Systematic prediction of genes functionally linked to CRISPR-Cas systems by gene neighborhood analysis

Sergey A. Shmakov, Kira S. Makarova, Yuri I. Wolf, Konstantin V. Severinov, Eugene V. Koonin

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    76 Citations (Scopus)

    Abstract

    The CRISPR-Cas systems of bacterial and archaeal adaptive immunity consist of direct repeat arrays separated by unique spacers and multiple CRISPR-associated (cas) genes encoding proteins that mediate all stages of the CRISPR response. In addition to the relatively small set of core cas genes that are typically present in all CRISPR-Cas systems of a given (sub)type and are essential for the defense function, numerous genes occur in CRISPR-cas loci only sporadically. Some of these have been shown to perform various ancillary roles in CRISPR response, but the functional relevance of most remains unknown. We developed a computational strategy for systematically detecting genes that are likely to be functionally linked to CRISPR-Cas. The approach is based on a “CRISPRicity” metric that measures the strength of CRISPR association for all protein-coding genes from sequenced bacterial and archaeal genomes. Uncharacterized genes with CRISPRicity values comparable to those of cas genes are considered candidate CRISPR-linked genes. We describe additional criteria to predict functionally relevance for genes in the candidate set and identify 79 genes as strong candidates for functional association with CRISPR-Cas systems. A substantial majority of these CRISPR-linked genes reside in type III CRISPR-cas loci, which implies exceptional functional versatility of type III systems. Numerous candidate CRISPR-linked genes encode integral membrane proteins suggestive of tight membrane association of CRISPR-Cas systems, whereas many others encode proteins implicated in various signal transduction pathways. These predictions provide ample material for improving annotation of CRISPR-cas loci and experimental characterization of previously unsuspected aspects of CRISPR-Cas system functionality.

    Original languageEnglish
    Pages (from-to)E5307-E5316
    JournalProceedings of the National Academy of Sciences of the United States of America
    Volume115
    Issue number23
    DOIs
    Publication statusPublished - 5 Jun 2018

    Keywords

    • Computational genomics
    • CRISPR-Cas
    • Gene neighborhoods
    • Membrane proteins
    • Signaling

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