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bioRxiv · 10.1101/2024.12.26.630389

MethylQUEEN: A Methylation Encoded DNA Foundation Model

Li, M.·Gu, R.·Fan, S.·Fan, Y.·He, B.·Yang, J.·Chen, Y.·Xin, M.·Wen, H.·Yi, C.
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Abstract

DNA 5-methylcytosine (5mC) modification plays a pivotal role in many biological processes, yet 5mC information and pattern hidden behind remains to be explored. Here, we develop Methylation Language Model based on Quintuple Bidirectional Transformer (MethylQUEEN), a novel pre-trained DNA methylation foundation model capable of sensing methylation states and covering the genome-wide methylation landscape. Through tailored methylation-prone pre-training, MethylQUEEN effectively captured epigenetics information hidden within the DNA sequences: it accurately traces DNAs tissue-of-origin, and successfully recovers the expression profile through methylation states. Integrative analysis on MethylQUEENs attention scores also enables us to reveal the unique methylation status of a tissue for precise disease detection, and identifying key regulatory 5mC sites for disease intervention. As a result, MethylQUEEN signifies a new paradigm in methylation analysis for various biological problems. Besides, our study demonstrates the effectiveness of directly integrating methylation information into pre-training, offering new perspectives and methodologies for a range of methylation-related biological processes. It serves as an initial exploration for the development of more comprehensive epigenomic models.

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Li, M., Gu, R., Fan, S., Fan, Y., He, B., Yang, J., Chen, Y., Xin, M., Wen, H., Yi, C.. 2024-12-26. MethylQUEEN: A Methylation Encoded DNA Foundation Model. https://doi.org/10.1101/2024.12.26.630389

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