Click here to close Hello! We notice that you are using Internet Explorer, which is not supported by Echinobase and may cause the site to display incorrectly. We suggest using a current version of Chrome, FireFox, or Safari.
Echinobase
ECB-ART-46729
Viruses 2018 Nov 01;1011:. doi: 10.3390/v10110602.
Show Gene links Show Anatomy links

CRISPRStudio: A User-Friendly Software for Rapid CRISPR Array Visualization.

Dion MB , Labrie SJ , Shah SA , Moineau S .


Abstract
The CRISPR-Cas system biologically serves as an adaptive defense mechanism against phages. However, there is growing interest in exploiting the hypervariable nature of the CRISPR locus, often of viral origin, for microbial typing and tracking. Moreover, the spacer content of any given strain provides a phage resistance profile. Large-scale CRISPR typing studies require an efficient method for showcasing CRISPR array similarities across multiple isolates. Historically, CRISPR arrays found in microbes have been represented by colored shapes based on nucleotide sequence identity and, while this approach is now routinely used, only scarce computational resources are available to automate the process, making it very time-consuming for large datasets. To alleviate this tedious task, we introduce CRISPRStudio, a command-line tool developed to accelerate CRISPR analysis and standardize the preparation of CRISPR array figures. It first compares nucleotide spacer sequences present in a dataset and then clusters them based on sequence similarity to assign a meaningful representative color. CRISPRStudio offers versatility to suit different biological contexts by including options such as automatic sorting of CRISPR loci and highlighting of shared spacers, while remaining fast and user-friendly.

PubMed ID: 30388811
PMC ID: PMC6267562
Article link: Viruses
Grant support: [+]

Genes referenced: cse1l LOC115925415 LOC583082


Article Images: [+] show captions
References [+] :
Almeida, Molecular characterization of Salmonella Typhimurium isolated in Brazil by CRISPR-MVLST. 2017, Pubmed