Dandan Huang

Hainan Institute of Biotechnology, Haikou, 570206, Hainan, China
Author    Correspondence author
Computational Molecular Biology, 2025, Vol. 15, No. 5   
Received: 07 Aug., 2025    Accepted: 18 Sep., 2025    Published: 09 Oct., 2025

This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

CRISPR-Cas systems have revolutionized plant genome editing by enabling precise, efficient, and targeted modifications, with tomato (Solanum lycopersicum) serving as a key model for translational applications in crop improvement. This study explored the application of CRISPR design algorithms in the selection and validation of guide RNAs (gRNAs) for optimizing tomato genome editing. The mechanisms of action of the CRISPR-Cas9 and Cas12a systems were analyzed, and major design tools such as CHOPCHOP, CRISPOR, and CRISPR-P were compared. The performance of the algorithms was evaluated in terms of targeting efficiency and specificity. Using the SlMLO1 gene as a functional target, this study conducted a case study using CRISPR-P and CRISPR-GE platforms to design and evaluate gRNAs, achieving effective gene editing and enhancing tomato resistance to powdery mildew. This study highlights the challenges faced by algorithms in predicting off-target effects and adapting to the complex tomato genome, while also emphasizing the potential of integrating machine learning and tomato-specific databases to improve design accuracy. This research underscores the increasing synergy between computational biology and experimental biology, paving the way for the development of next-generation AI-assisted genome editing tools suitable for crops.

CRISPR-Cas9; Guide RNA design; Tomato genome editing; Algorithm optimization; SlMLO1 gene