Integrated analysis of competing endogenous RNA networks in peripheral blood mononuclear cells of systemic lupus erythematosus
Background Systemic lupus erythematosus (SLE) is an autoimmune disease with a complicated pathogenesis, and its aetiology has not been clearly unveiled. The lack of effective diagnosis and treatment methods makes it necessary to explore the molecular mechanism of SLE. We aimed to identify some criti...
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Published in | Journal of translational medicine Vol. 19; no. 1; pp. 1 - 15 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
London
BioMed Central
21.08.2021
BioMed Central Ltd BMC |
Subjects | |
Online Access | Get full text |
ISSN | 1479-5876 1479-5876 |
DOI | 10.1186/s12967-021-03033-8 |
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Abstract | Background
Systemic lupus erythematosus (SLE) is an autoimmune disease with a complicated pathogenesis, and its aetiology has not been clearly unveiled. The lack of effective diagnosis and treatment methods makes it necessary to explore the molecular mechanism of SLE. We aimed to identify some critical signalling pathways and key competing endogenous RNAs (ceRNAs) underlying the molecular mechanism of SLE and to map out the systematic signalling networks by integrating the data on different kinds of RNAs.
Methods
Peripheral blood mononuclear cells (PBMCs) were collected from both SLE patients and healthy subjects, RNA was extracted from the PBMCs, and RNA libraries including ribosomal RNA-depleted strand-specific libraries and small RNA libraries were built for deep RNA sequencing (RNA-seq). RNA-seq yielded differential expression profiles of lncRNAs/circRNAs/miRNAs/mRNAs related to SLE. The DAVID database (v. 6.8) was employed for Gene Ontology (GO) and KEGG pathway analysis. ceRNA networks (circRNA/lncRNA-miRNA-mRNA) were constructed and visualized using Cytoscape software (v. 3.5.0). The TargetScan and miRanda databases were used to predict target relationships in ceRNA networks. qRT-PCR was used to verify our data.
Results
Differential expression of ceRNAs related to SLE was detected in SLE patients’ PBMCs: 644 mRNAs (384 upregulated, 260 downregulated), 326 miRNAs (223 upregulated, 103 downregulated), 221 lncRNAs (79 upregulated, 142 downregulated), and 31 circRNAs (21 upregulated, 10 downregulated). We drew ceRNA signalling networks made up of the differentially expressed mRNAs/miRNAs/lncRNAs/circRNAs mentioned above, and the hub genes included IRF5, IFNAR2, TLR7, IRAK4, STAT1, STAT2, C2, and Tyk2. These hub genes were involved in ceRNA signalling pathways, such as the IL-17 signalling pathway and type I interferon signalling pathway.
Conclusions
We explored the differential expression profiles of various kinds of ceRNAs and integrated signalling networks constructed by ceRNAs. Our findings offer new insights into the pathogenesis of SLE and hint at therapeutic strategies. |
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AbstractList | Background Systemic lupus erythematosus (SLE) is an autoimmune disease with a complicated pathogenesis, and its aetiology has not been clearly unveiled. The lack of effective diagnosis and treatment methods makes it necessary to explore the molecular mechanism of SLE. We aimed to identify some critical signalling pathways and key competing endogenous RNAs (ceRNAs) underlying the molecular mechanism of SLE and to map out the systematic signalling networks by integrating the data on different kinds of RNAs. Methods Peripheral blood mononuclear cells (PBMCs) were collected from both SLE patients and healthy subjects, RNA was extracted from the PBMCs, and RNA libraries including ribosomal RNA-depleted strand-specific libraries and small RNA libraries were built for deep RNA sequencing (RNA-seq). RNA-seq yielded differential expression profiles of lncRNAs/circRNAs/miRNAs/mRNAs related to SLE. The DAVID database (v. 6.8) was employed for Gene Ontology (GO) and KEGG pathway analysis. ceRNA networks (circRNA/lncRNA-miRNA-mRNA) were constructed and visualized using Cytoscape software (v. 3.5.0). The TargetScan and miRanda databases were used to predict target relationships in ceRNA networks. qRT-PCR was used to verify our data. Results Differential expression of ceRNAs related to SLE was detected in SLE patients’ PBMCs: 644 mRNAs (384 upregulated, 260 downregulated), 326 miRNAs (223 upregulated, 103 