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Identification of Infertility-Associated Topologically Important Genes Using Weighted Co-expression Network Analysis

Endometriosis has been associated with a high risk of infertility. However, the underlying molecular mechanism of infertility in endometriosis remains poorly understood. In our study, we aimed to discover topologically important genes related to infertility in endometriosis, based on the structure n...

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Autores principales: Wu, Jingni, Xia, Xiaomeng, Hu, Ye, Fang, Xiaoling, Orsulic, Sandra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7887323/
https://www.ncbi.nlm.nih.gov/pubmed/33613630
http://dx.doi.org/10.3389/fgene.2021.580190
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author Wu, Jingni
Xia, Xiaomeng
Hu, Ye
Fang, Xiaoling
Orsulic, Sandra
author_facet Wu, Jingni
Xia, Xiaomeng
Hu, Ye
Fang, Xiaoling
Orsulic, Sandra
author_sort Wu, Jingni
collection PubMed
description Endometriosis has been associated with a high risk of infertility. However, the underlying molecular mechanism of infertility in endometriosis remains poorly understood. In our study, we aimed to discover topologically important genes related to infertility in endometriosis, based on the structure network mining. We used microarray data from the Gene Expression Omnibus (GEO) database to construct a weighted gene co-expression network for fertile and infertile women with endometriosis and to identify gene modules highly correlated with clinical features of infertility in endometriosis. Additionally, the protein–protein interaction network analysis was used to identify the potential 20 hub messenger RNAs (mRNAs) while the network topological analysis was used to identify nine candidate long non-coding RNAs (lncRNAs). Functional annotations of clinically significant modules and lncRNAs revealed that hub genes might be involved in infertility in endometriosis by regulating G protein-coupled receptor signaling (GPCR) activity. Gene Set Enrichment Analysis showed that the phospholipase C-activating GPCR signaling pathway is correlated with infertility in patients with endometriosis. Taken together, our analysis has identified 29 hub genes which might lead to infertility in endometriosis through the regulation of the GPCR network.
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spelling pubmed-78873232021-02-18 Identification of Infertility-Associated Topologically Important Genes Using Weighted Co-expression Network Analysis Wu, Jingni Xia, Xiaomeng Hu, Ye Fang, Xiaoling Orsulic, Sandra Front Genet Genetics Endometriosis has been associated with a high risk of infertility. However, the underlying molecular mechanism of infertility in endometriosis remains poorly understood. In our study, we aimed to discover topologically important genes related to infertility in endometriosis, based on the structure network mining. We used microarray data from the Gene Expression Omnibus (GEO) database to construct a weighted gene co-expression network for fertile and infertile women with endometriosis and to identify gene modules highly correlated with clinical features of infertility in endometriosis. Additionally, the protein–protein interaction network analysis was used to identify the potential 20 hub messenger RNAs (mRNAs) while the network topological analysis was used to identify nine candidate long non-coding RNAs (lncRNAs). Functional annotations of clinically significant modules and lncRNAs revealed that hub genes might be involved in infertility in endometriosis by regulating G protein-coupled receptor signaling (GPCR) activity. Gene Set Enrichment Analysis showed that the phospholipase C-activating GPCR signaling pathway is correlated with infertility in patients with endometriosis. Taken together, our analysis has identified 29 hub genes which might lead to infertility in endometriosis through the regulation of the GPCR network. Frontiers Media S.A. 2021-02-03 /pmc/articles/PMC7887323/ /pubmed/33613630 http://dx.doi.org/10.3389/fgene.2021.580190 Text en Copyright © 2021 Wu, Xia, Hu, Fang and Orsulic. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Wu, Jingni
Xia, Xiaomeng
Hu, Ye
Fang, Xiaoling
Orsulic, Sandra
Identification of Infertility-Associated Topologically Important Genes Using Weighted Co-expression Network Analysis
title Identification of Infertility-Associated Topologically Important Genes Using Weighted Co-expression Network Analysis
title_full Identification of Infertility-Associated Topologically Important Genes Using Weighted Co-expression Network Analysis
title_fullStr Identification of Infertility-Associated Topologically Important Genes Using Weighted Co-expression Network Analysis
title_full_unstemmed Identification of Infertility-Associated Topologically Important Genes Using Weighted Co-expression Network Analysis
title_short Identification of Infertility-Associated Topologically Important Genes Using Weighted Co-expression Network Analysis
title_sort identification of infertility-associated topologically important genes using weighted co-expression network analysis
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7887323/
https://www.ncbi.nlm.nih.gov/pubmed/33613630
http://dx.doi.org/10.3389/fgene.2021.580190
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