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Absolute quantification of single-base m6A methylation in the mammalian transcriptome using GLORI

Abstract

N6-methyladenosine (m6A) is the most abundant RNA modification in mammalian cells and the best-studied epitranscriptomic mark. Despite the development of various tools to map m6A, a transcriptome-wide method that enables absolute quantification of m6A at single-base resolution is lacking. Here we use glyoxal and nitrite-mediated deamination of unmethylated adenosines (GLORI) to develop an absolute m6A quantification method that is conceptually similar to bisulfite-sequencing-based quantification of DNA 5-methylcytosine. We apply GLORI to quantify the m6A methylomes of mouse and human cells and reveal clustered m6A modifications with differential distribution and stoichiometry. In addition, we characterize m6A dynamics under stress and examine the quantitative landscape of m6A modification in gene expression regulation. GLORI is an unbiased, convenient method for the absolute quantification of the m6A methylome.

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Fig. 1: Glyoxal and nitrite-mediated adenosine deamination.
Fig. 2: Transcriptome-wide m6A identification by GLORI.
Fig. 3: The quantitative landscape of m6A.
Fig. 4: m6A form modification clusters.
Fig. 5: Dynamic m6A induced by stress conditions.

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Data availability

The sequence data generated in this study have been deposited in the NCBI Gene Expression Omnibus (GEO), under accession code GSE210563. The public MAZTER-seq, miCLIP, and m6A-seq datasets were downloaded from the GEO database (GSE122961, GSE63753, SRA280261, and GSE165690). The published ribosome profiling datasets of HEK293T, HeLa, and MEF were download from the GEO database (GSE129194, GSE63591, and SRA280261). The life-time data of HeLa cell line were downloaded from the GEO database (GSE49339). The reference genome GRCh38 and GRCm38 were download from the following link: https://hgdownload.soe.ucsc.edu/downloads.html.

Code availability

The code of the GLORI-tools is available on GitHub from https://github.com/liucongcas/GLORI-tools.

References

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Frye, M., Jaffrey, S. R., Pan, T., Rechavi, G. & Suzuki, T. RNA modifications: what have we learned and where are we headed? Nat. Rev. Genet. 17, 365–372 (2016).

    Article  CAS  PubMed  Google Scholar 

  3. Perry, R. P. & Kelley, D. E. Existence of methylated messenger RNA in mouse L cells. Cell 1, 37–42 (1974).

    Article  CAS  Google Scholar 

  4. Perry, R. P., Kelley, D. E., Friderici, K. & Rottman, F. The methylated constituents of L cell messenger RNA: evidence for an unusual cluster at the 5′ terminus. Cell 4, 387–394 (1975).

    Article  CAS  PubMed  Google Scholar 

  5. Bokar, J. A., Rath-Shambaugh, M. E., Ludwiczak, R., Narayan, P. & Rottman, F. Characterization and partial purification of mRNA N6-adenosine methyltransferase from HeLa cell nuclei. internal mRNA methylation requires a multisubunit complex. J. Biol. Chem. 269, 17697–17704 (1994).

    Article  CAS  PubMed  Google Scholar 

  6. Bokar, J. A., Shambaugh, M. E., Polayes, D., Matera, A. G. & Rottman, F. M. Purification and cDNA cloning of the AdoMet-binding subunit of the human mRNA (N6-adenosine)-methyltransferase. RNA 3, 1233–1247 (1997).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Liu, J. et al. A METTL3–METTL14 complex mediates mammalian nuclear RNA N6-adenosine methylation. Nat. Chem. Biol. 10, 93–95 (2014).

    Article  CAS  PubMed  Google Scholar 

  8. Ping, X. L. et al. Mammalian WTAP is a regulatory subunit of the RNA N6-methyladenosine methyltransferase. Cell Res. 24, 177–189 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Schwartz, S. et al. Perturbation of m6A writers reveals two distinct classes of mRNA methylation at internal and 5– sites. Cell Rep 8, 284–296 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Patil, D. P. et al. m6A RNA methylation promotes XIST-mediated transcriptional repression. Nature 537, 369–373 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Jia, G. et al. N6-methyladenosine in nuclear RNA is a major substrate of the obesity-associated FTO. Nat. Chem. Biol. 7, 885–887 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Zheng, G. et al. ALKBH5 is a mammalian RNA demethylase that impacts RNA metabolism and mouse fertility. Mol. Cell 49, 18–29 (2013).

