Dataset Information

Identification of the key genes and long non?coding RNAs in ankylosing spondylitis using RNA sequencing.

ABSTRACT: Ankylosing spondylitis (AS) is an insidious and debilitating form of arthritis that involves the axial skeleton, and its etiology and pathogenesis remain unclear. In the present study, three patients with AS and three normal controls from our hospital were enrolled. RNA sequencing and bioinformatics analysis were performed in order to identify the differentially expressed (DE) mRNAs (DEmRNAs) and DE long non?coding RNAs (DElncRNAs) between the patients with AS and normal controls. Construction of an AS?specific protein?protein interaction network, a weighted DElncRNA?DEmRNA co?expression network and functional annotation of the DEmRNAs co?expressed with DElncRNAs was performed. Nearby cis?targeted DEmRNAs or DElncRNAs were identified by searching for DEmRNAs that were transcribed within 100?kb up? or downstream of DElncRNAs. Based on the Gene Expression Omnibus datasets GSE25101 and GSE73754, the expression of selected DEmRNAs and DElncRNAs were verified using published RNA sequencing data from blood samples, and receiver operating characteristic analysis of selected DEmRNAs was performed. Compared with the normal controls, 1,072 DEmRNAs and 372 DElncRNAs in the patients with AS were identified. Caspase recruitment domain family member 11 and DNA methyltransferase 1 have great diagnostic value for AS. MSTRG.8559 and LINC00987 were also identified as two hub DElncRNAs. The T?cell receptor signaling pathway was a significantly enriched pathway of the DEmRNAs co?expressed with DElncRNAs in patients with AS. In conclusion, the present study identified the key DEmRNAs and DElncRNAs in AS, which provides novel information for understanding the pathogenesis of AS and developing potential biomarkers for AS.

SUBMITTER: Xu Z

PROVIDER: S-EPMC6365023 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Identification of the key genes and long non‑coding RNAs in ankylosing spondylitis using RNA sequencing.

Xu Zhengkuan Z Li Hao H Chen Qixin Q Chen Gang G

International journal of molecular medicine 20181220 3

Ankylosing spondylitis (AS) is an insidious and debilitating form of arthritis that involves the axial skeleton, and its etiology and pathogenesis remain unclear. In the present study, three patients with AS and three normal controls from our hospital were enrolled. RNA sequencing and bioinformatics analysis were performed in order to identify the differentially expressed (DE) mRNAs (DEmRNAs) and DE long non‑coding RNAs (DElncRNAs) between the patients with AS and normal controls. Construction o ...[more]

PMID: 30592273

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Project description:Background:Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related deaths worldwide. Although multiple efforts have been made to understand the development of HCC, morbidity, and mortality rates remain high. In this study, we aimed to discover the mRNAs and long non-coding RNAs (lncRNAs) that contribute to the progression of HCC. We constructed a lncRNA-related competitive endogenous RNA (ceRNA) network to elucidate the molecular regulatory mechanism underlying HCC. Methods:A microarray dataset (GSE54238) containing information about both mRNAs and lncRNAs was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) and lncRNAs (DElncRNAs) in tumor tissues and non-cancerous tissues were identified using the limma package of the R software. The miRNAs that are targeted by DElncRNAs were predicted using miRcode, while the target mRNAs of miRNAs were retrieved from miRDB, miRTarBas, and TargetScan. Functional annotation and pathway enrichment of DEGs were performed using the EnrichNet website. We constructed a protein-protein interaction (PPI) network of DEGs using STRING, and identified the hub genes using Cytoscape. Survival analysis of the hub genes and DElncRNAs was performed using the gene expression profiling interactive analysis database. The expression of molecules with prognostic values was validated on the UALCAN database. The hepatic expression of hub genes was examined using the Human Protein Atlas. The hub genes and DElncRNAs with prognostic values as well as the predictive miRNAs were selected to construct the ceRNA networks. Results:We found that 10 hub genes (KPNA2, MCM7, CKS2, KIF23, HMGB2, ZWINT, E2F1, MCM4, H2AFX, and EZH2) and four lncRNAs (FAM182B, SNHG6, SNHG1, and SNHG3) with prognostic values were overexpressed in the hepatic tumor samples. We also constructed a network containing 10 lncRNA-miRNA-mRNA pathways, which might be responsible for regulating the biological mechanisms underlying HCC. Conclusion:We found that the 10 significantly overexpressed hub genes and four lncRNAs were negatively correlated with the prognosis of HCC. Further, we suggest that lncRNA SNHG1 and the SNHG3-related ceRNAs can be potential research targets for exploring the molecular mechanisms of HCC.