downregulated), 221 lncRNAs (79 upregulated, 142 downregulated), and 31 circRNAs (21 upregulated, 10 downregulated). We drew ceRNA signalling networks made up of the differentially expressed mRNAs/miRNAs/lncRNAs/circRNAs mentioned above, and the hub genes included IRF5, IFNAR2, TLR7, IRAK4, STAT1, STAT2, C2, and Tyk2. These hub genes were involved in ceRNA signalling pathways, such as the IL-17 signalling pathway and type I interferon signalling pathway. Conclusions We explored the differential expression profiles of various kinds of ceRNAs and integrated signalling networks constructed by ceRNAs. Our findings offer new insights into the pathogenesis of SLE and hint at therapeutic strategies. Background Systemic lupus erythematosus (SLE) is an autoimmune disease with a complicated pathogenesis, and its aetiology has not been clearly unveiled. The lack of effective diagnosis and treatment methods makes it necessary to explore the molecular mechanism of SLE. We aimed to identify some critical signalling pathways and key competing endogenous RNAs (ceRNAs) underlying the molecular mechanism of SLE and to map out the systematic signalling networks by integrating the data on different kinds of RNAs. Methods Peripheral blood mononuclear cells (PBMCs) were collected from both SLE patients and healthy subjects, RNA was extracted from the PBMCs, and RNA libraries including ribosomal RNA-depleted strand-specific libraries and small RNA libraries were built for deep RNA sequencing (RNA-seq). RNA-seq yielded differential expression profiles of lncRNAs/circRNAs/miRNAs/mRNAs related to SLE. The DAVID database (v. 6.8) was employed for Gene Ontology (GO) and KEGG pathway analysis. ceRNA networks (circRNA/lncRNA-miRNA-mRNA) were constructed and visualized using Cytoscape software (v. 3.5.0). The TargetScan and miRanda databases were used to predict target relationships in ceRNA networks. qRT-PCR was used to verify our data. Results Differential expression of ceRNAs related to SLE was detected in SLE patients’ PBMCs: 644 mRNAs (384 upregulated, 260 downregulated), 326 miRNAs (223 upregulated, 103 downregulated), 221 lncRNAs (79 upregulated, 142 downregulated), and 31 circRNAs (21 upregulated, 10 downregulated). We drew ceRNA signalling networks made up of the differentially expressed mRNAs/miRNAs/lncRNAs/circRNAs mentioned above, and the hub genes included IRF5, IFNAR2, TLR7, IRAK4, STAT1, STAT2, C2, and Tyk2. These hub genes were involved in ceRNA signalling pathways, such as the IL-17 signalling pathway and type I interferon signalling pathway. Conclusions We explored the differential expression profiles of various kinds of ceRNAs and integrated signalling networks constructed by ceRNAs. Our findings offer new insights into the pathogenesis of SLE and hint at therapeutic strategies. Abstract Background Systemic lupus erythematosus (SLE) is an autoimmune disease with a complicated pathogenesis, and its aetiology has not been clearly unveiled. The lack of effective diagnosis and treatment methods makes it necessary to explore the molecular mechanism of SLE. We aimed to identify some critical signalling pathways and key competing endogenous RNAs (ceRNAs) underlying the molecular mechanism of SLE and to map out the systematic signalling networks by integrating the data on different kinds of RNAs. Methods Peripheral blood mononuclear cells (PBMCs) were collected from both SLE patients and healthy subjects, RNA was extracted from the PBMCs, and RNA libraries including ribosomal RNA-depleted strand-specific libraries and small RNA libraries were built for deep RNA sequencing (RNA-seq). RNA-seq yielded differential expression profiles of lncRNAs/circRNAs/miRNAs/mRNAs related to SLE. The DAVID database (v. 6.8) was employed for Gene Ontology (GO) and KEGG pathway analysis. ceRNA networks (circRNA/lncRNA-miRNA-mRNA) were constructed and visualized using Cytoscape software (v. 3.5.0). The TargetScan and miRanda databases were used to predict target relationships in ceRNA networks. qRT-PCR was used to verify our data. Results Differential expression of ceRNAs related to SLE was detected in SLE patients’ PBMCs: 644 mRNAs (384 upregulated, 260 downregulated), 326 miRNAs (223 upregulated, 103 downregulated), 221 lncRNAs (79 upregulated, 142 downregulated), and 31 circRNAs (21 upregulated, 10 downregulated). We drew ceRNA signalling networks made up of the differentially expressed mRNAs/miRNAs/lncRNAs/circRNAs