Prediction and validation of native and engineered cas9 guide sequences

Alexandra E. Briner, Emily D. Henriksen, Rodolphe Barrangou

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Cas9-based technologies rely on native elements of Type II CRISPR–Cas bacterial immune systems, including the trans-activating CRISPR RNA (tracrRNA), CRISPR RNA (crRNA), Cas9 protein, and protospacer-adjacent motif (PAM). The tracrRNA and crRNA form an RNA duplex that guides the Cas9 endonuclease to complementary nucleic acid sequences. Mechanistically, Cas9 initiates interactions by binding to the target PAM sequence and interrogating the target DNA in a 3′-to-5′ manner. Complementarity between the guide RNA and the target DNA is key. In natural systems, precise cleavage occurs when the target DNA sequence contains a PAM flanking a sequence homologous to the crRNA spacer sequence. Currently, the majority of commercial Cas9-based genome-editing tools are derived from the Type II CRISPR–Cas system of Streptococcus pyogenes. However, a diverse set of Type II CRISPR–Cas systems exist in nature that are potentially valuable for genome engineering applications. Exploitation of these systems requires prediction and validation of both native and engineered dual and single guide RNAs to drive Cas9 functionality. Here, we discuss how to identify the elements of these immune systems to develop next-generation Cas9-based genome-editing tools. We first discuss how to predict tracrRNA sequences and suggest a method for designing single guide RNAs containing only critical structural modules. We then outline how to predict the PAM sequence, which is crucial for determining potential targets for Cas9. Finally, validation of the system elements through transcriptome analysis and interference assays is essential for developing next-generation Cas9-based genome-editing tools.

Original languageEnglish (US)
Pages (from-to)628-634
Number of pages7
JournalCold Spring Harbor Protocols
Volume2016
Issue number7
DOIs
StatePublished - Jul 2016

All Science Journal Classification (ASJC) codes

  • Biochemistry, Genetics and Molecular Biology(all)

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