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Transcriptional profiling to identify the key genes and pathways of pterygium

PURPOSE: 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. MET...

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Autores principales: Chen, Yihui, Wang, Haoyu, Jiang, Yaping, Zhang, Xiaoyan, Wang, Qingzhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7204871/
https://www.ncbi.nlm.nih.gov/pubmed/32411530
http://dx.doi.org/10.7717/peerj.9056
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author Chen, Yihui
Wang, Haoyu
Jiang, Yaping
Zhang, Xiaoyan
Wang, Qingzhong
author_facet Chen, Yihui
Wang, Haoyu
Jiang, Yaping
Zhang, Xiaoyan
Wang, Qingzhong
author_sort Chen, Yihui
collection PubMed
description PURPOSE: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
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spelling pubmed-72048712020-05-14 Transcriptional profiling to identify the key genes and pathways of pterygium Chen, Yihui Wang, Haoyu Jiang, Yaping Zhang, Xiaoyan Wang, Qingzhong PeerJ Bioinformatics PURPOSE: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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. PeerJ Inc. 2020-05-04 /pmc/articles/PMC7204871/ /pubmed/32411530 http://dx.doi.org/10.7717/peerj.9056 Text en ©2020 Chen et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Chen, Yihui
Wang, Haoyu
Jiang, Yaping
Zhang, Xiaoyan
Wang, Qingzhong
Transcriptional profiling to identify the key genes and pathways of pterygium
title Transcriptional profiling to identify the key genes and pathways of pterygium
title_full Transcriptional profiling to identify the key genes and pathways of pterygium
title_fullStr Transcriptional profiling to identify the key genes and pathways of pterygium
title_full_unstemmed Transcriptional profiling to identify the key genes and pathways of pterygium
title_short Transcriptional profiling to identify the key genes and pathways of pterygium
title_sort transcriptional profiling to identify the key genes and pathways of pterygium
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7204871/
https://www.ncbi.nlm.nih.gov/pubmed/32411530
http://dx.doi.org/10.7717/peerj.9056
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