Evidence map›Paper›PMID 19381263›Full record

ArticlePLoS genetics2009

Evidence for antisense transcription associated with microRNA target mRNAs in Arabidopsis.

Qing-Jun Luo, Manoj P Samanta, Fatih Köksal, Jaroslav Janda, David W Galbraith, Casey R Richardson, Fangqian Ou-Yang, Christopher D Rock

Open access · goldAbstract read
In one paragraph

Article in PLoS genetics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
8.0field-weighted citation impact, top 3% 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

23 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Review
  10. PLncDB: plant long non-coding RNA database.Bioinformatics (Oxford, England) · 2013
    Article
  11. Article
  12. Role of RNA interference (RNAi) in the Moss Physcomitrella patens.International journal of molecular sciences · 2013
    Review
  13. Article
  14. MicroRNAs in the moss Physcomitrella patens.Plant molecular biology · 2012
    Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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

8 authors at 2 institutions in 1 country.

Qing-Jun LuoDepartment of Biological Sciences, Texas Tech University, Lubbock, Texas, USA.
Manoj P Samanta
Fatih Köksal
Jaroslav Janda
David W Galbraith
Casey R Richardson
Fangqian Ou-Yang
Christopher D Rock
Texas Tech University · USUniversity of Arizona · US

Funding

Computational analysis of causality between miRNAs and antisense transcriptionR21GM077245 · NIGMS · TEXAS TECH UNIVERSITY · PI ROCK, CHRISTOPHER DALE · 2007 to 2009
$519k
NIGMS NIH HHS 1R21GM077245NIGMS NIH HHS R21 GM077245
6 · The paper itself

Abstract

Antisense transcription is a pervasive phenomenon, but its source and functional significance is largely unknown. We took an expression-based approach to explore microRNA (miRNA)-related antisense transcription by computational analyses of published whole-genome tiling microarray transcriptome and deep sequencing small RNA (smRNA) data. Statistical support for greater abundance of antisense transcription signatures and smRNAs was observed for miRNA targets than for paralogous genes with no miRNA cleavage site. Antisense smRNAs were also found associated with MIRNA genes. This suggests that miRNA-associated "transitivity" (production of small interfering RNAs through antisense transcription) is more common than previously reported. High-resolution (3 nt) custom tiling microarray transcriptome analysis was performed with probes 400 bp 5' upstream and 3' downstream of the miRNA cleavage sites (direction relative to the mRNA) for 22 select miRNA target genes. We hybridized RNAs labeled from the smRNA pathway mutants, including hen1-1, dcl1-7, hyl1-2, rdr6-15, and sgs3-14. Results showed that antisense transcripts associated with miRNA targets were mainly elevated in hen1-1 and sgs3-14 to a lesser extent, and somewhat reduced in dcl11-7, hyl11-2, or rdr6-15 mutants. This was corroborated by semi-quantitative reverse transcription PCR; however, a direct correlation of antisense transcript abundance in MIR164 gene knockouts was not observed. Our overall analysis reveals a more widespread role for miRNA-associated transitivity with implications for functions of antisense transcription in gene regulation. HEN1 and SGS3 may be links for miRNA target entry into different RNA processing pathways.

Indexed as

Transcription, GeneticArabidopsisArabidopsis ProteinsGene Expression Regulation, PlantMicroRNAsRNA, AntisenseRNA, MessengerArabidopsis ProteinsMicroRNAsRNA, AntisenseRNA, Messenger

Identifiers

PMID19381263
PMCPMC2664332
OpenAlexW2069966091

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.