Transcriptional profiling to identify the key genes and pathways of pterygium

• Published in: PeerJ (San Francisco, CA) Vol. 8; p. e9056
• Main Authors: Chen, Yihui, Wang, Haoyu, Jiang, Yaping, Zhang, Xiaoyan, Wang, Qingzhong
• Format: Journal Article
• Language: English
• Published: United States PeerJ. Ltd 04.05.2020; PeerJ, Inc; PeerJ Inc
• Subjects: 1-Phosphatidylinositol 3-kinase; Age; AKT protein; Analysis; Biochemistry; Bioinformatics; Cell adhesion; Cell migration; Cornea; Deoxyribonucleic acid; Diseases; DNA; Endoplasmic reticulum; Extracellular matrix; Eye diseases; Gene expression; Genes; Genetic aspects; Genetic research; Genomes; Hemoglobin; Hub genes; Molecular biology; Novels; Ocular surface disease; Ontology; Ophthalmology; Pathogenesis; Photoreceptors; Pterygium; Ribonucleic acid; RNA; RNA sequencing; Signal transduction; Software; Studies; Transcription; Transcription (Genetics); Weighted gene co-expression network analysis; United States > US; Pterygium; RNA sequencing; Ocular surface disease; Hub genes; Pathogenesis; Weighted gene co-expression network analysis
• ISSN: 2167-8359; 2167-8359
• DOI: 10.7717/peerj.9056

Pterygium results from a variety of biological pathways that are involved in the formation of ocular surface diseases. However, the exact pathogenesis of pterygium is still unclear. Our study focused on gene expression profiles to better understand the potential mechanisms of pterygium. RNA sequencing experiments were performed on clinical pterygium tissues and normal conjunctival tissues. To identify the hub genes for the development of pterygium, we further conducted weighted gene co-expression network analysis (WGCNA). qRT-PCR was utilized to validate the dysregulation of the most significant differentially expressed genes (DEGs) and key hub genes in the independent subjects. A total of 339 DEGs (P-adjusted < 0.05 and log2 fold change [log2FC] ≥ 1.0) were obtained that reached statistical significance with p-values < 0.05. Among them, 200 DEGs were upregulated; these genes were mainly associated with the extracellular matrix and with cell adhesion or migration. In contrast, the 139 downregulated genes were enriched for endocrine and inflammation pathways. With regard to WGCNA, five modules were assigned based on the DEG profiles, and the biological functions of each module were verified with previously published GO terms. The functions included ECM-receptor interactions, the PI3K-Akt signalling pathway and an endoplasmic reticulum (ER)-related pathway. The five hub genes with the highest connectivity in each module and the five most significant DEGs showed dysregulated expression in the independent cohort samples. RNA sequencing and WGCNA provided novel insights into the potential regulatory mechanisms of pterygium. The identified DEGs and hub genes, which were classified into two groups according to different functions or signalings, may provide important references for further research on the molecular biology of pterygium.