CCTop: An Intuitive, Flexible and Reliable CRISPR/Cas9 Target Prediction Tool

PLoS One. 2015 Apr 24;10(4):e0124633. doi: 10.1371/journal.pone.0124633. eCollection 2015.

Abstract

Engineering of the CRISPR/Cas9 system has opened a plethora of new opportunities for site-directed mutagenesis and targeted genome modification. Fundamental to this is a stretch of twenty nucleotides at the 5' end of a guide RNA that provides specificity to the bound Cas9 endonuclease. Since a sequence of twenty nucleotides can occur multiple times in a given genome and some mismatches seem to be accepted by the CRISPR/Cas9 complex, an efficient and reliable in silico selection and evaluation of the targeting site is key prerequisite for the experimental success. Here we present the CRISPR/Cas9 target online predictor (CCTop, http://crispr.cos.uni-heidelberg.de) to overcome limitations of already available tools. CCTop provides an intuitive user interface with reasonable default parameters that can easily be tuned by the user. From a given query sequence, CCTop identifies and ranks all candidate sgRNA target sites according to their off-target quality and displays full documentation. CCTop was experimentally validated for gene inactivation, non-homologous end-joining as well as homology directed repair. Thus, CCTop provides the bench biologist with a tool for the rapid and efficient identification of high quality target sites.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Binding Sites
  • CRISPR-Cas Systems*
  • Computational Biology / methods*
  • Gene Targeting / methods
  • Genomics / methods
  • Humans
  • Internet*
  • RNA, Messenger / chemistry
  • RNA, Messenger / genetics
  • Reproducibility of Results
  • Software*
  • User-Computer Interface
  • Web Browser

Substances

  • RNA, Messenger

Grants and funding

TT received a Postdoctoral Fellowship of the cluster of excellence CellNetworks. The project was supported by the European Research Council (JW: ManISteC) and the German Research Foundation (DFG: SFB873, JW). The authors acknowledge the financial support of the Deutsche Forschungsgemeinschaft and Ruprecht-Karls-Universität Heidelberg within the funding programme Open Access Publishing. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.