. SAF2017-89745-R) to J.L.G.-P., the European Research Council (grant no. ERC-Consolidator ERC-STG-2012-233764) to J.L.G.-P. and a private donation from F. Serrano (Trading y Bolsa para Torpes, Granada, Spain). C.D. is supported by the British Heart Foundation (nos. SP/15/9/31605 and PG/14/59/31000), the Medical Research Council (no. MR/M017354/1), NC3Rs (no. CRACK-IT:35911-259146) and Heart Research UK (no. TRP01/12). L.Y. was supported by the Medical Research Council (grant no. MR/M017354/1). A.K. is supported by the Norwegian Research Council (grant no. 275286) and Health Authority South-East (grant no. 2018086). B.D. is supported by Norwegian Health Authority South-East (Regional Core Facility for Structural Biology) (grant no. 2015095). D.J.G. is funded by the Wellcome Trust (grant no. WT206194). This work was partially supported by Health Data Research UK, an initiative funded by UK Research and Innovation, Department of Health and Social Care (England) and the devolved administrations, and leading medical research charities.

Author information

A.A. performed immunostaining, microscopy, DRIP, DIP, RNA-seq, ChIP, qPCR, FACS sorting, cell culture experiments and contributed to bioinformatics analysis and data interpretation. T.C.G., A.R.R., J.L.G.-P. and R.D.E. performed bioinformatics analysis. A.C. and N.G. performed S9.6 immunoprecipitation and immunoblots. J.M.F., N.D. and I.R.C. performed LC–MS/MS. M.S. and D.G. performed SID–UPLC–MS/MS. A.R., A.A., M.L. and A.K. contributed to EMSA and mouse KO experiments. M.L., B.D. and A.K. generated His-fused YTHDF2 and performed MST. M.E. provided cell line samples. J.C., L.F, L.Y., C.D. and D.J.G. provided the WT REBL-PAT transcriptome dataset. A.R. conceived, designed and coordinated the study and drafted the manuscript together with A.A., N.G., J.L.G.-P. and I.R.C. All authors read and approved the final manuscript.

Correspondence to Arne Klungland or Natalia Gromak or Alexey Ruzov.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Validation of m6A DIP using synthetic RNA and DNA substrates.

Validation of m6A DIP using synthetic RNA and DNA substrates. See also Supplementary Note. (a) Schematic demonstrating the sequences of synthetic oligonucleotides and RNA:DNA hybrids used for spike in validation experiments. (b) The relative enrichment of DIP/DRIP performed on 0.1 pmol of spike in synthetic m6A-containing RNA:DNA hybrid (81-mer with 46 % GC content) shown in (a) using anti-m6A and S9.6 antibodies along with IGG for IP after the indicated time intervals of heat denaturation. (c) S9.6 DRIP exhibits comparable efficiencies in precipitating non-modified and m6A-containing RNA:DNA hybrids. Relative enrichment of DRIP performed on the m6A-containing RNA:DNA synthetic substrate normalized against that of DRIP done on equivalent amount (0.1 pmol) of non-modified spike in synthetic RNA:DNA hybrid. (d) The results of m6A DIP on 0.1 pmol of the indicated spike in synthetic oligonucleotides and RNA:DNA hybrids. Unlike non-modified RNA:DNA hybrid substrate or single stranded m6A-containing RNA oligonucleotide, m6A-containing RNA:DNA hybrid is efficiently detected by m6A DIP technique. Data are means ± SD, n = 3 independent experiments.

Extended Data Fig. 2 Detailed schematic illustrating S9.6 DRIP and m6A DIP techniques.

Detailed schematic illustrating S9.6 DRIP and m6A DIP techniques.

Extended Data Fig. 3 m6A is present on the majority of RNA:DNA hybrids in hiPSCs.

m6A is present on the majority of RNA:DNA hybrids in hiPSCs. (a) Heatmaps showing the distribution of density of indicated reads across genomic regions containing peaks (3 kb around peak center) of the three categories: m6A peaks overlapping with S9.6 peaks (m6A/S9.6), m6A peaks that do not overlap with S9.6 DRIP peaks (m6A only) and S9.6 peaks that do not correspond to m6A DIP peaks (S9.6 only). The colour of each line represents the density of reads for a given peak. The width of the heatmaps is normalized by peak length. (b, c) Distribution of the m6A/S9.6-, m6A only- and S9.6 only peaks at the indicated genomic features (b) and relative to transcription start site (TSS) (c) in hiPSCs.