    Article  CAS  PubMed  Google Scholar 

  13. Barbieri, I. & Kouzarides, T. Role of RNA modifications in cancer. Nat. Rev. Cancer 20, 303–322 (2020).

    Article  CAS  PubMed  Google Scholar 

  14. Livneh, I., Moshitch-Moshkovitz, S., Amariglio, N., Rechavi, G. & Dominissini, D. The m6A epitranscriptome: transcriptome plasticity in brain development and function. Nat. Rev. Neurosci. 21, 36–51 (2020).

    Article  CAS  PubMed  Google Scholar 

  15. Li, X., Xiong, X. & Yi, C. Epitranscriptome sequencing technologies: decoding RNA modifications. Nat. Methods 14, 23–31 (2016).

    Article  PubMed  Google Scholar 

  16. Dominissini, D. et al. Topology of the human and mouse m6A RNA methylomes revealed by m6A-seq. Nature 485, 201–206 (2012).

    Article  CAS  PubMed  Google Scholar 

  17. Meyer, K. D. et al. Comprehensive analysis of mRNA methylation reveals enrichment in 3′ UTRs and near stop codons. Cell 149, 1635–1646 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Chen, K. et al. High-resolution N6-methyladenosine (m6A) map using photo-crosslinking-assisted m6A sequencing. Angew. Chem. Int. Ed. Engl. 54, 1587–1590 (2015).

    Article  CAS  PubMed  Google Scholar 

  19. Linder, B. et al. Single-nucleotide-resolution mapping of m6A and m6Am throughout the transcriptome. Nat. Methods 12, 767–772 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Molinie, B. et al. m6A-LAIC-seq reveals the census and complexity of the m6A epitranscriptome. Nat. Methods 13, 692–698 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Dierks, D. et al. Multiplexed profiling facilitates robust m6A quantification at site, gene and sample resolution. Nat. Methods 18, 1060–1067 (2021).

    Article  CAS  PubMed  Google Scholar 

  22. McIntyre, A. B. R. et al. Limits in the detection of m6A changes using MeRIP/m6A-seq. Sci Rep. 10, 6590 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Sun, H. et al. m6Am-seq reveals the dynamic m6Am methylation in the human transcriptome. Nat. Commun. 12, 4778 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Garcia-Campos, M. A. et al. Deciphering the ‘m6A Code’ via antibody-independent quantitative profiling. Cell 178, 731–747 e716 (2019).

    Article  CAS  PubMed  Google Scholar 

  25. Zhang, Z. et al. Single-base mapping of m6A by an antibody-independent method. Sci. Adv. 5, eaax0250 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Zhang, Z. et al. Systematic calibration of epitranscriptomic maps using a synthetic modification-free RNA library. Nat. Methods 18, 1213–1222 (2021).

    Article  CAS  PubMed  Google Scholar 

  27. Meyer, K. D. DART-seq: an antibody-free method for global m6A detection. Nat. Methods 16, 1275–1280 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Wang, Y., Xiao, Y., Dong, S., Yu, Q. & Jia, G. Antibody-free enzyme-assisted chemical approach for detection of N(6)-methyladenosine. Nat. Chem. Biol. 16, 896–903 (2020).

    Article  CAS  PubMed  Google Scholar 

  29. Shu, X. et al. A metabolic labeling method detects m6A transcriptome-wide at single base resolution. Nat. Chem. Biol. 16, 887–895 (2020).

    Article  CAS  PubMed  Google Scholar 

  30. Hu, L. et al. m6A RNA modifications are measured at single-base resolution across the mammalian transcriptome. Nat. Biotechnol. 40, 1210–1219 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Liu, N. et al. Probing N6-methyladenosine RNA modification status at single nucleotide resolution in mRNA and long noncoding RNA. RNA 19, 1848–1856 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Xiao, Y. et al. An elongation- and ligation-based qPCR amplification method for the radiolabeling-free detection of locus-specific N6-methyladenosine modification. Angew. Chem. Int. Ed. Engl. 57, 15995–16000 (2018).

    Article  CAS  PubMed  Google Scholar 

  33. Aschenbrenner, J. et al. Engineering of a DNA polymerase for direct m6A sequencing. Angew. Chem. Int. Ed. Engl. 57, 417–421 (2018).

    Article  CAS  PubMed  Google Scholar 

  34. Liu, W. et al. Identification of a selective DNA ligase for accurate recognition and ultrasensitive quantification of N6-methyladenosine in RNA at one-nucleotide resolution. Chem. Sci. 9, 3354–3359 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Raiber, E. A., Hardisty, R., van Delft, P. & Balasubramanian, S. Mapping and elucidating the function of modified bases in DNA. Nat. Rev. Chem. 1, 0069 (2017).