mentioned above, and the hub genes included IRF5, IFNAR2, TLR7, IRAK4, STAT1, STAT2, C2, and Tyk2. These hub genes were involved in ceRNA signalling pathways, such as the IL-17 signalling pathway and type I interferon signalling pathway. Conclusions We explored the differential expression profiles of various kinds of ceRNAs and integrated signalling networks constructed by ceRNAs. Our findings offer new insights into the pathogenesis of SLE and hint at therapeutic strategies. Systemic lupus erythematosus (SLE) is an autoimmune disease with a complicated pathogenesis, and its aetiology has not been clearly unveiled. The lack of effective diagnosis and treatment methods makes it necessary to explore the molecular mechanism of SLE. We aimed to identify some critical signalling pathways and key competing endogenous RNAs (ceRNAs) underlying the molecular mechanism of SLE and to map out the systematic signalling networks by integrating the data on different kinds of RNAs.BACKGROUNDSystemic lupus erythematosus (SLE) is an autoimmune disease with a complicated pathogenesis, and its aetiology has not been clearly unveiled. The lack of effective diagnosis and treatment methods makes it necessary to explore the molecular mechanism of SLE. We aimed to identify some critical signalling pathways and key competing endogenous RNAs (ceRNAs) underlying the molecular mechanism of SLE and to map out the systematic signalling networks by integrating the data on different kinds of RNAs.Peripheral blood mononuclear cells (PBMCs) were collected from both SLE patients and healthy subjects, RNA was extracted from the PBMCs, and RNA libraries including ribosomal RNA-depleted strand-specific libraries and small RNA libraries were built for deep RNA sequencing (RNA-seq). RNA-seq yielded differential expression profiles of lncRNAs/circRNAs/miRNAs/mRNAs related to SLE. The DAVID database (v. 6.8) was employed for Gene Ontology (GO) and KEGG pathway analysis. ceRNA networks (circRNA/lncRNA-miRNA-mRNA) were constructed and visualized using Cytoscape software (v. 3.5.0). The TargetScan and miRanda databases were used to predict target relationships in ceRNA networks. qRT-PCR was used to verify our data.METHODSPeripheral blood mononuclear cells (PBMCs) were collected from both SLE patients and healthy subjects, RNA was extracted from the PBMCs, and RNA libraries including ribosomal RNA-depleted strand-specific libraries and small RNA libraries were built for deep RNA sequencing (RNA-seq). RNA-seq yielded differential expression profiles of lncRNAs/circRNAs/miRNAs/mRNAs related to SLE. The DAVID database (v. 6.8) was employed for Gene Ontology (GO) and KEGG pathway analysis. ceRNA networks (circRNA/lncRNA-miRNA-mRNA) were constructed and visualized using Cytoscape software (v. 3.5.0). The TargetScan and miRanda databases were used to predict target relationships in ceRNA networks. qRT-PCR was used to verify our data.Differential expression of ceRNAs related to SLE was detected in SLE patients' PBMCs: 644 mRNAs (384 upregulated, 260 downregulated), 326 miRNAs (223 upregulated, 103 downregulated), 221 lncRNAs (79 upregulated, 142 downregulated), and 31 circRNAs (21 upregulated, 10 downregulated). We drew ceRNA signalling networks made up of the differentially expressed mRNAs/miRNAs/lncRNAs/circRNAs mentioned above, and the hub genes included IRF5, IFNAR2, TLR7, IRAK4, STAT1, STAT2, C2, and Tyk2. These hub genes were involved in ceRNA signalling pathways, such as the IL-17 signalling pathway and type I interferon signalling pathway.RESULTSDifferential expression of ceRNAs related to SLE was detected in SLE patients' PBMCs: 644 mRNAs (384 upregulated, 260 downregulated), 326 miRNAs (223 upregulated, 103 downregulated), 221 lncRNAs (79 upregulated, 142 downregulated), and 31 circRNAs (21 upregulated, 10 downregulated). We drew ceRNA signalling networks made up of the differentially expressed mRNAs/miRNAs/lncRNAs/circRNAs mentioned above, and the hub genes included IRF5, IFNAR2, TLR7, IRAK4, STAT1, STAT2, C2, and Tyk2. These hub genes were involved in ceRNA signalling pathways, such as the IL-17 signalling pathway and type I interferon signalling pathway.We explored the differential expression profiles of various kinds of ceRNAs and integrated signalling networks constructed by ceRNAs. Our findings offer new insights into the pathogenesis of SLE and hint at therapeutic strategies.CONCLUSIONSWe explored the