Mitigating the Off-target Effects in CRISPR/Cas9-mediated Genetic Editing with Bioinformatic Technologies

Abstract

The biological and clinical fields have recognized the CRISPR/Cas9 (clustered regularly interspaced short palindromic repeat/CRISPR associated protein 9) system as a precise and efficient tool for editing the genome. Despite its merits, the system poses crucial challenges, notably the off-target effects which could lead to unintended mutations - a substantial impediment for clinical applications that may potentially compromise the validity of research and the safety of therapeutic applications. Bioinformatics plays a pivotal role in mitigating this risk. Utilizing more refined bioinformatic tools and algorithms, researchers can reduce off-target mutations remarkably. These instruments, powered by machine learning and computational modelling, are able to predict off-target effects and provide aid for the design of more efficient sgRNA. Despite these advancements, it remains crucial to continue to focus on the improvement and assessment of such bioinformatics strategies. This review aims to holistically explore the mechanism and applications of CRISPR/Cas9 genome editing, its off-target effects, and the consequent impacts, along with the potential of bioinformatics techniques to identify off-target risks and facilitate sgRNA design. This review will also incorporate a clinical trial on HIV-1 treatment as a case study to highlight the potential of bioinformatics in devising solutions to mitigate the potential off-target effects of CRISPR/Cas9-mediated genetic editing.