Evidence map›Paper›PMID 32606372›Full record

ArticleScientific reports2020

miRNA-mRNA network regulation in the skeletal muscle fiber phenotype of chickens revealed by integrated analysis of miRNAome and transcriptome.

Yifan Liu, Ming Zhang, Yanju Shan, Gaige Ji, Xiaojun Ju, Yunjie Tu, Zhongwei Sheng, Jingfang Xie, Jianmin Zou, Jingting Shu

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

29 citing papers in PubMed, 39 citations in OpenAlex.

  1. Article
  2. Article
  3. MiRNAs in Poultry Health and Production: Progress and Challenges.Animals : an open access journal from MDPI · 2025
    Review
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  13. Comparative Genomics Identifies the Evolutionarily Conserved GeneInternational journal of molecular sciences · 2023
    Article
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  15. 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

10 authors at 3 institutions in 1 country.

Yifan Liu *Key Laboratory for Poultry Genetics and Breeding of Jiangsu Province, Poultry Institute, Chinese Academy of Agricultural Sciences, Yangzhou, 225125, Jiangsu, China.
Ming Zhang *Key Laboratory for Poultry Genetics and Breeding of Jiangsu Province, Poultry Institute, Chinese Academy of Agricultural Sciences, Yangzhou, 225125, Jiangsu, China.
Yanju ShanKey Laboratory for Poultry Genetics and Breeding of Jiangsu Province, Poultry Institute, Chinese Academy of Agricultural Sciences, Yangzhou, 225125, Jiangsu, China.
Gaige JiKey Laboratory for Poultry Genetics and Breeding of Jiangsu Province, Poultry Institute, Chinese Academy of Agricultural Sciences, Yangzhou, 225125, Jiangsu, China.
Xiaojun JuKey Laboratory for Poultry Genetics and Breeding of Jiangsu Province, Poultry Institute, Chinese Academy of Agricultural Sciences, Yangzhou, 225125, Jiangsu, China.
Yunjie TuKey Laboratory for Poultry Genetics and Breeding of Jiangsu Province, Poultry Institute, Chinese Academy of Agricultural Sciences, Yangzhou, 225125, Jiangsu, China.
Zhongwei ShengKey Laboratory for Poultry Genetics and Breeding of Jiangsu Province, Poultry Institute, Chinese Academy of Agricultural Sciences, Yangzhou, 225125, Jiangsu, China.
Jingfang XieJiangxi Academy of Agricultural Science, Nanchang, 330200, Jiangxi, China.
Jianmin ZouKey Laboratory for Poultry Genetics and Breeding of Jiangsu Province, Poultry Institute, Chinese Academy of Agricultural Sciences, Yangzhou, 225125, Jiangsu, China.
Jingting ShuKey Laboratory for Poultry Genetics and Breeding of Jiangsu Province, Poultry Institute, Chinese Academy of Agricultural Sciences, Yangzhou, 225125, Jiangsu, China. shujingting@163.com.
Chinese Academy of Agricultural Sciences · CNPoultry Research Institute · CNJiangxi Academy of Agricultural Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Skeletal muscle fibers are primarily categorized into oxidative and glycolytic fibers, and the ratios of different myofiber types are important factors in determining livestock meat quality. However, the molecular mechanism for determining muscle fiber types in chickens was hardly understood. In this study, we used RNA sequencing to systematically compare mRNA and microRNA transcriptomes of the oxidative muscle sartorius (SART) and glycolytic muscle pectoralis major (PMM) of Chinese Qingyuan partridge chickens. Among the 44,705 identified mRNAs in the two types of muscles, 3,457 exhibited significantly different expression patterns, including 2,364 up-regulated and 1,093 down-regulated mRNAs in the SART. A total of 698 chicken miRNAs were identified, including 189 novel miRNAs, among which 67 differentially expressed miRNAs containing 42 up-regulated and 25 down-regulated miRNAs in the SART were identified. Furthermore, function enrichment showed that the differentially expressed mRNAs and miRNAs were involved in energy metabolism, muscle contraction, and calcium, peroxisome proliferator-activated receptor (PPAR), insulin and adipocytokine signaling. Using miRNA-mRNA integrated analysis, we identified several candidate miRNA-gene pairs that might affect muscle fiber performance, viz, gga-miR-499-5p/SOX6 and gga-miR-196-5p/CALM1, which were supported by target validation using the dual-luciferase reporter system. This study revealed a mass of candidate genes and miRNAs involved in muscle fiber type determination, which might help understand the molecular mechanism underlying meat quality traits in chickens.

Indexed as

TranscriptomeAnimalsChickensGene Expression ProfilingGene Regulatory NetworksMicroRNAsMuscle Fibers, SkeletalMuscle, SkeletalPhenotypeRNA, MessengerMicroRNAsRNA, Messenger

Identifiers

PMID32606372
PMCPMC7326969
OpenAlexW3039118932

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.