Cargando…
Identification of key lncRNAs contributing to diabetic nephropathy by gene co-expression network analysis
LncRNA is reported to have important role in diabetic nephropathy (DN). Here, we aim to identify key lncRNAs of DN using bioinformatics and systems biological methods. Method: Five microarray data sets from Gene Expression Omnibus (GEO) database were included. Probe sets were re-annotated. In the tr...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6397236/ https://www.ncbi.nlm.nih.gov/pubmed/30824724 http://dx.doi.org/10.1038/s41598-019-39298-9 |
_version_ | 1783399388583821312 |
---|---|
author | Shang, Jin Wang, Shuai Jiang, Yumin Duan, Yiqi Cheng, Genyang Liu, Dong Xiao, Jing Zhao, Zhanzheng |
author_facet | Shang, Jin Wang, Shuai Jiang, Yumin Duan, Yiqi Cheng, Genyang Liu, Dong Xiao, Jing Zhao, Zhanzheng |
author_sort | Shang, Jin |
collection | PubMed |
description | LncRNA is reported to have important role in diabetic nephropathy (DN). Here, we aim to identify key lncRNAs of DN using bioinformatics and systems biological methods. Method: Five microarray data sets from Gene Expression Omnibus (GEO) database were included. Probe sets were re-annotated. In the training set, differential expressed genes (DEGs) were identified. Weighted gene co-expression network analysis (WGCNA) was constructed to screen diabetic-related hub genes and reveal their potential biological function. Two more human data sets and mouse data sets were used as validation sets. Results: A total of 424 DEGs, including 10 lncRNAs, were filtered in the training data set. WGCNA and enrichment analysis of hub genes showed that inflammation and metabolic disorders are prominent in DN. Three key lncRNAs (NR_130134.1, NR_029395.1 and NR_038335.1) were identified. These lncRNAs are also differently expressed in another two human data sets. Functional enrichment of the mouse data sets showed consistent changes with that in human, indicating similar changes in gene expression pattern of DN and confirmed confidence of our analysis. Human podocytes and mesangial cells were culture in vitro. QPCR and fluorescence in situ hybridization were taken out to validate the expression and relationship of key lncRNAs and their related mRNAs. Results were also consistent with our analysis. Conclusions: Inflammation and metabolic disorders are prominent in DN. We identify three lncRNAs that are involved in these processes possibly by interacting with co-expressed mRNAs. |
format | Online Article Text |
id | pubmed-6397236 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-63972362019-03-05 Identification of key lncRNAs contributing to diabetic nephropathy by gene co-expression network analysis Shang, Jin Wang, Shuai Jiang, Yumin Duan, Yiqi Cheng, Genyang Liu, Dong Xiao, Jing Zhao, Zhanzheng Sci Rep Article LncRNA is reported to have important role in diabetic nephropathy (DN). Here, we aim to identify key lncRNAs of DN using bioinformatics and systems biological methods. Method: Five microarray data sets from Gene Expression Omnibus (GEO) database were included. Probe sets were re-annotated. In the training set, differential expressed genes (DEGs) were identified. Weighted gene co-expression network analysis (WGCNA) was constructed to screen diabetic-related hub genes and reveal their potential biological function. Two more human data sets and mouse data sets were used as validation sets. Results: A total of 424 DEGs, including 10 lncRNAs, were filtered in the training data set. WGCNA and enrichment analysis of hub genes showed that inflammation and metabolic disorders are prominent in DN. Three key lncRNAs (NR_130134.1, NR_029395.1 and NR_038335.1) were identified. These lncRNAs are also differently expressed in another two human data sets. Functional enrichment of the mouse data sets showed consistent changes with that in human, indicating similar changes in gene expression pattern of DN and confirmed confidence of our analysis. Human podocytes and mesangial cells were culture in vitro. QPCR and fluorescence in situ hybridization were taken out to validate the expression and relationship of key lncRNAs and their related mRNAs. Results were also consistent with our analysis. Conclusions: Inflammation and metabolic disorders are prominent in DN. We identify three lncRNAs that are involved in these processes possibly by interacting with co-expressed mRNAs. Nature Publishing Group UK 2019-03-01 /pmc/articles/PMC6397236/ /pubmed/30824724 http://dx.doi.org/10.1038/s41598-019-39298-9 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Shang, Jin Wang, Shuai Jiang, Yumin Duan, Yiqi Cheng, Genyang Liu, Dong Xiao, Jing Zhao, Zhanzheng Identification of key lncRNAs contributing to diabetic nephropathy by gene co-expression network analysis |
title | Identification of key lncRNAs contributing to diabetic nephropathy by gene co-expression network analysis |
title_full | Identification of key lncRNAs contributing to diabetic nephropathy by gene co-expression network analysis |
title_fullStr | Identification of key lncRNAs contributing to diabetic nephropathy by gene co-expression network analysis |
title_full_unstemmed | Identification of key lncRNAs contributing to diabetic nephropathy by gene co-expression network analysis |
title_short | Identification of key lncRNAs contributing to diabetic nephropathy by gene co-expression network analysis |
title_sort | identification of key lncrnas contributing to diabetic nephropathy by gene co-expression network analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6397236/ https://www.ncbi.nlm.nih.gov/pubmed/30824724 http://dx.doi.org/10.1038/s41598-019-39298-9 |
work_keys_str_mv | AT shangjin identificationofkeylncrnascontributingtodiabeticnephropathybygenecoexpressionnetworkanalysis AT wangshuai identificationofkeylncrnascontributingtodiabeticnephropathybygenecoexpressionnetworkanalysis AT jiangyumin identificationofkeylncrnascontributingtodiabeticnephropathybygenecoexpressionnetworkanalysis AT duanyiqi identificationofkeylncrnascontributingtodiabeticnephropathybygenecoexpressionnetworkanalysis AT chenggenyang identificationofkeylncrnascontributingtodiabeticnephropathybygenecoexpressionnetworkanalysis AT liudong identificationofkeylncrnascontributingtodiabeticnephropathybygenecoexpressionnetworkanalysis AT xiaojing identificationofkeylncrnascontributingtodiabeticnephropathybygenecoexpressionnetworkanalysis AT zhaozhanzheng identificationofkeylncrnascontributingtodiabeticnephropathybygenecoexpressionnetworkanalysis |