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Integrative analysis of microRNAs and mRNAs revealed regulation of composition and metabolism in Nelore cattle

Overview of attention for article published in BMC Genomics, February 2018
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Title
Integrative analysis of microRNAs and mRNAs revealed regulation of composition and metabolism in Nelore cattle
Published in
BMC Genomics, February 2018
DOI 10.1186/s12864-018-4514-3
Pubmed ID
Authors

Gabriella B. Oliveira, Luciana C. A. Regitano, Aline S. M. Cesar, James M. Reecy, Karina Y. Degaki, Mirele D. Poleti, Andrezza M. Felício, James E. Koltes, Luiz L. Coutinho

Abstract

The amount of intramuscular fat can influence the sensory characteristics and nutritional value of beef, thus the selection of animals with adequate fat deposition is important to the consumer. There is growing knowledge about the genes and pathways that control the biological processes involved in fat deposition in muscle. MicroRNAs (miRNAs) belong to a well-conserved class of non-coding small RNAs that modulate gene expression across a range of biological functions in animal development and physiology. The aim of this study was to identify differentially expressed (DE) miRNAs, regulatory candidate genes and co-expression networks related to intramuscular fat (IMF) deposition. To achieve this, we used mRNA and miRNA expression data from the Longissimus dorsi muscle of 30 Nelore steers with high (H) and low (L) genomic estimated breeding values (GEBV) for IMF deposition. Differential miRNA expression analysis between animals with extreme GEBV values for IMF identified six DE miRNAs (FDR 10%). Functional annotation of the target genes for these microRNAs indicated that the PPARs signaling pathway is involved with IMF deposition. Candidate regulatory genes such as SDHAF4, FBXO17, ALDOA and PKM were identified by partial correlation with information theory (PCIT), phenotypic impact factor (PIF) and regulatory impact factor (RIF) co-expression approaches from integrated miRNA-mRNA expression data. Two DE miRNAs (FDR 10%), bta-miR-143 and bta-miR-146b, which were upregulated in the Low IMF group, were correlated with regulatory candidate genes, which were functionally enriched for fatty acid oxidation GO terms. Co-expression patterns obtained by weighted correlation network analysis (WGCNA), which showed possible interaction and regulation between mRNAs and miRNAs, identified several modules related to immune system function, protein metabolism, energy metabolism and glucose catabolism according to in silico analysis performed herein. In this study, several genes and miRNAs were identified as candidate regulators of IMF by analyzing DE miRNAs using two different miRNA-mRNA co-expression network methods. This study contributes to the understanding of potential regulatory mechanisms of gene signaling networks involved in fat deposition processes measured in muscle. Glucose metabolism and inflammation processes were the main pathways found in silico to influence intramuscular fat deposition in beef cattle in the integrative mRNA-miRNA co-expression analysis.

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Mendeley readers

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The data shown below were compiled from readership statistics for 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 67 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 11 16%
Student > Ph. D. Student 10 15%
Researcher 9 13%
Student > Bachelor 6 9%
Student > Doctoral Student 6 9%
Other 7 10%
Unknown 18 27%
Readers by discipline Count As %
Agricultural and Biological Sciences 22 33%
Biochemistry, Genetics and Molecular Biology 12 18%
Veterinary Science and Veterinary Medicine 5 7%
Computer Science 2 3%
Psychology 1 1%
Other 3 4%
Unknown 22 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 February 2018.
All research outputs
#18,587,406
of 23,023,224 outputs
Outputs from BMC Genomics
#8,229
of 10,699 outputs
Outputs of similar age
#328,238
of 437,841 outputs
Outputs of similar age from BMC Genomics
#161
of 204 outputs
Altmetric has tracked 23,023,224 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,699 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 12th percentile – i.e., 12% of its peers scored the same or lower than it.
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We're also able to compare this research output to 204 others from the same source and published within six weeks on either side of this one. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.