Evidence map›Paper›PMID 22072964›Full record

ArticlePLoS pathogens2011

Sequence-based analysis uncovers an abundance of non-coding RNA in the total transcriptome of Mycobacterium tuberculosis.

Kristine B Arnvig, Iñaki Comas, Nicholas R Thomson, Joanna Houghton, Helena I Boshoff, Nicholas J Croucher, Graham Rose, Timothy T Perkins, Julian Parkhill, Gordon Dougan and 1 more

Open access · goldAbstract read
In one paragraph

Article in PLoS pathogens, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 141 papers.

0numbers the graph read from it
0cells of the map it votes in
141citing papers in PubMed
13.7field-weighted citation impact, top 1% 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

141 citing papers in PubMed, 257 citations in OpenAlex.

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81 more citing papers are in PubMed but not listed here.

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

11 authors at 3 institutions in 2 countries.

Kristine B ArnvigDivision of Mycobacterial Research, MRC National Institute for Medical Research, London, United Kingdom. karnvig@nimr.mrc.ac.uk
Iñaki Comas
Nicholas R Thomson
Joanna Houghton
Helena I Boshoff
Nicholas J Croucher
Graham Rose
Timothy T Perkins
Julian Parkhill
Gordon Dougan
Douglas B Young
Wellcome Sanger Institute · GBMRC London Institute of Medical Sciences · GBNational Institute of Allergy and Infectious Diseases · US

Funding

Intramural NIH HHSMedical Research Council MC_U117581288Medical Research Council U117581288Wellcome Trust
6 · The paper itself

Abstract

RNA sequencing provides a new perspective on the genome of Mycobacterium tuberculosis by revealing an extensive presence of non-coding RNA, including long 5' and 3' untranslated regions, antisense transcripts, and intergenic small RNA (sRNA) molecules. More than a quarter of all sequence reads mapping outside of ribosomal RNA genes represent non-coding RNA, and the density of reads mapping to intergenic regions was more than two-fold higher than that mapping to annotated coding sequences. Selected sRNAs were found at increased abundance in stationary phase cultures and accumulated to remarkably high levels in the lungs of chronically infected mice, indicating a potential contribution to pathogenesis. The ability of tubercle bacilli to adapt to changing environments within the host is critical to their ability to cause disease and to persist during drug treatment; it is likely that novel post-transcriptional regulatory networks will play an important role in these adaptive responses.

Indexed as

TranscriptomeAnimalsBase SequenceGene Expression Regulation, BacterialMiceMice, Inbred C57BLMycobacterium tuberculosisOligonucleotide Array Sequence AnalysisRNA, BacterialRNA, UntranslatedSequence Analysis, RNARNA, BacterialRNA, Untranslated

Identifiers

PMID22072964
PMCPMC3207917
OpenAlexW2150390148

What OpenQuestion holds

Textmetadata
LicenceCC0
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.