SWOffinder: Efficient and versatile search of CRISPR off-targets with bulges by Smith-Waterman alignment

Ofir Yaish, Amichai Malle, Eliav Cohen, Yaron Orenstein

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

CRISPR/Cas9 technology is revolutionizing the field of gene editing. While this technology enables the targeting of any gene, it may also target unplanned loci, termed off-target sites (OTS), which are a few mismatches, insertions, and deletions from the target. While existing methods for finding OTS up to a given mismatch threshold are efficient, other methods considering insertions and deletions are limited by long runtimes, incomplete OTS lists, and partial support of versatile thresholds. Here, we developed SWOffinder, an efficient method based on Smith-Waterman alignment to find all OTS up to some edit distance. We implemented an original trace-back approach to find OTS under versatile criteria, such as separate limits on the number of insertions, deletions, and mismatches. Compared to state-of-the-art methods, only SWOffinder finds all OTS in the genome in just a few minutes. SWOffinder enables accurate and efficient genomic search of OTS, which will lead to safer gene editing.

Original languageEnglish
Article number108557
JournaliScience
Volume27
Issue number1
DOIs
StatePublished - 19 Jan 2024

Bibliographical note

Publisher Copyright:
© 2023 The Author(s)

Funding

This study was partially supported by the Israel Science Foundation (grant no. 358/21 ). We gratefully acknowledge the support of the CRISPR-IL consortium for supporting our research and for giving access to the AWS platform used for part of this work. Ofir acknowledges the support of the Azrieli PhD fellowship , the Kretiman PhD fellowship at Ben-Gurion University , Nehemia Levtzion Ph.D. fellowship from the Israeli Council for Higher Education , and the cloud-compute credit by the Planning and Budgeting Committee through IUCC.

FundersFunder number
Israel Science Foundation358/21
Council for Higher Education

    Keywords

    • Algorithms
    • Bioinformatics
    • Biological constraints
    • Techniques in genetics

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