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

Nature Biotechnology volume 41, pages 355–366 (2023)Cite this article

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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.

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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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Author notes

  1. These authors contributed equally: Cong Liu, Hanxiao Sun, Yunpeng Yi, Weiguo Shen, Kai Li.

Authors and Affiliations

  1. State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing, China

    Cong Liu, Hanxiao Sun, Bo Lu, Haowei Meng, Jinying Peng & Chengqi Yi

  2. State Key Laboratory of Natural and Biomimetic Drugs, Department of Chemical Biology, School of Pharmaceutical Sciences, Peking University, Beijing, China

    Yunpeng Yi, Weiguo Shen, Fei Li, Yongkang Hou & Jing Wang

  3. Shandong Provincial Animal and Poultry Green Health Products Creation Engineering Laboratory, Institute of Poultry Science, Shandong Academy of Agricultural Science, Jinan, China

    Yunpeng Yi

  4. Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China

    Kai Li, Ye Xiao & Yuchen Li

  5. Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China

    Kai Li, Ye Xiao, Yuchen Li & Chengqi Yi

  6. School of Life Sciences, Tsinghua University, Beijing, China

    Wenqing Liu

  7. Tsinghua-Peking Joint Center for Life Sciences, Tsinghua University, Beijing, China

    Wenqing Liu

  8. Department of Chemical Biology and Synthetic and Functional Biomolecules Center, College of Chemistry and Molecular Engineering, Peking University, Beijing, China

    Chengqi Yi

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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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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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