Network-based inference of master regulators in epithelial membrane protein 2-treated human RPE cells

Abstract

Abstract Background The application of cell-specific construction of transcription regulatory networks (TRNs) to identify their master regulators (MRs) in EMP2 induced vascular proliferation disorders has been largely unexplored. Methods Different expression gene (DEGs) analyses was processed with DESeq2 R package, for public RNA-seq transcriptome data of EMP2-treated hRPECs versus vector control (VC) or wild type (WT) hRPECs. Virtual Inference of protein activity by Enriched Regulon analysis (VIPER) was used for inferring regulator activity and ARACNE algorithm was conducted to construct TRNs and identify some MRs with DEGs from comparisons. Results Functional analysis of DEGs and the module analysis of TRNs demonstrated that over-expressed EMP2 leads to a significant induction in the activity of regulators next to transcription factors and other genes implicated in vasculature development, cell proliferation, and protein kinase B signaling, whereas regulators near several genes of platelet activation vascular proliferation were repressed. Among these, PDGFA, ALDH1L2, BA1AP3, ANGPT1 and ST3GAL5 were found differentially expressed and significantly activitve in EMP2-over-expressed hRPECs versus vector control under hypoxia and may thus identified as MRs for EMP2-induced lesion under hypoxia. Conclusions MRs obtained in this study might serve as potential biomarkers for EMP2 induced lesion under hypoxia, illustrating gene expression landscapes which might be specific for diabetic retinopathy and might provide improved understanding of the disease.

Keywords

• Differentially expressed genes (DEGs)
• Epithelial membrane protein 2 (EMP2)
• Retinal pigment epithelial cells (hRPECs)
• Computational inference
• Gene expression
• Master regulators (MRs)