Evidence map›Paper›PMID 23071387›Full record

ArticleEvolutionary bioinformatics online2012

Translation Efficiency in Upstream Region of microRNA Targets in Arabidopsis thaliana.

Wanjun Gu, Chuanying Zhai, Xiaofei Wang, Xueying Xie, Gurunadh Parinandi, Tong Zhou

Open access · goldAbstract read
In one paragraph

Article in Evolutionary bioinformatics online, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.1field-weighted citation impact, top 47% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. 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

6 authors at 1 institution in 1 country.

Wanjun GuKey Laboratory of Child Development and Learning Science of Ministry of Education of China, Southeast University, Nanjing, Jiangsu 210096, China.
Chuanying Zhai
Xiaofei Wang
Xueying Xie
Gurunadh Parinandi
Tong Zhou
Southeast University · CN

Funding

Selectively targeting delta opioid receptor subtypes to control drinking behaviorR01AA020401 · NIAAA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI WHISTLER, JENNIFER L · 2011 to 2015
$1.8M
NIAAA NIH HHS R01 AA020401
6 · The paper itself

Abstract

With respect to upstream regions of microRNA (miRNA) target sites located in protein coding sequences, experimental studies have suggested rare codons, rather than frequent codons, are important for miRNA function, because they slow down the local translational process. But, whether there is a trend of reduced translation efficiency near miRNA targets is still unknown. Using Arabidopsis thaliana, we perform genome-wide analysis of synonymous codon usage in upstream regions of miRNA target sites. At the whole genome level, we find no significant selection signals for decreased translational efficiency. However, the same genome analyses do show substantial variations of translation efficiency reduction among miRNA targets. We find that miRNA conservation level, gene codon usage bias, and the mechanism of miRNA action can account for the differences in translation efficiency. But gene's GC content, gene expression level, and miRNA target's conservation level have no effect on local translation efficiency of miRNA targets. Although local translation efficiency in the upstream region of miRNA targets is related to miRNA function in A. thaliana, the selection signal of rare codon usage in that region is weak. We propose some other biological factors are more important than local translation efficiency in miRNA action when miRNA targets are located in protein coding sequences.

Indexed as

miRNA bindingsynonymous codonstranslation efficiency

Identifiers

PMID23071387
PMCPMC3469488
OpenAlexW2074414885

What OpenQuestion holds

Textmetadata
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.