Computational approaches for effective CRISPR guide RNA design and evaluation

The Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)/ CRISPR-associated (Cas) system has emerged as the main technology for gene editing. Successful editing by CRISPR requires an appropriate Cas protein and guide RNA. However, low cleavage efficiency and off-target effects hamper the development and application of CRISPR/Cas systems. To predict cleavage efficiency and specificity, numerous computational approaches have been developed for scoring guide RNAs. Most scores are empirical or trained by experimental datasets, and scores are implemented using various computational methods. Herein, we discuss these approaches, focusing mainly on the features or computational methods they utilise. Furthermore, we summarise these tools and give some suggestions for their usage. We also recommend three versatile web-based tools with user-friendly interfaces and preferable functions. The review provides a comprehensive and up-to-date overview of computational approaches for guide RNA design that could help users to select the optimal tools for their research.