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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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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. |
format | Online Article Text |
id | pubmed-7887323 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
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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