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N6-methyladenosine (m6A) is the most abundant mRNA modification withinmammalian cells, holding pivotal significance in the regulation of mRNAstability, translation, and splicing. Furthermore, it plays a critical role inthe regulation of RNA degradation by primarily recruiting the YTHDF2 readerprotein. However, the selective regulation of mRNA decay of the m6A-methylatedmRNA through YTHDF2 binding is poorly understood. To improve our understanding,we developed m6A-BERT-Deg, a BERT model adapted for predicting YTHDF2-mediateddegradation of m6A-methylated mRNAs. We meticulously assembled a high-qualitytraining dataset by integrating multiple data sources for the HeLa cell line.To overcome the limitation of small training samples, we employed apre-training-fine-tuning strategy by first performing a self-supervisedpre-training of the model on 427,760 unlabeled m6A site sequences. The testresults demonstrated the importance of this pre-training strategy in enablingm6A-BERT-Deg to outperform other benchmark models. We further conducted acomprehensive model interpretation and revealed a surprising finding that thepresence of co-factors in proximity to m6A sites may disrupt YTHDF2-mediatedmRNA degradation, subsequently enhancing mRNA stability. We also extended ouranalyses to the HEK293 cell line, shedding light on the context-dependentYTHDF2-mediated mRNA degradation.

Understanding YTHDF2-mediated mRNA Degradation By m6A-BERT-Deg