ArticleBriefings in bioinformatics2024
Understanding YTHDF2-mediated mRNA degradation by m6A-BERT-Deg.
Article in Briefings in bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
8 citing papers in PubMed, 7 citations in OpenAlex.
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- Systematic identification of tissue-conserved mbioRxiv : the preprint server for biology · 2026Article
- The Regulatory Role of mCells · 2026Review
- Cross-RNA transferable sequence representation learning for lncRNA m6A site detection via novel deep domain separation networks.Briefings in bioinformatics · 2025Article
- METTL3-mediated mMolecular biology reports · 2025Review
- Targeting YTHDF2 with pH-responsive siRNA nanoparticles suppresses MYC m6A modification and restores antitumor immunity in hepatocellular carcinoma.Journal of nanobiotechnology · 2025Article
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
N6-methyladenosine (m6A) is the most abundant mRNA modification within mammalian cells, holding pivotal significance in the regulation of mRNA stability, translation and splicing. Furthermore, it plays a critical role in the regulation of RNA degradation by primarily recruiting the YTHDF2 reader protein. However, the selective regulation of mRNA decay of the m6A-methylated mRNA through YTHDF2 binding is poorly understood. To improve our understanding, we developed m6A-BERT-Deg, a BERT model adapted for predicting YTHDF2-mediated degradation of m6A-methylated mRNAs. We meticulously assembled a high-quality training dataset by integrating multiple data sources for the HeLa cell line. To overcome the limitation of small training samples, we employed a pre-training-fine-tuning strategy by first performing a self-supervised pre-training of the model on 427 760 unlabeled m6A site sequences. The test results demonstrated the importance of this pre-training strategy in enabling m6A-BERT-Deg to outperform other benchmark models. We further conducted a comprehensive model interpretation and revealed a surprising finding that the presence of co-factors in proximity to m6A sites may disrupt YTHDF2-mediated mRNA degradation, subsequently enhancing mRNA stability. We also extended our analyses to the HEK293 cell line, shedding light on the context-dependent YTHDF2-mediated mRNA degradation.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.