Dion MB et al. (2018), CRISPRStudio: A User-Friendly Software for Rapi...

ECB-ART-46729

Viruses 2018 Nov 01;1011:. doi: 10.3390/v10110602.

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

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

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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.

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Genes referenced: cse1l LOC115925415 LOC583082

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	Figure 1. CRISPRStudio workflow scheme. (A) Spacer sequences are first extracted from the CRISPRDetect gff output file, (B) then aligned with fasta36, and (C) clustered, based on the mismatch cut-off. (D) Each cluster is assigned a two-color code and an SVG (scalable vector graphics) file is produced for visualization.
	Figure 2. Comparison of color-coding systems of CRISPRviz and CRISPRStudio. Each row represents the same array with the exception of the sixth spacer (marked with an arrow) for which we changed the first nucleotide (A to G, C, T or N). CRISPRviz displays spacers with the same color only when they have identical sequences. This results in spacers with only one mismatch having different colors depending on the nucleotide change. CRISPRStudio offers a customizable number of mismatches. When the score cut-off is set to zero, only spacer pairs without mismatch will have the same color. By default, the score cut-off is set to 2, which allows for mutations and/or sequencing errors, without changing the spacers colors.
	Figure 3. Array clustering method implemented in CRISPRStudio. A set of 74 Salmonella strains are displayed here in clusters of similar arrays. CRISPR 1 and CRISPR 2 are shown from right to left. The color-coding easily distinguishes the three major groups following the clustering, which correspond to different serotypes.
	Figure 4. Versatility offered by CRISPRStudio. Vector graphics output allows for easy manual editing. Here, four Salmonella strains are displayed with their two CRISPR loci split in two columns. White spaces were added to the original figure (A) so that homologous spacers are vertically aligned (B).
	Figure 5. CRISPR loci misnumbering. CRISPR loci are given inconsistent numbers by CRISPRDetect in the cases where sequences from two samples do not contain all of the same CRISPR loci.
	Figure 6. Optional graying out to easily mark similar and unique spacers across and within samples. (A) The CRISPR 1 loci of seven S. thermophilus strains were used to illustrate this feature. Two options are available: (B) Unique spacers present only once in the figure are grayed out to highlight similar spacers across the dataset or (C) similar spacers are grayed out to highlight unique colored spacers. Grayed out spacers all bear the same symbol consisting of a white square with a light gray diamond.

References [+] :

Almeida, Molecular characterization of Salmonella Typhimurium isolated in Brazil by CRISPR-MVLST. 2017, Pubmed