differential expression profiles of various kinds of ceRNAs and integrated signalling networks constructed by ceRNAs. Our findings offer new insights into the pathogenesis of SLE and hint at therapeutic strategies. Systemic lupus erythematosus (SLE) is an autoimmune disease with a complicated pathogenesis, and its aetiology has not been clearly unveiled. The lack of effective diagnosis and treatment methods makes it necessary to explore the molecular mechanism of SLE. We aimed to identify some critical signalling pathways and key competing endogenous RNAs (ceRNAs) underlying the molecular mechanism of SLE and to map out the systematic signalling networks by integrating the data on different kinds of RNAs. Peripheral blood mononuclear cells (PBMCs) were collected from both SLE patients and healthy subjects, RNA was extracted from the PBMCs, and RNA libraries including ribosomal RNA-depleted strand-specific libraries and small RNA libraries were built for deep RNA sequencing (RNA-seq). RNA-seq yielded differential expression profiles of lncRNAs/circRNAs/miRNAs/mRNAs related to SLE. The DAVID database (v. 6.8) was employed for Gene Ontology (GO) and KEGG pathway analysis. ceRNA networks (circRNA/lncRNA-miRNA-mRNA) were constructed and visualized using Cytoscape software (v. 3.5.0). The TargetScan and miRanda databases were used to predict target relationships in ceRNA networks. qRT-PCR was used to verify our data. Differential expression of ceRNAs related to SLE was detected in SLE patients' PBMCs: 644 mRNAs (384 upregulated, 260 downregulated), 326 miRNAs (223 upregulated, 103 downregulated), 221 lncRNAs (79 upregulated, 142 downregulated), and 31 circRNAs (21 upregulated, 10 downregulated). We drew ceRNA signalling networks made up of the differentially expressed mRNAs/miRNAs/lncRNAs/circRNAs mentioned above, and the hub genes included IRF5, IFNAR2, TLR7, IRAK4, STAT1, STAT2, C2, and Tyk2. These hub genes were involved in ceRNA signalling pathways, such as the IL-17 signalling pathway and type I interferon signalling pathway. We explored the differential expression profiles of various kinds of ceRNAs and integrated signalling networks constructed by ceRNAs. Our findings offer new insights into the pathogenesis of SLE and hint at therapeutic strategies. Background Systemic lupus erythematosus (SLE) is an autoimmune disease with a complicated pathogenesis, and its aetiology has not been clearly unveiled. The lack of effective diagnosis and treatment methods makes it necessary to explore the molecular mechanism of SLE. We aimed to identify some critical signalling pathways and key competing endogenous RNAs (ceRNAs) underlying the molecular mechanism of SLE and to map out the systematic signalling networks by integrating the data on different kinds of RNAs. Methods Peripheral blood mononuclear cells (PBMCs) were collected from both SLE patients and healthy subjects, RNA was extracted from the PBMCs, and RNA libraries including ribosomal RNA-depleted strand-specific libraries and small RNA libraries were built for deep RNA sequencing (RNA-seq). RNA-seq yielded differential expression profiles of lncRNAs/circRNAs/miRNAs/mRNAs related to SLE. The DAVID database (v. 6.8) was employed for Gene Ontology (GO) and KEGG pathway analysis. ceRNA networks (circRNA/lncRNA-miRNA-mRNA) were constructed and visualized using Cytoscape software (v. 3.5.0). The TargetScan and miRanda databases were used to predict target relationships in ceRNA networks. qRT-PCR was used to verify our data. Results Differential expression of ceRNAs related to SLE was detected in SLE patients' PBMCs: 644 mRNAs (384 upregulated, 260 downregulated), 326 miRNAs (223 upregulated, 103 downregulated), 221 lncRNAs (79 upregulated, 142 downregulated), and 31 circRNAs (21 upregulated, 10 downregulated). We drew ceRNA signalling networks made up of the differentially expressed mRNAs/miRNAs/lncRNAs/circRNAs mentioned above, and the hub genes included IRF5, IFNAR2, TLR7, IRAK4, STAT1, STAT2, C2, and Tyk2. These hub genes were involved in ceRNA signalling pathways, such as the IL-17 signalling pathway and type I interferon signalling pathway. Conclusions We explored the differential expression profiles of various kinds of ceRNAs and integrated signalling networks constructed by ceRNAs. Our findings offer new insights into the pathogenesis of SLE and hint at therapeutic strategies. Keywords: ceRNAs, Integrative analysis, SLE, RNA sequencing |
