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bioRxiv · 10.1101/2025.01.06.603201

CHOPOFF: symbolic alignments enable fast and sensitive CRISPR off-target detection

Labun, K.·Rio, O.·Tjeldnes, H.·Swirski, M.·Komisarczuk, A. Z.·Haapaniemi, E. M.·Valen, E.
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Abstract

CRISPR/Cas systems offer powerful tools for genome editing, but their therapeutic application is hampered by the risk of unintended off-target mutations. Many molecular methods have been established to detect off-target editing, however, their sensitivity depends on first identifying potential sites using in silico methods. However, these in silico prediction methods are challenged by a trade-off between speed and sensitivity, and can fail to comprehensively detect all edited off-target sites. Here, we demonstrate that ignoring bulges has led to missing editing at off-target sites in previous studies and that continuing this practice can lead to inflated claims of fidelity. As a solution, we introduce the concept of symbolic alignments to efficiently identify off-targets without sacrificing sensitivity. We further present specialized data structures that enable rapid, alignment-free probabilistic ranking of guide RNAs based on their predicted off-target burden. Implemented in the tool CHOPOFF, these innovations accommodate mismatches, bulges (insertions/deletions), and incorporate genomic sequence variants for personalized off-target assessment. Benchmarking demonstrates that CHOPOFF significantly outperforms state-of-the-art tools in both prediction accuracy and computational speed. AvailabilityCHOPOFF command line available at https://github.com/JokingHero/CHOPOFF.jl CHOPOFF web server available at https://crisprtools.org/chopoff

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Labun, K., Rio, O., Tjeldnes, H., Swirski, M., Komisarczuk, A. Z., Haapaniemi, E. M., Valen, E.. 2025-01-06. CHOPOFF: symbolic alignments enable fast and sensitive CRISPR off-target detection. https://doi.org/10.1101/2025.01.06.603201

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