CasCollect: targeted assembly of CRISPR-associated operons from high-throughput sequencing data

Journal Article · Thu Sep 03 00:00:00 EDT 2020 · NAR Genomics and Bioinformatics

DOI:https://doi.org/10.1093/nargab/lqaa063· OSTI ID:1657646

Podlevsky, Joshua D.  ^[1]; Hudson, Corey M. ^[2]; Timlin, Jerilyn A. ^[2]; Williams, Kelly P.  ^[3]

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1. Molecular and Microbiology, Sandia National Laboratories, Albuquerque, NM 87185, USA
2. Computational Biology and Biophysics, Sandia National Laboratories, Albuquerque, NM 87185, USA
3. Systems Biology, Sandia National Laboratories, Livermore, CA 94550, USA

Abstract CRISPR arrays and CRISPR-associated (Cas) proteins comprise a widespread adaptive immune system in bacteria and archaea. These systems function as a defense against exogenous parasitic mobile genetic elements that include bacteriophages, plasmids and foreign nucleic acids. With the continuous spread of antibiotic resistance, knowledge of pathogen susceptibility to bacteriophage therapy is becoming more critical. Additionally, gene-editing applications would benefit from the discovery of new cas genes with favorable properties. While next-generation sequencing has produced staggering quantities of data, transitioning from raw sequencing reads to the identification of CRISPR/Cas systems has remained challenging. This is especially true for metagenomic data, which has the highest potential for identifying novel cas genes. We report a comprehensive computational pipeline, CasCollect, for the targeted assembly and annotation of cas genes and CRISPR arrays—even isolated arrays—from raw sequencing reads. Benchmarking our targeted assembly pipeline demonstrates significantly improved timing by almost two orders of magnitude compared with conventional assembly and annotation, while retaining the ability to detect CRISPR arrays and cas genes. CasCollect is a highly versatile pipeline and can be used for targeted assembly of any specialty gene set, reconfigurable for user provided Hidden Markov Models and/or reference nucleotide sequences.

• Sponsoring Organization: USDOE
• Grant/Contract Number: NA-0003525
• OSTI ID: 1657646
• Journal Information: NAR Genomics and Bioinformatics, Journal Name: NAR Genomics and Bioinformatics Vol. 2 Journal Issue: 3; ISSN 2631-9268
• Publisher: Oxford University Press
• Country of Publication: United Kingdom
• Language: English