Evidence map›Paper›PMID 29184116›Full record

ArticleScientific reports2017

Proteomic and microRNA Transcriptome Analysis revealed the microRNA-SmyD1 network regulation in Skeletal Muscle Fibers performance of Chinese perch.

WuYing Chu, FangLiang Zhang, Rui Song, YuLong Li, Ping Wu, Lin Chen, Jia Cheng, ShaoJun Du, JianShe Zhang

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.7field-weighted citation impact, top 33% 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

7 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Molecular Mechanisms Regulating Muscle Plasticity in Fish.Animals : an open access journal from MDPI · 2020
    Review
  5. Article
  6. Article
  7. 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

9 authors at 1 institution in 2 countries.

WuYing ChuDepartment of Bioengineering and Environmental Science, Changsha University, Changsha, Hunan, 410003, China.
FangLiang ZhangDepartment of Bioengineering and Environmental Science, Changsha University, Changsha, Hunan, 410003, China.
Rui SongInstitute of Hunan Aquaculture and Fisheries, Changsha, 410005, China.
YuLong LiDepartment of Bioengineering and Environmental Science, Changsha University, Changsha, Hunan, 410003, China.
Ping WuDepartment of Bioengineering and Environmental Science, Changsha University, Changsha, Hunan, 410003, China.
Lin ChenDepartment of Bioengineering and Environmental Science, Changsha University, Changsha, Hunan, 410003, China.
Jia ChengDepartment of Bioengineering and Environmental Science, Changsha University, Changsha, Hunan, 410003, China.
ShaoJun DuDepartment of Bioengineering and Environmental Science, Changsha University, Changsha, Hunan, 410003, China.
JianShe ZhangDepartment of Bioengineering and Environmental Science, Changsha University, Changsha, Hunan, 410003, China. jzhang@ccsu.edu.cn.
Changsha University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fish myotomes are comprised of anatomically segregated fast and slow muscle fibers that possess different metabolic and contractile properties. Although the expression profile properties in fast and slow muscle fibers had been investigated at the mRNA levels, a comprehensive analysis at proteomic and microRNA transcriptomic levels is limited. In the present study, we first systematically compared the proteomic and microRNA transcriptome of the slow and fast muscles of Chinese perch (Siniperca chuatsi). Total of 2102 proteins were identified in muscle tissues. Among them, 99 proteins were differentially up-regulated and 400 were down-regulated in the fast muscle compared with slow muscle. MiRNA microarrays revealed that 199 miRNAs identified in the two types of muscle fibers. Compared with the fast muscle, the 32 miRNAs was up-regulated and 27 down-regulated in the slow muscle. Specifically, expression of miR-103 and miR-144 was negatively correlated with SmyD1a and SmyD1b expression in fast and slow muscles, respectively. The luciferase reporter assay further verified that the miR-103 and miR-144 directly regulated the SmyD1a and SmyD1b expression by targeting their 3'-UTR. The constructed miRNA-SmyD1 interaction network might play an important role in controlling the development and performance of different muscle fiber types in Chinese perch.

Indexed as

Gene Expression ProfilingProteomeProteomicsTranscriptome3' Untranslated RegionsAnimalsComputational BiologyGene Expression RegulationMicroRNAsModels, BiologicalMuscle Fibers, Fast-TwitchMuscle Fibers, SkeletalMuscle Fibers, Slow-TwitchPerchesRNA InterferenceRNA, Messenger3' Untranslated RegionsMicroRNAsProteomeRNA, Messenger

Identifiers

PMID29184116
PMCPMC5705591
OpenAlexW2770414538

What OpenQuestion holds

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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.