Multi–Omics Analysis of Key microRNA–mRNA Metabolic Regulatory Networks in Skeletal Muscle of Obese Rabbits
microRNAs (miRNAs), small non-coding RNA with a length of about 22 nucleotides, are involved in the energy metabolism of skeletal muscle cells. However, their molecular mechanism of metabolism in rabbit skeletal muscle is still unclear. In this study, 16 rabbits, 8 in the control group (CON–G) and 8...
Main Authors: | , , , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-04-01
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Series: | International Journal of Molecular Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/1422-0067/22/8/4204 |
Summary: | microRNAs (miRNAs), small non-coding RNA with a length of about 22 nucleotides, are involved in the energy metabolism of skeletal muscle cells. However, their molecular mechanism of metabolism in rabbit skeletal muscle is still unclear. In this study, 16 rabbits, 8 in the control group (CON–G) and 8 in the experimental group (HFD–G), were chosen to construct an obese model induced by a high–fat diet fed from 35 to 70 days of age. Subsequently, 54 differentially expressed miRNAs, 248 differentially expressed mRNAs, and 108 differentially expressed proteins related to the metabolism of skeletal muscle were detected and analyzed with three sequencing techniques (small RNA sequencing, transcriptome sequencing, and tandem mass tab (TMT) protein technology). It was found that 12 miRNAs and 12 core genes (e.g., <i>CRYL1</i>, <i>VDAC3</i> and <i>APIP</i>) were significantly different in skeletal muscle from rabbits in the two groups. The network analysis showed that seven miRNA-mRNA pairs were involved in metabolism. Importantly, two miRNAs (miR-92a-3p and miR-30a/c/d-5p) regulated three transcription factors (MYBL2, STAT1 and IKZF1) that may be essential for lipid metabolism. These results enhance our understanding of molecular mechanisms associated with rabbit skeletal muscle metabolism and provide a basis for future studies in the metabolic diseases of human obesity. |
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ISSN: | 1661-6596 1422-0067 |