基于人工智能的CRISPR-Cas系统的设计、挖掘与改造

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

摘要:

随着合成生物学的兴起，CRISPR-Cas系统作为基因编辑的核心工具在医药、农业和工业生物技术等领域展现了巨大潜力。本文综述了人工智能(artificial intelligence, AI)技术在CRISPR-Cas系统设计、挖掘与改造中的应用进展。AI技术，特别是机器学习，通过分析高通量测序数据，优化sgRNA设计、提升编辑效率、预测脱靶效应。本文讨论了AI在单链引导RNA (single guide RNA, sgRNA)设计与评估中的应用，并对基于机器学习的CRISPR阵列、Cas蛋白的注释与挖掘，以及AI在CRISPR相关的基因编辑关键蛋白改造中的潜力也进行了重点探讨。这些研究不仅提高了基因编辑的效率和精确性，还为基因组工程开辟了新的可能性，也为实现智能化和精准化的基因组编辑奠定了基础。

Abstract:

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.