ArticleNumber | 362 |
Audience | Academic |
Author | Qiu, Jie Hong, Xiaoping Liu, Dongzhou Tang, Donge Dai, Weier Song, Wencong Yin, Lianghong Dai, Yong |
Author_xml | – sequence: 1 givenname: Wencong surname: Song fullname: Song, Wencong organization: Department of Clinical Medical Research Center, Guangdong Provincial Engineering Research Center of Autoimmune Disease Precision Medicine, Shenzhen Engineering Research Center of Autoimmune Disease, The Second Clinical Medical College, Jinan University (Shenzhen Peoples Hospital), The First Affiliated Hospital, Jinan University – sequence: 2 givenname: Jie surname: Qiu fullname: Qiu, Jie organization: School of Computer Science and Engineering, Yulin Normal University – sequence: 3 givenname: Lianghong surname: Yin fullname: Yin, Lianghong organization: The First Affiliated Hospital, Jinan University – sequence: 4 givenname: Xiaoping surname: Hong fullname: Hong, Xiaoping organization: Department of Clinical Medical Research Center, Guangdong Provincial Engineering Research Center of Autoimmune Disease Precision Medicine, Shenzhen Engineering Research Center of Autoimmune Disease, The Second Clinical Medical College, Jinan University (Shenzhen Peoples Hospital) – sequence: 5 givenname: Weier surname: Dai fullname: Dai, Weier organization: College of Natural Science, University of Texas at Austin – sequence: 6 givenname: Donge surname: Tang fullname: Tang, Donge email: donge66@126.com organization: Department of Clinical Medical Research Center, Guangdong Provincial Engineering Research Center of Autoimmune Disease Precision Medicine, Shenzhen Engineering Research Center of Autoimmune Disease, The Second Clinical Medical College, Jinan University (Shenzhen Peoples Hospital), Guangxi Key Laboratory of Metabolic Disease Research, Central Laboratory of Guilin NO. 924 Hospital – sequence: 7 givenname: Dongzhou surname: Liu fullname: Liu, Dongzhou email: liu_dz2001@sina.com organization: Department of Clinical Medical Research Center, Guangdong Provincial Engineering Research Center of Autoimmune Disease Precision Medicine, Shenzhen Engineering Research Center of Autoimmune Disease, The Second Clinical Medical College, Jinan University (Shenzhen Peoples Hospital) – sequence: 8 givenname: Yong orcidid: 0000-0002-6840-9158 surname: Dai fullname: Dai, Yong email: daiyong22@aliyun.com organization: Department of Clinical Medical Research Center, Guangdong Provincial Engineering Research Center of Autoimmune Disease Precision Medicine, Shenzhen Engineering Research Center of Autoimmune Disease, The Second Clinical Medical College, Jinan University (Shenzhen Peoples Hospital), Guangxi Key Laboratory of Metabolic Disease Research, Central Laboratory of Guilin NO. 924 Hospital |
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Keywords | Integrative analysis RNA sequencing ceRNAs SLE |
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Systemic lupus erythematosus (SLE) is an autoimmune disease with a complicated pathogenesis, and its aetiology has not been clearly unveiled. The... Background Systemic lupus erythematosus (SLE) is an autoimmune disease with a complicated pathogenesis, and its aetiology has not been clearly unveiled. The... Systemic lupus erythematosus (SLE) is an autoimmune disease with a complicated pathogenesis, and its aetiology has not been clearly unveiled. The lack of... Abstract Background Systemic lupus erythematosus (SLE) is an autoimmune disease with a complicated pathogenesis, and its aetiology has not been clearly... |
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SubjectTerms | Autoimmune diseases Biomedical and Life Sciences Biomedicine ceRNAs Development and progression Disease Genetic aspects Genomes Health aspects Immunobiology and immunotherapy Integrative analysis Interferon Interleukin 17 Kinases Leukocytes (mononuclear) Lupus Lymphocytes Medical diagnosis Medicine/Public Health MicroRNAs miRNA Monocytes mRNA Pathogenesis Patients Peripheral blood mononuclear cells Physiological aspects RNA RNA sequencing rRNA Signal transduction SLE Stat1 protein Stat2 protein Systemic lupus erythematosus TLR7 protein Toll-like receptors Tyk2 protein |
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Title | Integrated analysis of competing endogenous RNA networks in peripheral blood mononuclear cells of systemic lupus erythematosus |
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