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Characterization of CRISPR RNA transcription by exploiting stranded metatranscriptomic data

CRISPR–Cas systems are bacterial adaptive immune systems, each typically composed of a locus of cas genes and a CRISPR array of spacers flanked by repeats. Processed transcripts of CRISPR arrays (crRNAs) play important roles in the interference process mediated by these systems, guiding targeted imm...

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Detalles Bibliográficos
Autores principales: Ye, Yuzhen, Zhang, Quan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4911918/
https://www.ncbi.nlm.nih.gov/pubmed/27190232
http://dx.doi.org/10.1261/rna.055988.116
Descripción
Sumario:CRISPR–Cas systems are bacterial adaptive immune systems, each typically composed of a locus of cas genes and a CRISPR array of spacers flanked by repeats. Processed transcripts of CRISPR arrays (crRNAs) play important roles in the interference process mediated by these systems, guiding targeted immunity. Here we developed computational approaches that allow us to characterize the expression of many CRISPRs in their natural environments, using community RNA-seq (metatranscriptomic) data. By exploiting public human gut metatranscriptomic data sets, we studied the expression of 56 repeat-sequence types of CRISPRs, revealing that most CRISPRs are transcribed in one direction (producing crRNAs). In rarer cases, including a type II system associated with Bacteroides fragilis, CRISPRs are transcribed in both directions. Type III CRISPR–Cas systems were found in the microbiomes, but metatranscriptomic reads were barely found for their CRISPRs. We observed individual-level variation of the crRNA transcription, and an even greater transcription of a CRISPR from the antisense strand than the crRNA strand in one sample. The orientations of CRISPR expression implicated by metatranscriptomic data are largely in agreement with prior predictions for CRISPRs, with exceptions. Our study shows the promise of exploiting community RNA-seq data for investigating the transcription of CRISPR–Cas systems.