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Integrative analysis of the expression profiles of whole coding and non-coding RNA transcriptomes and construction of the competing endogenous RNA networks for chronic obstructive pulmonary disease

The pathogenesis of Chronic Obstructive Pulmonary Disease (COPD) is implicated in airway inflammation, oxidative stress, protease/anti-protease and emphysema. Abnormally expressed non-coding RNAs (ncRNAs) play a vital role in regulation of COPD occurrence and progression. The regulatory mechanisms o...

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Autores principales: Feng, Xueyan, Dong, Hui, Li, Beibei, Yu, Liang, Zhu, Jinyuan, Lou, Caili, Zhang, Jin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9923003/
https://www.ncbi.nlm.nih.gov/pubmed/36793900
http://dx.doi.org/10.3389/fgene.2023.1050783
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author Feng, Xueyan
Dong, Hui
Li, Beibei
Yu, Liang
Zhu, Jinyuan
Lou, Caili
Zhang, Jin
author_facet Feng, Xueyan
Dong, Hui
Li, Beibei
Yu, Liang
Zhu, Jinyuan
Lou, Caili
Zhang, Jin
author_sort Feng, Xueyan
collection PubMed
description The pathogenesis of Chronic Obstructive Pulmonary Disease (COPD) is implicated in airway inflammation, oxidative stress, protease/anti-protease and emphysema. Abnormally expressed non-coding RNAs (ncRNAs) play a vital role in regulation of COPD occurrence and progression. The regulatory mechanisms of the circRNA/lncRNA-miRNA-mRNA (competing endogenous RNA, ceRNA) networks might facilitate our cognition of RNA interactions in COPD. This study aimed to identified novel RNA transcripts and constructed the potential ceRNA networks of COPD patients. Total transcriptome sequencing of the tissues from patients with COPD (COPD) (n = 7) and non-COPD control subjects (Normal) (n = 6) was performed, and the expression profiles of differentially expressed genes (DEGs), including mRNAs, lncRNAs, circRNAs, and miRNAs, were analyzed. The ceRNA network was established based on the miRcode and miRanda databases. Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), Gene Set Enrichment Analysis (GSEA), and Gene set variation analysis (GSVA) were implemented for functional enrichment analysis of DEGs. Finally, CIBERSORTx was extracted to analyze the relevance between hub genes and various immune cells.The Starbase and JASPAR databases were used to construct hub-RNA binding proteins (RBPs) and lncRNA-transcription factor (TF) interaction networks. A total of 1,796 mRNAs, 2,207 lncRNAs, and 11 miRNAs showed differentially expression between the lung tissue samples from the normal and COPD groups. Based on these DEGs, lncRNA/circRNA-miRNA-mRNA ceRNA networks were constructed respectively. In addition, ten hub genes were identified. Among them, RPS11, RPL32, RPL5, and RPL27A were associated with the proliferation, differentiation, and apoptosis of the lung tissue. The biological function revealed that TNF–α via NF–kB and IL6/JAK/STAT3 signaling pathways were involved in COPD. Our research constructed the lncRNA/circRNA-miRNA-mRNA ceRNA networks, filtrated ten hub genes may regulate the TNF-α/NF-κB, IL6/JAK/STAT3 signally pathways, which indirectly elucidated the post-transcriptional regulation mechanism of COPD and lay the foundation for excavating the novel targets of diagnosis and treatment in COPD.
