Dataset Information

Increasing the specificity of CRISPR systems with engineered RNA secondary structures.

ABSTRACT: CRISPR (clustered regularly interspaced short palindromic repeat) systems have been broadly adopted for basic science, biotechnology, and gene and cell therapy. In some cases, these bacterial nucleases have demonstrated off-target activity. This creates a potential hazard for therapeutic applications and could confound results in biological research. Therefore, improving the precision of these nucleases is of broad interest. Here we show that engineering a hairpin secondary structure onto the spacer region of single guide RNAs (hp-sgRNAs) can increase specificity by several orders of magnitude when combined with various CRISPR effectors. We first demonstrate that designed hp-sgRNAs can tune the activity of a transactivator based on Cas9 from Streptococcus pyogenes (SpCas9). We then show that hp-sgRNAs increase the specificity of gene editing using five different Cas9 or Cas12a variants. Our results demonstrate that RNA secondary structure is a fundamental parameter that can tune the activity of diverse CRISPR systems.

SUBMITTER: Kocak DD

PROVIDER: S-EPMC6626619 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Increasing the specificity of CRISPR systems with engineered RNA secondary structures.

Kocak D Dewran DD Josephs Eric A EA Bhandarkar Vidit V Adkar Shaunak S SS Kwon Jennifer B JB Gersbach Charles A CA

Nature biotechnology 20190415 6

CRISPR (clustered regularly interspaced short palindromic repeat) systems have been broadly adopted for basic science, biotechnology, and gene and cell therapy. In some cases, these bacterial nucleases have demonstrated off-target activity. This creates a potential hazard for therapeutic applications and could confound results in biological research. Therefore, improving the precision of these nucleases is of broad interest. Here we show that engineering a hairpin secondary structure onto the sp ...[more]

PMID: 30988504

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Project description:BackgroundAccurate structure prediction methods play an important role for the understanding of RNA function. Energy-based, pseudoknot-free secondary structure prediction is one of the most widely used and versatile approaches, and improved methods for this task have received much attention over the past five years. Despite the impressive progress that as been achieved in this area, existing evaluations of the prediction accuracy achieved by various algorithms do not provide a comprehensive, statistically sound assessment. Furthermore, while there is increasing evidence that no prediction algorithm consistently outperforms all others, no work has been done to exploit the complementary strengths of multiple approaches.ResultsIn this work, we present two contributions to the area of RNA secondary structure prediction. Firstly, we use state-of-the-art, resampling-based statistical methods together with a previously published and increasingly widely used dataset of high-quality RNA structures to conduct a comprehensive evaluation of existing RNA secondary structure prediction procedures. The results from this evaluation clarify the performance relationship between ten well-known existing energy-based pseudoknot-free RNA secondary structure prediction methods and clearly demonstrate the progress that has been achieved in recent years. Secondly, we introduce AveRNA, a generic and powerful method for combining a set of existing secondary structure prediction procedures into an ensemble-based method that achieves significantly higher prediction accuracies than obtained from any of its component procedures.ConclusionsOur new, ensemble-based method, AveRNA, improves the state of the art for energy-based, pseudoknot-free RNA secondary structure prediction by exploiting the complementary strengths of multiple existing prediction procedures, as demonstrated using a state-of-the-art statistical resampling approach. In addition, AveRNA allows an intuitive and effective control of the trade-off between false negative and false positive base pair predictions. Finally, AveRNA can make use of arbitrary sets of secondary structure prediction procedures and can therefore be used to leverage improvements in prediction accuracy offered by algorithms and energy models developed in the future. Our data, MATLAB software and a web-based version of AveRNA are publicly available at http://www.cs.ubc.ca/labs/beta/Software/AveRNA.

Dataset Information

Increasing the specificity of CRISPR systems with engineered RNA secondary structures.

Publications

Increasing the specificity of CRISPR systems with engineered RNA secondary structures.

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