Evidence map›Paper›PMID 30602381›Full record

ArticleBMC molecular biology2019

MiRNAs differentially expressed in skeletal muscle of animals with divergent estimated breeding values for beef tenderness.

Berna I G Kappeler, Luciana C A Regitano, Mirele D Poleti, Aline S M Cesar, Gabriel C M Moreira, Gustavo Gasparin, Luiz L Coutinho

Open access · hybridAbstract read
In one paragraph

Article in BMC molecular biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
1.8field-weighted citation impact, top 16% 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

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. Exploring the miRNAs Profile in Dark-Cutting Beef.Foods (Basel, Switzerland) · 2024
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. 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

7 authors at 3 institutions in 1 country.

Berna I G KappelerDepartment of Animal Science, "Luiz de Queiroz" College of Agriculture, University of São Paulo, Piracicaba, SP, 13418-900, Brazil.
Luciana C A RegitanoEmbrapa Pecuária Sudeste, São Carlos, SP, 13560-970, Brazil.
Mirele D PoletiDepartment of Veterinary Medicine, Faculty of Animal Science and Food Engineering, University of São Paulo, Pirassununga, SP, 13635-900, Brazil.
Aline S M CesarDepartment of Animal Science, "Luiz de Queiroz" College of Agriculture, University of São Paulo, Piracicaba, SP, 13418-900, Brazil.
Gabriel C M MoreiraDepartment of Animal Science, "Luiz de Queiroz" College of Agriculture, University of São Paulo, Piracicaba, SP, 13418-900, Brazil.
Gustavo GasparinDepartment of Animal Science, "Luiz de Queiroz" College of Agriculture, University of São Paulo, Piracicaba, SP, 13418-900, Brazil.
Luiz L CoutinhoDepartment of Animal Science, "Luiz de Queiroz" College of Agriculture, University of São Paulo, Piracicaba, SP, 13418-900, Brazil. llcoutinho@usp.br.
Universidade de São Paulo · BRBrazilian Agricultural Research Corporation · BRUniversidade Cidade de São Paulo · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMicroRNAs (miRNAs) are small noncoding RNAs of approximately 22 nucleotides, highly conserved among species, which modulate gene expression by cleaving messenger RNA target or inhibiting translation. MiRNAs are involved in the regulation of many processes including cell proliferation, differentiation, neurogenesis, angiogenesis, and apoptosis. Beef tenderness is an organoleptic characteristic of great influence in the acceptance of meat by consumers. Previous studies have shown that collagen level, marbling, apoptosis and proteolysis are among the many factors that affect beef tenderness. Considering that miRNAs can modulate gene expression, this study was designed to identify differentially expressed miRNAs that could be modulating biological processes involved with beef tenderness.

resultsDeep sequence analysis of miRNA libraries from longissimus thoracis muscle allowed the identification of 42 novel and 308 known miRNAs. Among the known miRNAs, seven were specifically expressed in skeletal muscle. Differential expression analysis between animals with high (H) and low (L) estimated breeding values for shear force (EBVSF) revealed bta-mir-182 and bta-mir-183 are up-regulated (q value < 0.05) in animals with L EBVSF, and bta-mir-338 is up-regulated in animals with H EBVSF. The number of bovine predicted targets for bta-mir-182, bta-mir-183 and bta-mir-338 were 811, 281 and 222, respectively, which correspond to 1204 unique target genes. Among these, four of them, MEF2C, MAP3K2, MTDH and TNRC6B were common targets of the three differentially expressed miRNAs. The functional analysis identified important pathways related to tenderness such as apoptosis and the calpain-calpastatin system.

conclusionThe results obtained indicate the importance of miRNAs in the regulatory mechanisms that influence muscle proteolysis and meat tenderness and contribute to our better understanding of the role of miRNAs in biological processes associated with beef tenderness.

Indexed as

BreedingRed MeatAnimalsApoptosisCalcium-Binding ProteinsCattleMannitol DehydrogenasesMAP Kinase Kinase Kinase 2MEF2 Transcription FactorsMicroRNAsMuscle, SkeletalRNA-Binding ProteinsCalcium-Binding Proteinscalpastatinmannitol 2-dehydrogenase (NADP)Mannitol DehydrogenasesMAP Kinase Kinase Kinase 2MEF2 Transcription FactorsMicroRNAsRNA-Binding ProteinsBeefBos indicusbta-miRMicroRNAShear force

Identifiers

PMID30602381
PMCPMC6317189
OpenAlexW2908509300

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.