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Identification of Key circRNAs/lncRNAs/miRNAs/mRNAs and Pathways in Preeclampsia Using Bioinformatics Analysis

BACKGROUND: This study aimed to identify significantly altered circRNAs/lncRNAs/miRNAs/mRNAs pathways in preeclampsia (PE), investigate their target relationships, and determine their biological functions. MATERIAL/METHODS: Base on RNA-seq technique and the GEO database, expression profiles of circR...

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Autores principales: Liu, Siwei, Xie, Xie, Lei, Huajiang, Zou, Bingyu, Xie, Lan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Scientific Literature, Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6413561/
https://www.ncbi.nlm.nih.gov/pubmed/30833538
http://dx.doi.org/10.12659/MSM.912801
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author Liu, Siwei
Xie, Xie
Lei, Huajiang
Zou, Bingyu
Xie, Lan
author_facet Liu, Siwei
Xie, Xie
Lei, Huajiang
Zou, Bingyu
Xie, Lan
author_sort Liu, Siwei
collection PubMed
description BACKGROUND: This study aimed to identify significantly altered circRNAs/lncRNAs/miRNAs/mRNAs pathways in preeclampsia (PE), investigate their target relationships, and determine their biological functions. MATERIAL/METHODS: Base on RNA-seq technique and the GEO database, expression profiles of circRNAs/lncRNAs/miRNAs/mRNAs related to PE were obtained. Differentially expressed RNAs were determined using the Limma package in R. Gene set enrichment analysis (GSEA) was performed using GSEA software (v. 3.0) and illustrated by ClusterProfiler and ggplot2 package in R. DAVID database (v. 6.8) was implemented to analyze functional categories and the association between genes and the corresponding Gene Ontology (GO) classification. The R visualization package GOPlot was used to get a better visualization of the relationships between genes and the selected functional categories. CeRNA networks which visualized the correlations between circRNA/lncRNA-miRNA-mRNA were constructed using Cytoscape software (v. 3.6.0). Targetscan and miRanda database were used to predict target relationships between circRNA/lncRNA-miRNA-mRNA. QRT-PCR and luciferase reporter assay were used to verify the expression and target relationship of has_circ_0088196/LINC01492/miR-100-5p/LIF (leukemia inhibitory factor). RESULTS: The jak-stat signaling pathway was activated and miR-100-5p was downregulated in PE compared with normal tissues both in collected placental tissue samples and GEO database. Upregulated LIF, LINC01492, and hsa_circ_0088196 were negatively correlated with miR-100-5p expression and had a targeted relationship with miR-100-5p. CONCLUSIONS: miR-100-5p may suppress PE development, while LIF, LINC01492, and hsa_circ_0088196 may promote it though inhibiting miR-100-5p. The jak-stat signaling pathway was activated and involved in PE progression.
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spelling pubmed-64135612019-04-09 Identification of Key circRNAs/lncRNAs/miRNAs/mRNAs and Pathways in Preeclampsia Using Bioinformatics Analysis Liu, Siwei Xie, Xie Lei, Huajiang Zou, Bingyu Xie, Lan Med Sci Monit Molecular Biology BACKGROUND: This study aimed to identify significantly altered circRNAs/lncRNAs/miRNAs/mRNAs pathways in preeclampsia (PE), investigate their target relationships, and determine their biological functions. MATERIAL/METHODS: Base on RNA-seq technique and the GEO database, expression profiles of circRNAs/lncRNAs/miRNAs/mRNAs related to PE were obtained. Differentially expressed RNAs were determined using the Limma package in R. Gene set enrichment analysis (GSEA) was performed using GSEA software (v. 3.0) and illustrated by ClusterProfiler and ggplot2 package in R. DAVID database (v. 6.8) was implemented to analyze functional categories and the association between genes and the corresponding Gene Ontology (GO) classification. The R visualization package GOPlot was used to get a better visualization of the relationships between genes and the selected functional categories. CeRNA networks which visualized the correlations between circRNA/lncRNA-miRNA-mRNA were constructed using Cytoscape software (v. 3.6.0). Targetscan and miRanda database were used to predict target relationships between circRNA/lncRNA-miRNA-mRNA. QRT-PCR and luciferase reporter assay were used to verify the expression and target relationship of has_circ_0088196/LINC01492/miR-100-5p/LIF (leukemia inhibitory factor). RESULTS: The jak-stat signaling pathway was activated and miR-100-5p was downregulated in PE compared with normal tissues both in collected placental tissue samples and GEO database. Upregulated LIF, LINC01492, and hsa_circ_0088196 were negatively correlated with miR-100-5p expression and had a targeted relationship with miR-100-5p. CONCLUSIONS: miR-100-5p may suppress PE development, while LIF, LINC01492, and hsa_circ_0088196 may promote it though inhibiting miR-100-5p. The jak-stat signaling pathway was activated and involved in PE progression. International Scientific Literature, Inc. 2019-03-05 /pmc/articles/PMC6413561/ /pubmed/30833538 http://dx.doi.org/10.12659/MSM.912801 Text en © Med Sci Monit, 2019 This work is licensed under Creative Common Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) )
spellingShingle Molecular Biology
Liu, Siwei
Xie, Xie
Lei, Huajiang
Zou, Bingyu
Xie, Lan
Identification of Key circRNAs/lncRNAs/miRNAs/mRNAs and Pathways in Preeclampsia Using Bioinformatics Analysis
title Identification of Key circRNAs/lncRNAs/miRNAs/mRNAs and Pathways in Preeclampsia Using Bioinformatics Analysis
title_full Identification of Key circRNAs/lncRNAs/miRNAs/mRNAs and Pathways in Preeclampsia Using Bioinformatics Analysis
title_fullStr Identification of Key circRNAs/lncRNAs/miRNAs/mRNAs and Pathways in Preeclampsia Using Bioinformatics Analysis
title_full_unstemmed Identification of Key circRNAs/lncRNAs/miRNAs/mRNAs and Pathways in Preeclampsia Using Bioinformatics Analysis
title_short Identification of Key circRNAs/lncRNAs/miRNAs/mRNAs and Pathways in Preeclampsia Using Bioinformatics Analysis
title_sort identification of key circrnas/lncrnas/mirnas/mrnas and pathways in preeclampsia using bioinformatics analysis
topic Molecular Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6413561/
https://www.ncbi.nlm.nih.gov/pubmed/30833538
http://dx.doi.org/10.12659/MSM.912801
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