    Article  CAS  Google Scholar 

  36. Shapiro, R. & Pohl, S. H. The reaction of ribonucleosides with nitrous acid. Side products and kinetics. Biochemistry 7, 448–455 (1968).

    Article  CAS  PubMed  Google Scholar 

  37. Schuster, H. & Wilhelm, R. C. Reaction differences between tobacco mosaic virus and its free ribonucleic acid with nitrous acid. Biochim. Biophys. Acta 68, 554–560 (1963).

    Article  CAS  PubMed  Google Scholar 

  38. Shapiro, R. & Hachmann, J. The reaction of guanine derivatives with 1,2-dicarbonyl compounds. Biochemistry 5, 2799–2807 (1966).

    Article  CAS  PubMed  Google Scholar 

  39. Nakaya, K., Takenaka, O., Horinishi, H. & Shibata, K. Reactions of glyoxal with nucleic acids. Nucleotides and their component bases. Biochim. Biophys. Acta 161, 23–31 (1968).

    Article  CAS  PubMed  Google Scholar 

  40. Broude, N. E. & Budowsky, E. I. The reaction of glyoxal with nucleic acid components. 3. Kinetics of the reaction with monomers. Biochim. Biophys. Acta 254, 380–388 (1971).

    Article  CAS  PubMed  Google Scholar 

  41. Cattenoz, P. B., Taft, R. J., Westhof, E. & Mattick, J. S. Transcriptome-wide identification of A > I RNA editing sites by inosine specific cleavage. RNA 19, 257–270 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Knutson, S. D., Arthur, R. A., Johnston, H. R. & Heemstra, J. M. Selective enrichment of A-to-I edited transcripts from cellular RNA using endonuclease V. J. Am. Chem. Soc. 142, 5241–5251 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Kivioja, T. et al. Counting absolute numbers of molecules using unique molecular identifiers. Nat. Methods 9, 72–74 (2011).

    Article  PubMed  Google Scholar 

  44. Islam, S. et al. Quantitative single-cell RNA-seq with unique molecular identifiers. Nat. Methods 11, 163–166 (2014).

    Article  CAS  PubMed  Google Scholar 

  45. Wei, J. et al. Differential m6A, m6Am, and m1A demethylation mediated by FTO in the cell nucleus and cytoplasm. Mol. Cell 71, 973–985 e975 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Levanon, E. Y. et al. Systematic identification of abundant A-to-I editing sites in the human transcriptome. Nat. Biotechnol. 22, 1001–1005 (2004).

    Article  CAS  PubMed  Google Scholar 

  47. Tan, M. H. et al. Dynamic landscape and regulation of RNA editing in mammals. Nature 550, 249–254 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  48. Huang, T., Chen, W., Liu, J., Gu, N. & Zhang, R. Genome-wide identification of mRNA 5-methylcytosine in mammals. Nat. Struct. Mol. Biol. 26, 380–388 (2019).

    Article  CAS  PubMed  Google Scholar 

  49. Yang, X. et al. 5-methylcytosine promotes mRNA export—NSUN2 as the methyltransferase and ALYREF as an m5C reader. Cell Res. 27, 606–625 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Yankova, E. et al. Small-molecule inhibition of METTL3 as a strategy against myeloid leukaemia. Nature 593, 597–601 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Zhou, J. et al. Dynamic m6A mRNA methylation directs translational control of heat shock response. Nature 526, 591–594 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Meyer, K. D. et al. 5′ UTR m6A promotes cap-independent translation. Cell 163, 999–1010 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Mahdavi-Amiri, Y., Chung Kim Chung, K. & Hili, R. Single-nucleotide resolution of N6-adenine methylation sites in DNA and RNA by nitrite sequencing. Chem. Sci. 12, 606–612 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  54. Werner, S. et al. NOseq: amplicon sequencing evaluation method for RNA m6A sites after chemical deamination. Nucleic Acids Res. 49, e23 (2021).

    Article  CAS  PubMed  Google Scholar 

  55. Moore, L. D., Le, T. & Fan, G. DNA methylation and its basic function. Neuropsychopharmacology 38, 23–38 (2013).

    Article  CAS  PubMed  Google Scholar 

  56. Mohn, F. et al. Lineage-specific polycomb targets and de novo DNA methylation define restriction and potential of neuronal progenitors. Mol. Cell 30, 755–766 (2008).

