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Kingdom-Wide CRISPR Guide Design with ALLEGRO

Mohseni, A.; Ghorbani Nia, R.; Tafrishi, A.; Liu, X.-Z.; Stajich, J. E.; Wheeldon, I.; Lonardi, S.

2025-02-17 bioinformatics
10.1101/2025.02.13.638206 bioRxiv
Show abstract

Designing CRISPR single guide RNA (sgRNA) libraries targeting entire kingdoms of life will significantly advance genetic research in diverse and underexplored taxa. Current sgRNA design tools are often species-specific and fail to scale to large, phylogenetically diverse datasets, limiting their applicability to comparative genomics, evolutionary studies, and biotechnology. Here, we present ALLEGRO, a combinatorial optimization algorithm able to design minimal, yet highly effective sgRNA libraries targeting thousands of species. Leveraging integer linear programming, ALLEGRO identified compact sgRNA sets simultaneously targeting several genes of interest for over 2,000 species across the fungal kingdom. We experimentally validated the sgRNAs designed by ALLEGRO in Kluyveromyces marxianus, Komagataella phaffii, and Yarrowia lipolytica. In addition, we adopted a generalized Cas9-Ribonucleoprotein delivery system coupled with protoplast transformation to extend ALLEGROs sgRNA libraries to other untested fungal genomes, such as Rhodotorula araucariae. Our experimental results, along with cross-validation, show that ALLEGRO enables efficient CRISPR genome editing, supporting the development of universal sgRNA libraries applicable to entire taxonomic groups.

Published in Nucleic Acids Research (predicted rank #1) · training set

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