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Article Abstract

Designing CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) 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 introduce ALLEGRO, a combinatorial optimization algorithm designed to compose minimal, yet highly effective sgRNA libraries targeting thousands of species at the same time. Leveraging integer linear programming, ALLEGRO identified compact sgRNA sets simultaneously targeting multiple genes of interest for over 2000 species across the fungal kingdom. We experimentally validated sgRNAs designed by ALLEGRO in Kluyveromyces marxianus, Komagataella phaffii, Yarrowia lipolytica, and Saccharomyces cerevisiae, confirming successful genome edits. Additionally, we employed a generalized Cas9-ribonucleoprotein delivery system to apply ALLEGRO's sgRNA libraries to untested fungal genomes, such as Rhodotorula araucariae. Our experimental findings, together with cross-validation, demonstrate that ALLEGRO facilitates efficient CRISPR genome editing, enabling the development of universal sgRNA libraries applicable to entire taxonomic groups.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12362242PMC
http://dx.doi.org/10.1093/nar/gkaf783DOI Listing

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Kingdom-wide CRISPR guide design with ALLEGRO.

Nucleic Acids Res

August 2025

Chemical and Environmental Engineering, University of California, Riverside, CA 92521, United States.

Designing CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) 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 introduce ALLEGRO, a combinatorial optimization algorithm designed to compose minimal, yet highly effective sgRNA libraries targeting thousands of species at the same time.

View Article and Find Full Text PDF