Identification of hub genes involved in apparent metabolizable energy of chickens.

Zahra Pezeshkian, Seyed Ziaeddin Mirhoseini, Shahrokh Ghovvati
Author Information
  1. Zahra Pezeshkian: Department of Animal Sciences, Faculty of Agriculture, University of Guilan, Rasht, Iran. ORCID
  2. Seyed Ziaeddin Mirhoseini: Department of Animal Sciences, Faculty of Agriculture, University of Guilan, Rasht, Iran. ORCID
  3. Shahrokh Ghovvati: Department of Animal Sciences, Faculty of Agriculture, University of Guilan, Rasht, Iran. ORCID

Abstract

Feed efficiency is one of the most economically significant traits in a breeding program. Apparent metabolizable energy is the most used method to evaluate energy utilization for feed efficiency. The purpose of this study was to identify candidate genes of chickens with divergent apparent metabolizable energy by bioinformatics analysis. The gene expression profile of duodenal of the highest and lowest apparent metabolizable energy-ranked birds were analyzed. Differentially expressed genes were picked out using GEO2R tool. Gene ontology and pathway analysis were performed using bioinformatics tools. Cytoscape software was used to visualize protein-protein network. There were 201 DEGs, including 99 up-regulated genes enriched in metabolic pathways, Cellular senescence and Focal adhesion, and 102 down-regulated genes enriched in metabolic pathways, Regulation of actin cytoskeleton, Neuroactive ligand-receptor interaction, Calcium signaling pathway and Focal adhesion. Two important modules were detected and pathway enrichment analysis showed that they were mainly associated with Focal adhesion, Regulation of actin cytoskeleton and RNA transport. Fifteen hub genes were selected and among them, , and might be the core genes related to apparent metabolizable energy of chickens. These hub genes can be used as biomarkers for apparent metabolizable energy and feed efficiency in breeding program of chickens.

Keywords

MeSH Term

Animals
Chickens
Computational Biology
Gene Expression Profiling
Gene Expression Regulation, Neoplastic
Gene Ontology
Gene Regulatory Networks

Word Cloud

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