Prediction of microRNAs affecting genes involved in Peroxisome proliferator-activated receptors (PPARs) signaling pathway in broilers

Document Type : Full Research Paper

Authors

1 Department of Animal Science, Faculty of Animal Science and Food Technology, Agricultural science and Natural Resources University of Khuzestan, Mollasani, Iran

2 Department of Animal Science, Faculty of Animal science and Food Technology, Agricultural Science and Natural Resources University of Khuzestan, Mollasani, Iran

3 Associate Professor, Department of Animal Science, Faculty of Animal science and Food Technology, Agricultural Science and Natural Resources University of Khuzestan, Ahvaz, Iran

Abstract

Chicken is one of the most important sources of meat in human societies. One of the important goals of broiler breeding is to reduce the accumulation of fat in broilers. The pathways of peroxisome proliferative activating receptors (PPARs signal pathway) play an important role in fat accumulation. This pathway includes a group of nuclear receptor proteins that play a key role in proliferation, cell differentiation, and metabolism (carbohydrates, lipids, proteins). Therefore, it is important to identify the genes involved in this pathway. This study was performed to predict the microRNAs affecting the peroxisome proliferator receptors (PPARs) with the aim of reducing fat accumulation in broilers. Analysis of the chicken genome reference file in the KEGG database led to the identification of 68 genes involved in the signaling pathway (PPAR). Then, the gene network is drawn by using a STRING network. In addition, protein interaction network analysis was performed using Cytoscape software. Eight genes ACOX1, PPARA, LPL, FABP3, CPT1A, EHHADH, SCD, and PPARGC1 were selected as the most influential genes of the PPAR signaling pathway based on centrality indices (including degree centrality, betweenness centrality, closeness centrality) provided by Cytoscape software. Also, the microRNAs corresponding to these genes was identified using databases: MIRdb and Targetscan. Finally, the MirNet network was utilized for the prediction of target genes and drawing a protein-microRNA interaction network. The results showed that gga-mir-1759-3p affects three genes CPT1A, LPL, and PPARGC1A. Perhaps using this micro-RNA can reduce the accumulation of fat in broiler.                                

Keywords

References

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Veterinary Research & Biological Products
Volume 35, Issue 3 - Serial Number 3
September 2022
Pages 2-11

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History

  • Receive Date: 07 August 2021
  • Revise Date: 21 September 2021
  • Accept Date: 28 September 2021

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