Project description:Background The precise pathogenesis of ankylosing spondylitis (AS) is still largely unknown at present. Our previous study found that toll-like receptor 4 (TLR4) downregulated and performed immunoregulatory dysfunction in mesenchymal stem cells from AS patients (AS-MSCs). The aim of this study was to explore the expression profiles of long non-coding RNAs (lncRNAs) and messenger RNAs (mRNAs) in TLR4-primed AS-MSCs, and to clarify the potential mechanisms. Methods The immunoregulatory effects of MSCs were determined after TLR4 activation. Next, the differentially-expressed (DE) lncRNAs and mRNAs between AS-MSCs and TLR4-primed AS-MSCs [stimulated by lipopolysaccharide (LPS)] were identified via high-throughput sequencing followed by quantitative real-time PCR (qRT-PCR) confirmation. Finally, bioinformatics analyses were performed to identify the critical biological functions, signaling pathways, and associated functional networks involved in the TLR4-primed immunoregulatory function of AS-MSCs. Results A total of 147 DE lncRNAs and 698 DE mRNAs were identified between TLR4-primed AS-MSCs and unstimulated AS-MSCs. Of these, 107 lncRNAs were upregulated and 40 were downregulated (fold change ≥2, P<0.05), while 504 mRNAs were upregulated and 194 were downregulated (fold change ≥2, P<0.05). Five lncRNAs and five mRNAs with the largest fold changes were respectively verified by qRT-PCR. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses demonstrated that the DE mRNAs and lncRNAs were highly associated with the inflammatory response, such as NOD-like receptor (NLR) signaling pathway, the TNF signaling pathway and the NF-κB signaling pathway. Cis-regulation prediction revealed eight novel lncRNAs, while trans-regulation prediction revealed 15 lncRNAs, respectively. Eight core pairs of lncRNA and target mRNA in the lncRNA-transcription factor (TF)-mRNA network were as follows: PACERR-PTGS2, LOC105378085-SOD2, LOC107986655-HIVEP2, MICB-DT-MICB, LOC105373925-SP140L, LOC107984251-IFIT5, LOC112268267-GBP2, and LOC101926887-IFIT3, respectively. Conclusions TLR4 activation in AS can enhance the immunoregulatory ability of MSCs. Eight core pairs of lncRNA and target mRNA were observed in TLR4-primed AS-MSCs, which could contribute to understanding the potential mechanism of AS-MSC immunoregulatory dysfunction.

Project description:Several previous studies have attempted to investigate the regulatory mechanisms underlying gene expression in ankylosing spondylitis (AS). However, the specific molecular pathways underlying this condition remain unclear. Previous research used next-generation RNA sequencing to identify a series of differentially expressed genes (DEGs) in peripheral blood mononuclear cells (PBMCs) when compared between patients with AS and healthy controls, thus implying that these DEGs may be related to AS. Furthermore, by screening these DEGS, it may be possible to facilitate clinical diagnosis and optimize treatment strategies. In order to test this hypothesis, we recruited 15 patients with AS and 15 healthy controls. We randomly selected five subjects from each group of patients for RNA sequencing analysis. Sequence reads were generated by an Illumina HiSeq2500 platform and mapped on to the human reference genome using HISAT2. We successfully identified 973 significant DEGs (p < 0.05) in PBMCs. When compared with controls, 644 of these genes were upregulated (with a fold?change?(FC) > 2) in AS patients and 329 were downregulated (FC < 0.5). Our analysis identified numerous genes related to immune response. Gene Ontology (GO) analysis indicated that these DEGs were significantly related to the positive regulation of epidermal growth factor-activated receptor activity, the positive regulation of the ERBB (erb-b2 receptor tyrosine kinase) signaling pathway, the differentiation of trophoblast giant cells, oxygen transport, immune-related pathways, and inflammation-related pathways. The DEGs were also closely related to the TNF and NF-?B signaling pathways. Six DEGs were verified by quantitative real-time polymerase chain reaction (qRT-PCR). Receiver operating characteristic (ROC) curve analysis indicated that IL6 may represent a useful biomarker for diagnosing AS. The development of new biomarkers may help us to elucidate the specific mechanisms involved in the development and progression of AS.

Dataset Information

Identification of the key genes and long non?coding RNAs in ankylosing spondylitis using RNA sequencing.

Publications

Identification of the key genes and long non‑coding RNAs in ankylosing spondylitis using RNA sequencing.

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