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Discovering CRISPR-Cas system with self-processing pre-crRNA capability by foundation models

Nature Communications. 2025-01; 
Wenhui Li, Xianyue Jiang, Wuke Wang, Liya Hou, Runze Cai, Yongqian Li, Qiuxi Gu, Qinchang Chen, Peixiang Ma, Jin Tang, Menghao Guo, Guohui Chuai, Xingxu Huang, Jun Zhang, Qi Liu
Products/Services Used Details Operation
Synthetic sgRNA and crRNA Service Target cleavage assays were performed in a 30-μL reaction mixture containing 300 ng substrate and 400 ng RNP complex in a final 1x NEB r2.1 buffer (GenScript, target, and crRNA sequences are given in Supplementary Data 13). A Get A Quote

摘要

The discovery of CRISPR-Cas systems has paved the way for advanced gene editing tools. However, traditional Cas discovery methods relying on sequence similarity may miss distant homologs and aren’t suitable for functional recognition. With protein large language models (LLMs) evolving, there is potential for Cas system modeling without extensive training data. Here, we introduce CHOOSER (Cas HOmlog Observing and SElf-processing scReening), an AI framework for alignment-free discovery of CRISPR-Cas systems with selfprocessing pre-crRNA capability using protein foundation models. By using CHOOSER, we identify 11 Casλ homologs, nearly doubling the known catalog. Notably, one homolog, EphcCasλ, is expe... More

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