Evidence map›Paper›PMID 25856313›Full record

ArticlePloS one2015

Bioinformatic identification and expression analysis of banana microRNAs and their targets.

Juan Chai, Renjun Feng, Hourui Shi, Mengyun Ren, Yindong Zhang, Jingyi Wang

Abstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Banana breeding by genome design.Journal of integrative plant biology · 2025
    Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. MiR-375 targets KLF4 and impacts the proliferation of colorectal carcinoma.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2016
    Article
  10. Review
  11. 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

6 authors.

Juan ChaiKey Laboratory of Biology and Genetic Resources of Tropical Crops, Ministry of Agriculture, Institute of Tropical Bioscience and Biotechnology, Chinese Academy of Tropical Agricultural Sciences, Haikou, Hainan, China.
Renjun FengKey Laboratory of Biology and Genetic Resources of Tropical Crops, Ministry of Agriculture, Institute of Tropical Bioscience and Biotechnology, Chinese Academy of Tropical Agricultural Sciences, Haikou, Hainan, China.
Hourui ShiKey Laboratory of Biology and Genetic Resources of Tropical Crops, Ministry of Agriculture, Institute of Tropical Bioscience and Biotechnology, Chinese Academy of Tropical Agricultural Sciences, Haikou, Hainan, China; College of Agronomy, Hainan University, Haikou, Hainan, China.
Mengyun RenKey Laboratory of Biology and Genetic Resources of Tropical Crops, Ministry of Agriculture, Institute of Tropical Bioscience and Biotechnology, Chinese Academy of Tropical Agricultural Sciences, Haikou, Hainan, China; College of Agronomy, Hainan University, Haikou, Hainan, China.
Yindong ZhangCollege of Agronomy, Hainan University, Haikou, Hainan, China.
Jingyi WangKey Laboratory of Biology and Genetic Resources of Tropical Crops, Ministry of Agriculture, Institute of Tropical Bioscience and Biotechnology, Chinese Academy of Tropical Agricultural Sciences, Haikou, Hainan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MicroRNAs (miRNAs) represent a class of endogenous non-coding small RNAs that play important roles in multiple biological processes by degrading targeted mRNAs or repressing mRNA translation. Thousands of miRNAs have been identified in many plant species, whereas only a limited number of miRNAs have been predicted in M. acuminata (A genome) and M. balbisiana (B genome). Here, previously known plant miRNAs were BLASTed against the Expressed Sequence Tag (EST) and Genomic Survey Sequence (GSS), a database of banana genes. A total of 32 potential miRNAs belonging to 13 miRNAs families were detected using a range of filtering criteria. 244 miRNA:target pairs were subsequently predicted, most of which encode transcription factors or enzymes that participate in the regulation of development, growth, metabolism, and other physiological processes. In order to validate the predicted miRNAs and the mutual relationship between miRNAs and their target genes, qRT-PCR was applied to detect the tissue-specific expression levels of 12 putative miRNAs and 6 target genes in roots, leaves, flowers, and fruits. This study provides some important information about banana pre-miRNAs, mature miRNAs, and miRNA target genes and these findings can be applied to future research of miRNA functions.

Indexed as

Computational BiologyDatabases, GeneticDNA PrimersExpressed Sequence TagsGene Expression Regulation, PlantGenes, PlantMicroRNAsMusaReal-Time Polymerase Chain ReactionReverse Transcriptase Polymerase Chain ReactionDNA PrimersMicroRNAs

Identifiers

PMID25856313
PMCPMC4391839

What OpenQuestion holds

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LicenceCC BY
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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.