Evidence map›Paper›PMID 30223794›Full record

ArticleBMC genomics2018

MicroRNA profiling associated with muscle growth in modern broilers compared to an unselected chicken breed.

Bhuwan Khatri, Dongwon Seo, Stephanie Shouse, Jeong Hoon Pan, Nicholas J Hudson, Jae Kyeom Kim, Walter Bottje, Byungwhi C Kong

Open access · goldAbstract readComparative Study
In one paragraph

Article in BMC genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
1.4field-weighted citation impact, top 21% 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

20 citing papers in PubMed, 37 citations in OpenAlex.

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  14. Nutrition and microRNAs: Novel Insights to Fight Sarcopenia.Antioxidants (Basel, Switzerland) · 2020
    Review
  15. Article
  16. Article
  17. MicroRNA regulatory networks in the pathogenesis of sarcopenia.Journal of cellular and molecular medicine · 2020
    Review
  18. Review
  19. Article
  20. mRNAs expression profiles of high glucose-induced memory in human umbilical vein endothelial cells.Diabetes, metabolic syndrome and obesity : targets and therapy · 2019
    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

8 authors at 2 institutions in 2 countries.

Bhuwan KhatriDepartment of Poultry Science, Center of Excellence for Poultry Science, University of Arkansas, Fayetteville, AR, 72701, USA.
Dongwon SeoDepartment of Poultry Science, Center of Excellence for Poultry Science, University of Arkansas, Fayetteville, AR, 72701, USA.
Stephanie ShouseDepartment of Poultry Science, Center of Excellence for Poultry Science, University of Arkansas, Fayetteville, AR, 72701, USA.
Jeong Hoon PanSchool of Human Environmental Sciences, University of Arkansas, Fayetteville, AR, 72701, USA.
Nicholas J HudsonSchool of Agriculture and Food Sciences, The University of Queensland, QLD4343, Gatton, Australia.
Jae Kyeom KimSchool of Human Environmental Sciences, University of Arkansas, Fayetteville, AR, 72701, USA.
Walter BottjeDepartment of Poultry Science, Center of Excellence for Poultry Science, University of Arkansas, Fayetteville, AR, 72701, USA.
Byungwhi C KongDepartment of Poultry Science, Center of Excellence for Poultry Science, University of Arkansas, Fayetteville, AR, 72701, USA. bkong@uark.edu.
University of Arkansas at Fayetteville · USAgriculture and Food · AU

Funding

USDA-NIFA 2013-01953
6 · The paper itself

Abstract

backgroundGenetically selected modern broiler chickens have acquired outstanding production efficiency through rapid growth and improved feed efficiency compared to unselected chicken breeds. Recently, we analyzed the transcriptome of breast muscle tissues obtained from modern pedigree male (PeM) broilers (rapid growth and higher efficiency) and foundational Barred Plymouth Rock (BPR) chickens (slow growth and poorer efficiency). This study was designed to investigate microRNAs that play role in rapid growth of the breast muscles in modern broiler chickens.

resultsIn this study, differential abundance of microRNA (miRNA) was analyzed in breast muscle of PeM and BPR chickens and the results were integrated with differentially expressed (DE) mRNA in the same tissues. A total of 994 miRNA were identified in PeM and BPR chicken lines from the initial analysis of small RNA sequencing data. After filtering and statistical analyses, the results showed miR-2131-5p, miR-221-5p, miR-126-3p, miR-146b-5p, miR-10a-5p, let-7b, miR-125b-5p, and miR-146c-5p up-regulated whereas miR-206 down-regulated in PeM compared to BPR breast muscle. Based on inhibitory regulations of miRNAs on the mRNA abundance, our computational analysis using miRDB, an online software, predicated that 118 down-regulated mRNAs may be targeted by the up-regulated miRNAs, while 35 up-regulated mRNAs appear to be due to a down-regulated miRNA (i.e., miR-206). Functional network analyses of target genes of DE miRNAs showed their involvement in calcium signaling, axonal guidance signaling, and NRF2-mediated oxidative stress response pathways suggesting their involvement in breast muscle growth in chickens.

conclusionFrom the integrated analyses of differentially expressed miRNA-mRNA data, we were able to identify breast muscle specific miRNAs and their target genes whose concerted actions can contribute to rapid growth and higher feed efficiency in modern broiler chickens. This study provides foundation data for elucidating molecular mechanisms that govern muscle growth in chickens.

Indexed as

BreedingGene Expression RegulationTranscriptomeAnimalsBreastChickensCluster AnalysisComputational BiologyMaleMetabolic Networks and PathwaysMicroRNAsMuscle DevelopmentRNA, MessengerMicroRNAsRNA, MessengerBarred Plymouth RockDifferential expressionmiRNAPedigree male broilerProduction efficiency

Identifiers

PMID30223794
PMCPMC6142689
OpenAlexW2891502533

What OpenQuestion holds

Textmetadata
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.