[Artificial intelligence-assisted design, mining, and modification of CRISPR-Cas systems].

作者：Yufeng Mao, Guangyun Chu, Qingling Liang, Ye Liu, Yi Yang, Xiaoping Liao, Meng Wang · 发表于：PubMed · 年份：2025 · DOI：10.13345/j.cjb.240865 · 被引用次数：1 · 研究领域：CRISPR and Genetic Engineering、Machine Learning in Bioinformatics、RNA regulation and disease

With the rapid advancement of synthetic biology, CRISPR-Cas systems have emerged as a powerful tool for gene editing, demonstrating significant potential in various fields, including medicine, agriculture, and industrial biotechnology. This review comprehensively summarizes the significant progress in applying artificial intelligence (AI) technologies to the design, mining, and modification of CRISPR-Cas systems. AI technologies, especially machine learning, have revolutionized sgRNA design by analyzing high-throughput sequencing data, thereby improving the editing efficiency and predicting off-target effects with high accuracy. Furthermore, this paper explores the role of AI in sgRNA design and evaluation, highlighting its contributions to the annotation and mining of CRISPR arrays and Cas proteins, as well as its potential for modifying key proteins involved in gene editing. These advancements have not only improved the efficiency and precision of gene editing but also expanded the horizons of genome engineering, paving the way for intelligent and precise genome editing.