Evidence map›Paper›PMID 27507983›Full record

ArticleFrontiers in plant science2016

Validation of Suitable Reference Genes for Assessing Gene Expression of MicroRNAs in Lonicera japonica.

Yaolong Wang, Juan Liu, Xumin Wang, Shuang Liu, Guoliang Wang, Junhui Zhou, Yuan Yuan, Tiying Chen, Chao Jiang, Liangping Zha and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in plant science, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.7field-weighted citation impact, top 26% 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

6 citing papers in PubMed, 9 citations in OpenAlex.

  1. MicroRNAs in Medicinal Plants.International journal of molecular sciences · 2022
    Review
  2. Article
  3. Article
  4. Article
  5. CaScientific reports · 2018
    Article
  6. 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

11 authors at 3 institutions in 1 country.

Yaolong WangState Key Laboratory Breeding Base of Dao-di Herbs, National Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing, China.
Juan LiuState Key Laboratory Breeding Base of Dao-di Herbs, National Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing, China.
Xumin WangBeijing Institute of Genomics, Chinese Academy of Sciences Beijing, China.
Shuang LiuState Key Laboratory Breeding Base of Dao-di Herbs, National Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing, China.
Guoliang WangBeijing Institute of Genomics, Chinese Academy of Sciences Beijing, China.
Junhui ZhouState Key Laboratory Breeding Base of Dao-di Herbs, National Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing, China.
Yuan YuanState Key Laboratory Breeding Base of Dao-di Herbs, National Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing, China.
Tiying ChenState Key Laboratory Breeding Base of Dao-di Herbs, National Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing, China.
Chao JiangState Key Laboratory Breeding Base of Dao-di Herbs, National Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing, China.
Liangping ZhaState Key Laboratory Breeding Base of Dao-di Herbs, National Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing, China.
Luqi HuangState Key Laboratory Breeding Base of Dao-di Herbs, National Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing, China.
Chinese Academy of Medical Sciences & Peking Union Medical College · CNBeijing Institute of Genomics · CNChinese Academy of Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MicroRNAs (miRNAs), which play crucial regulatory roles in plant secondary metabolism and responses to the environment, could be developed as promising biomarkers for different varieties and production areas of herbal medicines. However, limited information is available for miRNAs from Lonicera japonica, which is widely used in East Asian countries owing to various pharmaceutically active secondary metabolites. Selection of suitable reference genes for quantification of target miRNA expression through quantitative real-time (qRT)-PCR is important for elucidating the molecular mechanisms of secondary metabolic regulation in different tissues and varieties of L. japonica. For precise normalization of gene expression data in L. japonica, 16 candidate miRNAs were examined in three tissues, as well as 21 cultivated varieties collected from 16 production areas, using GeNorm, NormFinder, and RefFinder algorithms. Our results revealed combination of u534122 and u3868172 as the best reference genes across all samples. Their specificity was confirmed by detecting the cycling threshold (C t) value ranges in different varieties of L. japonica collected from diverse production areas, suggesting the use of these two reference miRNAs is sufficient for accurate transcript normalization with different tissues, varieties, and production areas. To our knowledge, this is the first report on validation of reference miRNAs in honeysuckle (Lonicera spp.). Restuls from this study can further facilitate discovery of functional regulatory miRNAs in different varieties of L. japonica.

Indexed as

different varietiesLonicera japonicamicroRNAsnormalizationqRT-PCRreference genevalidation

Identifiers

PMID27507983
PMCPMC4961011
OpenAlexW2494459710

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.