CRISpy-Pop: A Web Tool for Designing CRISPR/Cas9-Driven Genetic Modifications in Diverse Populations. Issue 11 (1st November 2020)

• Record Type: Journal Article
• Authors: Stoneman, Hayley R; Wrobel, Russell L; Place, Michael; Graham, Michael; Krause, David J; De Chiara, Matteo; Liti, Gianni; Schacherer, Joseph; Landick, Robert; Gasch, Audrey P; Sato, Trey K; Hittinger, Chris Todd
• Is Part Of: G3. Volume 10:Issue 11(2020)
• Page Start: 4287
• Page End: 4294
• Publication Date: 2020-11-01
• Subjects: CRISPR/Cas9 -- sgRNA -- genome editing -- population genomics -- yeast; Genetics -- Research -- Periodicals; Genomics -- Periodicals; Genetics; Genomics; Genes; Genetics -- Research; Genomics; Electronic journals; Periodical; Periodicals; Fulltext; Internet Resources; Periodicals; 572.8
• DOI: 10.1534/g3.120.401498
• Languages: English
• ISSNs: 2160-1836

Abstract

Abstract: CRISPR/Cas9 is a powerful tool for editing genomes, but design decisions are generally made with respect to a single reference genome. With population genomic data becoming available for an increasing number of model organisms, researchers are interested in manipulating multiple strains and lines. CRISpy-pop is a web application that generates and filters guide RNA sequences for CRISPR/Cas9 genome editing for diverse yeast and bacterial strains. The current implementation designs and predicts the activity of guide RNAs against more than 1000 Saccharomyces cerevisiae genomes, including 167 strains frequently used in bioenergy research. Zymomonas mobilis, an increasingly popular bacterial bioenergy research model, is also supported. CRISpy-pop is available as a web application (https://CRISpy-pop.glbrc.org/ ) with an intuitive graphical user interface. CRISpy-pop also cross-references the human genome to allow users to avoid the selection of guide RNAs with potential biosafety concerns. Additionally, CRISpy-pop predicts the strain coverage of each guide RNA within the supported strain sets, which aids in functional population genetic studies. Finally, we validate how CRISpy-pop can accurately predict the activity of guide RNAs across strains using population genomic data.