title: Crass: identification and reconstruction of CRISPR from unassembled metagenomic data.
abstract: Clustered regularly interspaced short palindromic repeats (CRISPR) constitute a bacterial and archaeal adaptive immune system that protect against bacteriophage (phage). Analysis of CRISPR loci reveals the history of phage infections and provides a direct link between phage and their hosts. All current tools for CRISPR identification have been developed to analyse completed genomes and are not well suited to the analysis of metagenomic data sets, where CRISPR loci are difficult to assemble owing to their repetitive structure and population heterogeneity. Here, we introduce a new algorithm, Crass, which is designed to identify and reconstruct CRISPR loci from raw metagenomic data without the need for assembly or prior knowledge of CRISPR in the data set. CRISPR in assembled data are often fragmented across many contigs/scaffolds and do not fully represent the population heterogeneity of CRISPR loci. Crass identified substantially more CRISPR in metagenomes previously analysed using assembly-based approaches. Using Crass, we were able to detect CRISPR that contained spacers with sequence homology to phage in the system, which would not have been identified using other approaches. The increased sensitivity, specificity and speed of Crass will facilitate comprehensive analysis of CRISPRs in metagenomic data sets, increasing our understanding of phage-host interactions and co-evolution within microbial communities.
authors.affiliation: Australian Centre for Ecogenomics, School of Chemistry and Molecular Biosciences and Advanced Water Management Centre, The University of Queensland, St Lucia, Brisbane, Queensland 4072, Australia.
authors.forename: Connor T
authors.initials: CT
authors.lastname: Skennerton
authors.forename: Michael
authors.initials: M
authors.lastname: Imelfort
authors.forename: Gene W
authors.initials: GW
authors.lastname: Tyson
mesh_terms: D000465:Algorithms; D001435:Bacteriophages / Q000235:genetics; D020745:Genome, Archaeal; D016680:Genome, Bacterial; D055029:Inverted Repeat Sequences; D056186:Metagenomics / Q000379:methods*