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Exon-intron boundary inhibits m6A deposition, enabling m6A distribution hallmark, longer mRNA half-life and flexible protein coding

Author

Listed:
  • Zhiyuan Luo

    (The Jackson Laboratory)

  • Qilian Ma

    (Soochow University)

  • Shan Sun

    (Soochow University)

  • Ningning Li

    (Soochow University)

  • Hongfeng Wang

    (Soochow University)

  • Zheng Ying

    (Soochow University)

  • Shengdong Ke

    (The Jackson Laboratory)

Abstract

Regional bias of N6-methyladenosine (m6A) mRNA modification avoiding splice site region, calls for an open hypothesis whether exon-intron boundary could affect m6A deposition. By deep learning modeling, we find that exon-intron boundary represses a proportion (12% to 34%) of m6A deposition at adjacent exons (~100 nt to splice site). Experiments validate that m6A signal increases once the host gene does not undergo pre-mRNA splicing to produce the same mRNA. Inhibited m6A sites have higher m6A enhancers and lower m6A silencers locally and show high heterogeneity at different exons genome-widely, with only a small proportion (12% to 15%) of exons showing strong inhibition, enabling more stable mRNAs and flexible protein coding. m6A is majorly responsible for why mRNAs with more exons be more stable. Exon junction complex (EJC) only partially contributes to this exon-intron boundary m6A inhibition in some short internal exons, highlighting additional factors yet to be identified.

Suggested Citation

  • Zhiyuan Luo & Qilian Ma & Shan Sun & Ningning Li & Hongfeng Wang & Zheng Ying & Shengdong Ke, 2023. "Exon-intron boundary inhibits m6A deposition, enabling m6A distribution hallmark, longer mRNA half-life and flexible protein coding," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-39897-1
    DOI: 10.1038/s41467-023-39897-1
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    References listed on IDEAS

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    1. Xin Yang & Robinson Triboulet & Qi Liu & Erdem Sendinc & Richard I. Gregory, 2022. "Exon junction complex shapes the m6A epitranscriptome," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
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    3. Zhiyuan Luo & Jiacheng Zhang & Jingyi Fei & Shengdong Ke, 2022. "Deep learning modeling m6A deposition reveals the importance of downstream cis-element sequences," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
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