Evidence map›Paper›PMID 23577827›Full record

ArticleBMC genomics2013

Conserved expression of natural antisense transcripts in mammals.

Maurice H T Ling, Yuguang Ban, Hongxiu Wen, San Ming Wang, Steven X Ge

Abstract readValidation Study
In one paragraph

Article in BMC genomics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing 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

32 citing papers in PubMed.

  1. Review
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  6. The Functional Meaning of 5'UTR in Protein-Coding Genes.International journal of molecular sciences · 2023
    Review
  7. Article
  8. Article
  9. Non-coding antisense transcripts: fine regulation of gene expression in cancer.Computational and structural biotechnology journal · 2022
    Review
  10. Article
  11. Article
  12. Article
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  16. Review
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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.

Maurice H T LingDepartment of Mathematics and Statistics, South Dakota State University, Brookings, SD 57007, USA.
Yuguang Ban
Hongxiu Wen
San Ming Wang
Steven X Ge

Funding

Large-scale expression analysis of natural antisense transcriptsR01GM083226 · NIGMS · SOUTH DAKOTA STATE UNIVERSITY · PI GE, XIJIN · 2009 to 2012
$837k
NIGMS NIH HHS GM083226NIGMS NIH HHS R01 GM083226
6 · The paper itself

Abstract

backgroundRecent studies had found thousands of natural antisense transcripts originating from the same genomic loci of protein coding genes but from the opposite strand. It is unclear whether the majority of antisense transcripts are functional or merely transcriptional noise.

resultsUsing the Affymetrix Exon array with a modified cDNA synthesis protocol that enables genome-wide detection of antisense transcription, we conducted large-scale expression analysis of antisense transcripts in nine corresponding tissues from human, mouse and rat. We detected thousands of antisense transcripts, some of which show tissue-specific expression that could be subjected to further study for their potential function in the corresponding tissues/organs. The expression patterns of many antisense transcripts are conserved across species, suggesting selective pressure on these transcripts. When compared to protein-coding genes, antisense transcripts show a lesser degree of expression conservation. We also found a positive correlation between the sense and antisense expression across tissues.

conclusionOur results suggest that natural antisense transcripts are subjected to selective pressure but to a lesser degree compared to sense transcripts in mammals.

Indexed as

Transcription, GeneticAnimalsDNA, ComplementaryExonsGene Expression ProfilingHumansMiceOligonucleotide Array Sequence AnalysisOrgan SpecificityRatsReverse Transcriptase Polymerase Chain ReactionRNA, AntisenseDNA, ComplementaryRNA, Antisense

Identifiers

PMID23577827
PMCPMC3635984

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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.