Extended Data Fig. 4 RNA:DNA hybrids exhibit cell cycle-specific dynamics in hPSCs.

RNA:DNA hybrids exhibit cell cycle-specific dynamics in hPSCs. (a) The diagram illustrating gating of single hiPSCs using PI-Area and PI-Width signals (left panel) and DNA content frequency histogram (right panel) of a representative hiPSCs population used for cell cycle analysis. hPSCs at G0/G1, S and G2/M phases are marked. (b) The coverage plots of m6A DIP and S9.6 DRIP densities (CPK) in the intronic regions of the indicated genes. m6A and S9.6 peaks are marked with red and blue rectangles.

Extended Data Fig. 5 m6A DIP signal is increased upon RNase H1 knockdown in hPSCs.

m6A DIP signal is increased upon RNase H1 knockdown in hPSCs. (a, b) The coverage plots of m6A and S9.6 DRIP/DIP densities (CPK) in the regions located downstream of the m6A and S9.6 peaks (marked with red rectangles). The location of regions that were used as controls in (d) is designated by blue rectangles. (c) Relative expression of RNase H1 and LINE1 transcripts in hPSCs transfected with control non-targeting (siCTL) and RNase H1 (siRNaseH1) siRNAs. (d) The results of m6A DIP qPCR of the indicated repeats and intronic sequences performed on siCTL and siRNaseH1 hiPSCs. The regions without peaks (RANBP17 Downstream and HECW1 Downstream) were used as controls. Generic primers amplifying Alu elements from the indicated families and evolutionarily young L1Hs were used for DRIP qPCRs and qPCR. Data are means ± SD, n = 3 independent experiments.

Extended Data Fig. 6 m6A is detectable on the RNA components of R-loops.

m6A is detectable on the RNA components of R-loops. (a) Schematic representation of the two round (S9.6 followed by m6A) DRIP/DIP procedure. (b, c) The results of the two round (S9.6 DRIP followed by m6A DIP) DRIP/DIP performed on individual intronic (b) and repetitive (c) m6A/S9.6 peak containing sequences. (d) Schematic representation of the m6A RIP performed on the RNA isolated from S9.6 IP-ed nucleic acids, followed by RT-qPCR of the candidate sequences. (e) The results of the m6A RIP performed on the S9.6 DRIP of individual and repetitive DRIP/m6A DIP-peak containing sequences. No RT represents control samples processed without reverse transcription. The regions without peaks (RANBP17 Downstream and HECW1 Downstream) were used as controls in (b and e). Representative results of analysis of one of 3 independent biological samples are presented. Data are means ± SD, n = 3 technical repeats.

Extended Data Fig. 7 METTL3 depletion leads to accumulation of RNA:DNA hybrids in hPSCs.

METTL3 depletion leads to accumulation of RNA:DNA hybrids in hPSCs. (a) The results of S9.6 DRIP qPCR of the indicated repeats and intronic sequences performed on siCTL and siMETTL3 hiPSCs sorted at different cell cycle phases. (b) Relative expression of the indicated transcripts in siCTL and siMETTL3 hiPSCs. The difference between the values of Y-axes in (a) and in Fig. 3b is due to incorporation of RNase H control samples in the analysis shown in Fig. 3b. Data are means ± SD, n = 3 independent experiments.

Extended Data Fig. 8 METTL3 depletion leads to an increase in the m6A DIP peaks in hPSCs.

METTL3 depletion leads to an increase in the m6A DIP peaks in hPSCs. (a) SID-UPLC-MS/MS quantification of m6A in the total nucleic acids (left panel), and in ultrafiltrate fractions released upon RNase H treatment of siCTL and siMETTL3 hPSCs (right panel). The data are means of 2 independent experiments. (b) The total numbers of consensus m6A peaks in WT and siMETTL3 hiPSCs. (c) Heatmaps showing the distribution of density of indicated reads across peak-containing genomic regions (3 kb around peak center) for S9.6 DRIP in WT and m6A DIP in WT and siMETTL3 hPSCs. The colour of each line represents the density of reads for a given peak. The width of the heatmaps is normalized by peak length. (d) Pie chart showing the percentages of transcripts differentially expressed between siCTL and siMETTL3 hPSCs (p < 0.01) and without significant changes in expression amongst genes containing siMETTL3-specific m6A peaks. P values were calculated using the Standard ballgown parametric F-test. (e) Pie chart demonstrating the percentages of genes differentially expressed between siCTL and siMETTL3 hPSCs containing siMETTL3-specific m6A peaks (diff peaks) and without such peaks (No diff peaks). (f) Average profile of m6A peak densities for all genes sorted based on levels of their expression in siMETTL3 hPSCs. The colour gradient represents log10 of mean RPKM per bin. (g) Average profile of m6A peak densities for all genes sorted based on the fold change of their expression between siCTL and siMETTL3 hPSCs. The colour gradient represents log10 of mean fold change (FC) per bin.

