Evidence map›Paper›PMID 27190232›Full record

ArticleRNA (New York, N.Y.)2016

Characterization of CRISPR RNA transcription by exploiting stranded metatranscriptomic data.

Yuzhen Ye, Quan Zhang

Open access · bronzeAbstract read
In one paragraph

Article in RNA (New York, N.Y.), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.9field-weighted citation impact, top 24% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 11 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Yuzhen YeSchool of Informatics and Computing, Indiana University, Bloomington, Indiana 47405, USA.
Quan ZhangSchool of Informatics and Computing, Indiana University, Bloomington, Indiana 47405, USA.
Indiana University Bloomington · US

Funding

Graph-centric approaches to metatranscriptomic and metaproteomic data analysisR01AI108888 · NIAID · TRUSTEES OF INDIANA UNIVERSITY · PI YE, YUZHEN · 2014 to 2017
$1.4M
NIAID NIH HHS R01 AI108888
6 · The paper itself

Abstract

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.

Indexed as

Clustered Regularly Interspaced Short Palindromic RepeatsTranscription, GeneticTranscriptomeGene Expression ProfilingRNARNACRISPR–Cas systemsCRISPR RNA (crRNA)metatranscriptomics

Identifiers

PMID27190232
PMCPMC4911918
OpenAlexW2403810095

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.