Evidence map›Paper›PMID 22266655›Full record

ArticleNucleic acids research2012

Revealing stable processing products from ribosome-associated small RNAs by deep-sequencing data analysis.

Marek Zywicki, Kamilla Bakowska-Zywicka, Norbert Polacek

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
3.0field-weighted citation impact, top 9% 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

36 citing papers in PubMed, 60 citations in OpenAlex.

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  9. Transcriptome-Wide Analysis of Stationary Phase Small ncRNAs inInternational journal of molecular sciences · 2021
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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

3 authors at 2 institutions in 2 countries.

Marek ZywickiInnsbruck Biocenter, Medical University Innsbruck, Division of Genomics and RNomics, Fritz-Pregl-Strasse 3, 6020 Innsbruck, Austria. marek.zywicki@i-med.ac.at
Kamilla Bakowska-Zywicka
Norbert Polacek
Innsbruck Medical University · ATUniversity of Bern · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The exploration of the non-protein-coding RNA (ncRNA) transcriptome is currently focused on profiling of microRNA expression and detection of novel ncRNA transcription units. However, recent studies suggest that RNA processing can be a multi-layer process leading to the generation of ncRNAs of diverse functions from a single primary transcript. Up to date no methodology has been presented to distinguish stable functional RNA species from rapidly degraded side products of nucleases. Thus the correct assessment of widespread RNA processing events is one of the major obstacles in transcriptome research. Here, we present a novel automated computational pipeline, named APART, providing a complete workflow for the reliable detection of RNA processing products from next-generation-sequencing data. The major features include efficient handling of non-unique reads, detection of novel stable ncRNA transcripts and processing products and annotation of known transcripts based on multiple sources of information. To disclose the potential of APART, we have analyzed a cDNA library derived from small ribosome-associated RNAs in Saccharomyces cerevisiae. By employing the APART pipeline, we were able to detect and confirm by independent experimental methods multiple novel stable RNA molecules differentially processed from well known ncRNAs, like rRNAs, tRNAs or snoRNAs, in a stress-dependent manner.

Indexed as

High-Throughput Nucleotide SequencingRNA Processing, Post-TranscriptionalSoftwareGene Expression ProfilingGene LibraryRibosomesRNA, Small UntranslatedRNA StabilitySaccharomyces cerevisiaeSequence Analysis, RNARNA, Small Untranslated

Identifiers

PMID22266655
PMCPMC3351166
OpenAlexW1987067847

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.