Extended Data Fig. 9 YTHDF2 co-localizes with R-loops in vivo and interacts with synthetic m6A-marked RNA:DNA hybrids in vitro.

YTHDF2 co-localizes with R-loops in vivo and interacts with synthetic m6A-marked RNA:DNA hybrids in vitro. (a) Co-immunostaining of YTHDF2 with R-loops (S9.6) in a representative hiPSCs interphase nucleus. Merged view and individual channels are shown. The area used for S9.6/YTHDF2 signals quantification is indicated. The arrow designates the region used for generation of signal intensity profile shown in (b). (b) The profile showing intensities of YTHDF2, S9.6 and 4,6-diamidino-2-phenylindole (DAPI) signals across the nuclear region marked with an arrow in (a). (c) Representative image of hPSCs immunostained for YTHDF2 and R-loops. Merged view and YTHDF2/S9.6 channels are shown. Scale bars are 20 μm The experiments shown in (a, c) were repeated independently 3 times with similar results. (d) Scatter diagram for YTHDF2 and S9.6 fluorescence intensities in an individual hPSCs nucleus. (e) The value of overlapping coefficient of YTHDF2 vs S9.6 intensities quantified for 20 cells immunostained for YTHDF2 and S9.6. The centre value is median, error bars show minimal and maximal values. (f, g) The results of EMSA using recombinant YTHDF2-His fusion (f) or YTHDF2-FLAG (g) and 0.15 pmol of unmodified (non) or m6A-containing (meth) RNA oligonucleotides (ssRNA) or corresponding synthetic RNA:DNA hybrids (RNA:DNA). Triangles indicate increasing concentrations of the protein (10, 100, 300 ng). Concentrations of the recombinant protein (g) and NaCl/KCl in the binding buffer are indicated. The RNA and RNA:DNA-protein complexes are arrowed. See also Supplementary Note. The gel images were cropped. The full scans of the gels are shown in Source Data 2.Source Data 2.

Extended Data Fig. 10 YTHDF2 interacts with R-loop-containing loci in vivo and its depletion leads to accumulation of RNA:DNA hybrids in hPSCs.

YTHDF2 interacts with R-loop-containing loci in vivo and its depletion leads to accumulation of RNA:DNA hybrids in hPSCs. (a-f) The results of YTHDF2 (a, c, e) and HNRNPA2B1 (b, d, f) ChIP qPCR of the indicated repeats and intronic sequences performed on REBL-PAT hiPSCs (a, b), siCTL and siMETTL3 hPSCs (c, d) as well as on siCNTL and siRNase H1 hPSCs (e, f). (g) Relative expression of YTHDF2 transcript in hiPSCs transfected with siYTHDF2 siRNAs compared with that in non-targeting control siRNA (siCTL) transfected cells. (h, i) The results of S9.6 DRIP qPCR (h) and m6A DIP qPCR (i) of the indicated repeats and intronic sequences performed on siCTL and siYTHDF2 hiPSCs. Generic primers amplifying Alu elements from the indicated families and evolutionarily young L1Hs were used for DRIP qPCRs and qPCR. The regions without peaks (RANBP17 Downstream and HECW1 Downstream) were used as controls. Representative results of analysis of one of 3 independent biological samples are presented. Data are means ± SD, n = 3 technical repeats.

Supplementary information

Supplementary Information

Supplementary Note, Figs. 1–10 and Table 1

Reporting Summary

Source data

Source Data Fig. 4

Full scans of the blots shown in Fig. 4a.

Source Data Extended Data Fig. 9

Full scans of the gels shown in Extended Data Fig. 9f,g.

Source Data Supplementary Fig. 9

Full scan of the gel shown in Supplementary Fig. 9.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Abakir, A., Giles, T.C., Cristini, A. et al. N6-methyladenosine regulates the stability of RNA:DNA hybrids in human cells. Nat Genet 52, 48–55 (2020). https://doi.org/10.1038/s41588-019-0549-x

Download citation

Further reading