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Refined sgRNA efficacy prediction improves large- and small-scale CRISPR-Cas9 applications
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2018 (English)In: Nucleic Acids Research, ISSN 0305-1048, E-ISSN 1362-4962, Vol. 46, no 3, p. 1375-1385Article in journal (Refereed) Published
Abstract [en]

Genome editing with the CRISPR-Cas9 system has enabled unprecedented efficacy for reverse genetics and gene correction approaches. While off-target effects have been successfully tackled, the effort to eliminate variability in sgRNA efficacies-which affect experimental sensitivity-is in its infancy. To address this issue, studies have analyzed the molecular features of highly active sgRNAs, but independent cross-validation is lacking. Utilizing fluorescent reporter knock-out assays with verification at selected endogenous loci, we experimentally quantified the target efficacies of 430 sgRNAs. Based on this dataset we tested the predictive value of five recently-established prediction algorithms. Our analysis revealed a moderate correlation (r = 0.04 to r = 0.20) between the predicted and measured activity of the sgRNAs, and modest concordance between the different algorithms. We uncovered a strong PAM-distal GC-content-dependent activity, which enabled the exclusion of inactive sgRNAs. By deriving nine additional predictive features we generated a linear model-based discrete system for the efficient selection (r = 0.4) of effective sgRNAs (CRISPRater). We proved our algorithms' efficacy on small and large external datasets, and provide a versatile combined on-and off-target sgRNA scanning platform. Altogether, our study highlights current issues and efforts in sgRNA efficacy prediction, and provides an easily-applicable discrete system for selecting efficient sgRNAs.

Place, publisher, year, edition, pages
2018. Vol. 46, no 3, p. 1375-1385
National Category
Cell and Molecular Biology
Identifiers
URN: urn:nbn:se:umu:diva-145587DOI: 10.1093/nar/gkx1268ISI: 000425294400034PubMedID: 29267886OAI: oai:DiVA.org:umu-145587DiVA, id: diva2:1191774
Available from: 2018-03-20 Created: 2018-03-20 Last updated: 2018-06-09Bibliographically approved

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Charpentier, Emmanuelle M.

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CiteExportLink to record
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Citation style
  • apa
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