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spelling pubmed-99230032023-02-14 Integrative analysis of the expression profiles of whole coding and non-coding RNA transcriptomes and construction of the competing endogenous RNA networks for chronic obstructive pulmonary disease Feng, Xueyan Dong, Hui Li, Beibei Yu, Liang Zhu, Jinyuan Lou, Caili Zhang, Jin Front Genet Genetics The pathogenesis of Chronic Obstructive Pulmonary Disease (COPD) is implicated in airway inflammation, oxidative stress, protease/anti-protease and emphysema. Abnormally expressed non-coding RNAs (ncRNAs) play a vital role in regulation of COPD occurrence and progression. The regulatory mechanisms of the circRNA/lncRNA-miRNA-mRNA (competing endogenous RNA, ceRNA) networks might facilitate our cognition of RNA interactions in COPD. This study aimed to identified novel RNA transcripts and constructed the potential ceRNA networks of COPD patients. Total transcriptome sequencing of the tissues from patients with COPD (COPD) (n = 7) and non-COPD control subjects (Normal) (n = 6) was performed, and the expression profiles of differentially expressed genes (DEGs), including mRNAs, lncRNAs, circRNAs, and miRNAs, were analyzed. The ceRNA network was established based on the miRcode and miRanda databases. Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), Gene Set Enrichment Analysis (GSEA), and Gene set variation analysis (GSVA) were implemented for functional enrichment analysis of DEGs. Finally, CIBERSORTx was extracted to analyze the relevance between hub genes and various immune cells.The Starbase and JASPAR databases were used to construct hub-RNA binding proteins (RBPs) and lncRNA-transcription factor (TF) interaction networks. A total of 1,796 mRNAs, 2,207 lncRNAs, and 11 miRNAs showed differentially expression between the lung tissue samples from the normal and COPD groups. Based on these DEGs, lncRNA/circRNA-miRNA-mRNA ceRNA networks were constructed respectively. In addition, ten hub genes were identified. Among them, RPS11, RPL32, RPL5, and RPL27A were associated with the proliferation, differentiation, and apoptosis of the lung tissue. The biological function revealed that TNF–α via NF–kB and IL6/JAK/STAT3 signaling pathways were involved in COPD. Our research constructed the lncRNA/circRNA-miRNA-mRNA ceRNA networks, filtrated ten hub genes may regulate the TNF-α/NF-κB, IL6/JAK/STAT3 signally pathways, which indirectly elucidated the post-transcriptional regulation mechanism of COPD and lay the foundation for excavating the novel targets of diagnosis and treatment in COPD. Frontiers Media S.A. 2023-01-30 /pmc/articles/PMC9923003/ /pubmed/36793900 http://dx.doi.org/10.3389/fgene.2023.1050783 Text en Copyright © 2023 Feng, Dong, Li, Yu, Zhu, Lou and Zhang. https://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
Feng, Xueyan
Dong, Hui
Li, Beibei
Yu, Liang
Zhu, Jinyuan
Lou, Caili
Zhang, Jin
Integrative analysis of the expression profiles of whole coding and non-coding RNA transcriptomes and construction of the competing endogenous RNA networks for chronic obstructive pulmonary disease
title Integrative analysis of the expression profiles of whole coding and non-coding RNA transcriptomes and construction of the competing endogenous RNA networks for chronic obstructive pulmonary disease
title_full Integrative analysis of the expression profiles of whole coding and non-coding RNA transcriptomes and construction of the competing endogenous RNA networks for chronic obstructive pulmonary disease
title_fullStr Integrative analysis of the expression profiles of whole coding and non-coding RNA transcriptomes and construction of the competing endogenous RNA networks for chronic obstructive pulmonary disease
title_full_unstemmed Integrative analysis of the expression profiles of whole coding and non-coding RNA transcriptomes and construction of the competing endogenous RNA networks for chronic obstructive pulmonary disease
title_short Integrative analysis of the expression profiles of whole coding and non-coding RNA transcriptomes and construction of the competing endogenous RNA networks for chronic obstructive pulmonary disease
title_sort integrative analysis of the expression profiles of whole coding and non-coding rna transcriptomes and construction of the competing endogenous rna networks for chronic obstructive pulmonary disease
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9923003/
https://www.ncbi.nlm.nih.gov/pubmed/36793900
http://dx.doi.org/10.3389/fgene.2023.1050783
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