Institut de Génétique et Microbiologie

CRISPRs web server


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Data Summary

Genomes analysed CRISPRs found (*)
Archea 150 563(126)
Bacteria 2612 3502(1176)
Total 2762 4065(1302)

*number of convincing CRISPR structures (number of genomes with such CRISPR)

Database status:
Last update : 2014-08-05

Contact:
Christine POURCEL

Welcome to CRISPRs web server. This site acts as a gateway to publicly accessible CRISPRs database and software. It enables the easy detection of CRISPRs in locally-produced data and consultation of CRISPRs present in the database. It also gives information on the presence of CRISPR-associated (cas) genes when they have been annotated as such.
This web site is the product of an original work by Ibtissem Grissa (PhD thesis Paris University) and is presently developed by Christine Drevet.


Please cite :
CRISPRFinder : a web tool to identify clustered regularly interspaced short palindromic repeats. Nucleic Acids Res. 2007 May 31;

The CRISPRdb database and tools to display CRISPRs and to generate dictionaries of spacers and repeats. BMC Bioinformatics. 2007 May 23;8(1):172 ;

CRISPRcompar : a website to compare clustered regularly interspaced short palindromic repeats. Nucleic Acid Res. 2008 Jul 1




General purpose of this site

This site provides tools to assist in the finding of CRISPRs structures in published microbial genomes or in user-submitted sequences. Importantly, this site does not focus on the genetic environment often associated with CRISPR structures, the so-called CAS (CRISPR-associated sequences) genes . The reason for this is that most CRISPR structures are not associated with CAS genes, so that CAS cannot be used as a CRISPR-finder tool. A second important aspect is that we have tried here to provide a tool which would not miss even the smallest CRISPR structures (containing a single spacer) and CRISPR which might be slightly different from canonical structures. Whereas the identification of the larger structures is relatively easy and straightforward, and has been achieved by a variety of methods, the search for the very small CRISPR is much more ambiguous. As a result, a number of very small "questionable" CRISPR are contained in the database. Many of these are not true CRISPRs, and they need to be critically investigated. It is expected that such candidates will for instance be investigated by typing multiple isolates from the same species. Larger alleles if they exist would need to be sequenced, and the CRISPR nature of the locus would then be confirmed or ruled out.

Site description

In order to adress this general goal, a number of tools are available here. One is the CRISPR database itself, in which microbial genomes have been pre-processed in search for CRISPRs structures. This database can be browsed in an intuitive way.

The second tool is the CRISPR finder tool. You can use this page to analyse your own data.

The third utility provides a global overview of CRISPRs present in the database. Lists of known DRs and spacers, and of CRISPRs ordered according to the number of spacers, are provided, with links to detailed information for the corresponding CRISPRs. Sequence alignments of selected DR regions can be produced using CLUSTAL W, together with dendrograms.

The BLAST CRISPR page will be of use to try to validate a questionable CRISPR. From this page, a candidate DR region (or spacer) can be compared to all DRs (or spacers) characterised so far from clear-cut CRISPR structures present in the database.

The FlankAlign link is useful to compare CRISPR flanking sequences, for instance when looking for the homolog of a CRISPR locus in other strains, or when trying to validate a questionable CRISPR, by searching for a leader sequence.

The last resource is the "CRISPRtionary". This is a very helpfull tool to analyse sequence from multiple alleles derived from the same locus. Such data would be produced for instance when investigating the diversity of CRISPR within a species by sequencing the locus in different isolates. This tool can then be used to automatically number spacers, produce a "dictionary", and code the alleles using this dictionary. Sample files are provided to illustrate how this works and what it does ( Pestis Dictionary and