Welcome to CRISPRome

CRISPRome

CRISPRome is a large publicly available CRISPR-Cas system database, systematically characterizing CRISPR-Cas elements across bacterial and archaeal genomes.

Database Access

Download & Access ⬇️: Download CRISPRome

Data Collection

We compiled data from multiple sources, including:

CRISPR-Cas System Identification

Using CRISPRCasFinder v2.0.355, we identified and extracted spacers and CRISPR arrays:

Spacer-Target Identification Process

  1. Spacer Deduplication & Alignment
    • Spacers were deduplicated and aligned using Blastn-short to a database of 7,042,467 genomes from RefSeq, GenBank, ICEberg, IMG/VR, and PLSDB.
    • makeblastdb was used to convert genome sequences into searchable databases.
  2. Blastn Alignment & Optimization
    • Blastn was run with optimized parameters (word_size 11, qcov_hsp_perc 95, perc_identity 95, max_hsps 3) to balance speed and accuracy.
    • High-performance computing clusters managed by Slurm were used for large-scale processing.
  3. Filtering & Prioritization
    • Hits were sorted by bitscore, keeping the top 10% for accuracy.
    • Prioritization order: viruses > plasmids = ICE > other sources, reflecting CRISPR-Cas immunity targets.
  4. Removing CRISPR Array Artifacts
    • Alignments overlapping known CRISPR array regions were removed to avoid false positives.
    • Additional CRISPR arrays were identified from NCBI genome annotations to refine filtering.
  5. Detecting Potential CRISPR Arrays
    • Arrays were defined by detecting regularly interspaced protospacers.
    • A threshold of ≥4 protospacers was used to minimize false positives, leading to the exclusion of 16,777 targets.
  6. LCA-Based One-to-One Spacer-Target Assignment
    • TaxonKit lca was used to determine the Lowest Common Ancestor (LCA) of multiple target matches.
    • This ensured each spacer was assigned to a single, biologically relevant target.