    Article  CAS  PubMed  Google Scholar 

  57. Dawson, M. A. & Kouzarides, T. Cancer epigenetics: from mechanism to therapy. Cell 150, 12–27 (2012).

    Article  CAS  PubMed  Google Scholar 

  58. Esteller, M. Cancer epigenomics: DNA methylomes and histone-modification maps. Nat. Rev. Genet. 8, 286–298 (2007).

    Article  CAS  PubMed  Google Scholar 

  59. Jones, P. A. Functions of DNA methylation: islands, start sites, gene bodies and beyond. Nat. Rev. Genet. 13, 484–492 (2012).

    Article  CAS  PubMed  Google Scholar 

  60. Horvath, S. & Raj, K. DNA methylation-based biomarkers and the epigenetic clock theory of ageing. Nat. Rev. Genet. 19, 371–384 (2018).

    Article  CAS  PubMed  Google Scholar 

  61. Park, Y., Figueroa, M. E., Rozek, L. S. & Sartor, M. A. MethylSig: a whole genome DNA methylation analysis pipeline. Bioinformatics 30, 2414–2422 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Bailey, T. L. et al. MEME SUITE: tools for motif discovery and searching. Nucleic Acids Res. 37, W202–W208 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Kim, D., Paggi, J. M., Park, C., Bennett, C. & Salzberg, S. L. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat. Biotechnol. 37, 907–915 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Feng, J., Liu, T., Qin, B., Zhang, Y. & Liu, X. S. Identifying ChIP-seq enrichment using MACS. Nat. Protoc. 7, 1728–1740 (2012).

    Article  CAS  PubMed  Google Scholar 

  65. Meng, J. et al. A protocol for RNA methylation differential analysis with MeRIP-Seq data and exomePeak R/Bioconductor package. Methods 69, 274–281 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

The authors would like to thank T. Luo, J. Liu, J. Zhou, P. Du, and G. Luo for discussions and help. We also thank P. Chai and Y. Cheng for assistance in the hypoxia experiment. We thank the National Center for Protein Sciences at Peking University in Beijing, China for assistance with quantification of library size distribution. We thank the State Key Laboratory of Natural and Biomimetic Drugs at Peking University for advice and support in technology. We thank the High Performance Computing Platform of the Center for Life Science for assistance with the analysis. This work was supported by the National Key R&D Program of China (2019YFA0802201 to C.Y., 2017YFA0505202 to J.W., 2019YFA0110902 to C.Y., and 2020YFA0710401 to J.P.) and the National Natural Science Foundation of China (22077006 to J.W., 91940304 to C.Y., 21825701 to C.Y., and 91853107 to J.W.).

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Authors and Affiliations

Authors

Contributions

J.W. and C.Y. conceived the project and designed the experiments; C.Y., J.W., C.L., H.S., K.L., and W.S. wrote the manuscript with the help of J.P.; H.S., Y.Y., and W.S. performed the experiments with the help of F.L., Y.X., and Y.H.; C.L developed the bioinformatics pipeline of GLORI; J.W. and Y.Y. developed the chemical method of GLORI; C.L. and K.L. designed and performed the bioinformatics analysis with the help of C.Y., H.M., B.L., and W.L.; H.S. designed and conducted all sample preparation for next-generation sequencing with the help of Y.X.; W.S. and H.S. further optimized the reaction condition with the help of F.L. and Y.L.; J.W. and C.Y. supervised the project.

Corresponding authors

Correspondence to Chengqi Yi or Jing Wang.

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Competing interests

A patent application has been filed by Peking University for the technology disclosed in this publication.

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Nature Biotechnology thanks Kathy Liu and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

Supplementary Figs 1–15.

Reporting Summary

Supplementary Data 1

GLORI-identified m6A sites in HEK293T cells.

Supplementary Data 2

GLORI-identified m6A sites in METTL3, METTL14, WTAP, and control knockdown cells.

Supplementary Data 3

GLORI-identified m6A sites in STM2457 treated cells.

Supplementary Data 4

GLORI-identified m6A sites in YTHDF2 and control knockdown cells.

Supplementary Data 5

Hypoxia stress-inducible m6A sites.

Supplementary Data 6

Heat shock stress-inducible m6A sites.

Supplementary Data 7

Spike-in model sequences and siRNA sequences.

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Liu, C., Sun, H., Yi, Y. et al. Absolute quantification of single-base m6A methylation in the mammalian transcriptome using GLORI. Nat Biotechnol 41, 355–366 (2023). https://doi.org/10.1038/s41587-022-01487-9

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