Evidence map›Paper›PMID 18653530›Full record

ArticleNucleic acids research2008

Trans-natural antisense transcripts including noncoding RNAs in 10 species: implications for expression regulation.

Jiong-Tang Li, Yong Zhang, Lei Kong, Qing-Rong Liu, Liping Wei

Abstract read
In one paragraph

Article in Nucleic acids research, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
–field-weighted citation impact
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

30 citing papers in PubMed.

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  14. Development of genodynamic metrics for exploring the biophysics of DNA polymorphisms.Journal of computational biology and bioinformatics research · 2014
    Article
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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

5 authors.

Jiong-Tang LiCenter for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering, College of Life Sciences, Peking University, Beijing, 100871, PR China.
Yong Zhang
Lei Kong
Qing-Rong Liu
Liping Wei

Funding

Intramural NIH HHS
6 · The paper itself

Abstract

Natural antisense transcripts are at least partially complementary to their sense transcripts. Cis-Sense/Antisense pairs (cis-SAs) have been extensively characterized and known to play diverse regulatory roles, whereas trans-Sense/Antisense pairs (trans-SAs) in animals are poorly studied. We identified long trans-SAs in human and nine other animals, using ESTs to increase coverage significantly over previous studies. The percentage of transcriptional units (TUs) involved in trans-SAs among all TUs was as high as 4.13%. Particularly 2896 human TUs (or 2.89% of all human TUs) were involved in 3327 trans-SAs. Sequence complementarities over multiple segments with predicted RNA hybridization indicated that some trans-SAs might have sophisticated RNA-RNA pairing patterns. One-fourth of human trans-SAs involved noncoding TUs, suggesting that many noncoding RNAs may function by a trans-acting antisense mechanism. TUs in trans-SAs were statistically significantly enriched in nucleic acid binding, ion/protein binding and transport and signal transduction functions and pathways; a significant number of human trans-SAs showed concordant or reciprocal expression pattern; a significant number of human trans-SAs were conserved in mouse. This evidence suggests important regulatory functions of trans-SAs. In 30 cases, trans-SAs were related to cis-SAs through paralogues, suggesting a possible mechanism for the origin of trans-SAs. All trans-SAs are available at http://trans.cbi.pku.edu.cn/.

Indexed as

Gene Expression RegulationAnimalsBase PairingBase SequenceCarrier ProteinsCattleComputational BiologyConserved SequenceDogsEvolution, MolecularGene DuplicationHumansMiceMolecular Sequence DataRatsRNA, AntisenseCarrier ProteinsRNA, AntisenseRNA, Untranslated

Identifiers

PMID18653530
PMCPMC2528163

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Registered trials

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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.