CRISpy-Pop: A Web Tool for Designing CRISPR/Cas9-Driven Genetic Modifications in Diverse Populations

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. C...

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Bibliographic Details
Published in:G3 : genes - genomes - genetics 2020-09, Vol.10 (10)
Main 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
Format: Article
Language:English
Subjects:
BASIC BIOLOGICAL SCIENCES
CRISPR/Cas9
genome editing
population genomics
sgRNA
yeast
Online Access:Get full text
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Summary: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 sgRNAs 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. Lastly, we validate how CRISpy-pop can accurately predict the activity of guide RNAs across strains using population genomic data.
ISSN:2160-1836
2160-1836