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Analysis of master transcription factors related to Parkinson’s disease through the gene transcription regulatory network

INTRODUCTION: This study investigated the relationships between differentially co-expressed gene pairs or links (DCLs) and transcription factors (TFs) in the gene transcription regulatory network (GTRN) to clarify the molecular mechanisms underlying the pathogenesis of Parkinson’s disease (PD). MATE...

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Autores principales: Wei, Li, He, Fei, Zhang, Wen, Chen, Wenhua, Yu, Bo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Termedia Publishing House 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8425256/
https://www.ncbi.nlm.nih.gov/pubmed/34522247
http://dx.doi.org/10.5114/aoms.2019.89460
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author Wei, Li
He, Fei
Zhang, Wen
Chen, Wenhua
Yu, Bo
author_facet Wei, Li
He, Fei
Zhang, Wen
Chen, Wenhua
Yu, Bo
author_sort Wei, Li
collection PubMed
description INTRODUCTION: This study investigated the relationships between differentially co-expressed gene pairs or links (DCLs) and transcription factors (TFs) in the gene transcription regulatory network (GTRN) to clarify the molecular mechanisms underlying the pathogenesis of Parkinson’s disease (PD). MATERIAL AND METHODS: Microarray dataset GSE7621 from Gene Expression Omnibus (GEO) was used to identify differentially expressed genes (DEGs) and perform Gene Ontology (GO) enrichment analysis. Differentially co-expressed genes (DCGs) and DCLs were identified by the DCGL package in R soft-ware. DCLs that were potentially related to the regulation mechanisms, and corresponding TFs, were identified using the DR sort function in the DCGL V2.0 package. The GTRN was constructed with these DCLs-TFs, and visualized with Cytoscape software. RESULTS: A total of 131 DEGs, including 77 up-regulated DEGs and 54 down-regulated DEGs, were identified, which were mainly enriched for plasma membrane, cell activities, and metabolism. We found that ICAM1-LTBP and CTHRC1-UTP3 might alter gene regulation relationships in PD. The GTRN was constructed with DCLs-TFs, including 348 nodes (118 TFs and 230 DCGs) and 1045 DCLs. These TFs (AHR, SP1, PAX5, etc.) could regulate many target genes (e.g. ICAM1 and LTBP) in the GTRN of PD. CONCLUSIONS: ICAM1 and LTBP may play a role in PD symptom development and pathology, and might be regulated by important TFs (AHR, SP1, PAX5, etc.) identified in the GTRN of PD. These findings may help elucidate the molecular mechanisms underlying PD and find a novel drug target for this disease.
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spelling pubmed-84252562021-09-13 Analysis of master transcription factors related to Parkinson’s disease through the gene transcription regulatory network Wei, Li He, Fei Zhang, Wen Chen, Wenhua Yu, Bo Arch Med Sci Basic Research INTRODUCTION: This study investigated the relationships between differentially co-expressed gene pairs or links (DCLs) and transcription factors (TFs) in the gene transcription regulatory network (GTRN) to clarify the molecular mechanisms underlying the pathogenesis of Parkinson’s disease (PD). MATERIAL AND METHODS: Microarray dataset GSE7621 from Gene Expression Omnibus (GEO) was used to identify differentially expressed genes (DEGs) and perform Gene Ontology (GO) enrichment analysis. Differentially co-expressed genes (DCGs) and DCLs were identified by the DCGL package in R soft-ware. DCLs that were potentially related to the regulation mechanisms, and corresponding TFs, were identified using the DR sort function in the DCGL V2.0 package. The GTRN was constructed with these DCLs-TFs, and visualized with Cytoscape software. RESULTS: A total of 131 DEGs, including 77 up-regulated DEGs and 54 down-regulated DEGs, were identified, which were mainly enriched for plasma membrane, cell activities, and metabolism. We found that ICAM1-LTBP and CTHRC1-UTP3 might alter gene regulation relationships in PD. The GTRN was constructed with DCLs-TFs, including 348 nodes (118 TFs and 230 DCGs) and 1045 DCLs. These TFs (AHR, SP1, PAX5, etc.) could regulate many target genes (e.g. ICAM1 and LTBP) in the GTRN of PD. CONCLUSIONS: ICAM1 and LTBP may play a role in PD symptom development and pathology, and might be regulated by important TFs (AHR, SP1, PAX5, etc.) identified in the GTRN of PD. These findings may help elucidate the molecular mechanisms underlying PD and find a novel drug target for this disease. Termedia Publishing House 2019-10-29 /pmc/articles/PMC8425256/ /pubmed/34522247 http://dx.doi.org/10.5114/aoms.2019.89460 Text en Copyright: © 2019 Termedia & Banach https://creativecommons.org/licenses/by-nc-sa/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) License, allowing third parties to copy and redistribute the material in any medium or format and to remix, transform, and build upon the material, provided the original work is properly cited and states its license.
spellingShingle Basic Research
Wei, Li
He, Fei
Zhang, Wen
Chen, Wenhua
Yu, Bo
Analysis of master transcription factors related to Parkinson’s disease through the gene transcription regulatory network
title Analysis of master transcription factors related to Parkinson’s disease through the gene transcription regulatory network
title_full Analysis of master transcription factors related to Parkinson’s disease through the gene transcription regulatory network
title_fullStr Analysis of master transcription factors related to Parkinson’s disease through the gene transcription regulatory network
title_full_unstemmed Analysis of master transcription factors related to Parkinson’s disease through the gene transcription regulatory network
title_short Analysis of master transcription factors related to Parkinson’s disease through the gene transcription regulatory network
title_sort analysis of master transcription factors related to parkinson’s disease through the gene transcription regulatory network
topic Basic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8425256/
https://www.ncbi.nlm.nih.gov/pubmed/34522247
http://dx.doi.org/10.5114/aoms.2019.89460
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