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A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
Published on: August 16, 2017
Comprehensive identification of essential pathways and transcription factors related to epilepsy by gene set
Kan He1, Weizhong Xiao2, Wenwen Lv1
1Center for Stem Cell and Translational Medicine, School of Life Sciences, Anhui University, Hefei, Anhui 230601, P.R. China.
Abstract:
Epilepsy is a common chronic neurological disorder characterized by seizures or convulsions, and is known to affect patients with primary brain tumors. The etiology of epilepsy is superficially thought to be multifactorial; however, the genetic factors which may be involved in the pathogenesis of seizures have not yet been elucidated, particularly at the pathway level. In the present study, in order to systematically investigate the gene regulatory networks involved in epilepsy, we employed a microarray dataset from the public database library of Gene Expression Omnibus (GEO) associated with tumor-induced epileptogenesis and applied gene set enrichment analysis (GSEA) on these data sets and performed candidate transcription factor (TF) selection. As a result, 68 upregulated pathways, including the extracellular matrix (ECM)-receptor interaction (P=0.004) and peroxisome proliferator-activated receptor (PPAR) signaling pathways (P=0.045), as well as 4 downregulated pathways, including the GnRH signaling pathway (P=0.029) and gap junction (P=0.034) were identified as epileptogenesis-related pathways. The majority of these pathways identified have been previously reported and our results were in accordance with those reports. However, some of these pathways identified were novel. Finally, co-expression networks of the related pathways were constructed with the significant core genes and TFs, such as PPAR-γ and phosphatidylethanolamine-binding protein. The results of our study may contribute to the improved understanding of the molecular mechanisms of epileptogenesis on a genome-wide level.
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