Reconstruction and Analysis of a Long Noncoding RNA-Associated Competing Endogenous RNA Network in Hypertrophic Cardiomypathy [array]
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ABSTRACT: Hypertrophic cardiomyopathy (HCM) is the most common heritable cardiomyopath that caused by mutations in genes encoding proteins of the cardiac sarcomere. Although multiple efforts have been made to understand the pathogenesis of HCM, the mechanisms of how long noncoding RNA (lncRNA)-associated competing endogenous RNA (ceRNA) network result in HCM still unkown. Herein, we acquired the different expression profiles of lncRNAs (DElncRNAs) and messenger RNAs (mRNA, DEGs) by using microarray, microRNAs (DEmiRNAs) by sequencing in plasma of HCM patients and healthy controls. LncRNA-miRNA pairs were predicted using miRcode and starBase, and crossed with DEmiRNAs. MiRNA-mRNA pairs were retrieved from miRanda and TargetScan, and crossed with DEGs. Combined these pairs, the ceRNA network was constructed and hub nodes were then analyzed to reconstruct subnetwork. Gene Ontology and KEGG pathways were used to analyse the mRNAs in the ceRNA. Total 520 DElncRNAs, 33 DEmiRNAs, and 371 DEGs were identified. By coexpression analysis, 682 lncRNA-mRNA pairs were identified with a coefficient ≥ 0.9 and p < 0.05. The ceRNA network with 8 lncRNAs, 3 miRNAs and 22 mRNAs was constructed visualized by Cytoscape. LncRNA RP11-66N24.4 and LINC00310 are among the top 10% nodes and the associated ceRNA subnetwork may be the center of the whole ceRNA network. Furthermore, the qRT-PCR results showed that LINC00310 was signifcantly decreased in HCM patients. For LINC00310, GO analysis revealed that the biological processes was enriched in cardiovascular system development, sprouting angiogenesis, circulatory system development and so on, and Pathway analysis was mainly enriched in cGMP-PKG signaling pathway. Our study reveals the novel lncRNA-related ceRNA network in HCM and the identified lncRNA LINC00310 may be roles in the pathogenesis mechanisms of HCM, which could provide further insight into the pathogenesis of HCM.
Project description:Hypertrophic cardiomyopathy (HCM) is the most common heritable cardiomyopath that caused by mutations in genes encoding proteins of the cardiac sarcomere. Although multiple efforts have been made to understand the pathogenesis of HCM, the mechanisms of how long noncoding RNA (lncRNA)-associated competing endogenous RNA (ceRNA) network result in HCM still unkown. Herein, we acquired the different expression profiles of lncRNAs (DElncRNAs) and messenger RNAs (mRNA, DEGs) by using microarray, microRNAs (DEmiRNAs) by sequencing in plasma of HCM patients and healthy controls. LncRNA-miRNA pairs were predicted using miRcode and starBase, and crossed with DEmiRNAs. MiRNA-mRNA pairs were retrieved from miRanda and TargetScan, and crossed with DEGs. Combined these pairs, the ceRNA network was constructed and hub nodes were then analyzed to reconstruct subnetwork. Gene Ontology and KEGG pathways were used to analyse the mRNAs in the ceRNA. Total 520 DElncRNAs, 33 DEmiRNAs, and 371 DEGs were identified. By coexpression analysis, 682 lncRNA-mRNA pairs were identified with a coefficient ≥ 0.9 and p < 0.05. The ceRNA network with 8 lncRNAs, 3 miRNAs and 22 mRNAs was constructed visualized by Cytoscape. LncRNA RP11-66N24.4 and LINC00310 are among the top 10% nodes and the associated ceRNA subnetwork may be the center of the whole ceRNA network. Furthermore, the qRT-PCR results showed that LINC00310 was signifcantly decreased in HCM patients. For LINC00310, GO analysis revealed that the biological processes was enriched in cardiovascular system development, sprouting angiogenesis, circulatory system development and so on, and Pathway analysis was mainly enriched in cGMP-PKG signaling pathway. Our study reveals the novel lncRNA-related ceRNA network in HCM and the identified lncRNA LINC00310 may be roles in the pathogenesis mechanisms of HCM, which could provide further insight into the pathogenesis of HCM.
Project description:Background: Cardiac fibrosis (CF) and heart failure (HF) are familiar heart diseases that are harmful to health, and severe CF can lead to HF. In this study, we tried to find their common potential molecular markers, which may help the diagnosis and treatment of CF and HF. Methods: Firstly, RNA library construction and high-throughput sequencing were performed. In addition, the DESeq2 package in R was used to screen genes with differentially expressed between different samples. Then, take the intersection of the differential mRNA, miRNA and lncRNA obtained for the two diseases. Thirdly, the ConsensusPathDB (CPDB) was used to perform biological functions enrichment for intersection differentially expressed mRNAs (DEmRNAs). Fourthly, construct gene interaction network and screen out key genes. Fifthly, RT-PCR verification was performed. Lastly, GSE104150 and GSE21125 data sets were utilized to validation the expression and diagnostic analysis. Results: There are 1477 DEmRNAs, 502 differentially expressed lncRNA (DElncRNAs) and 36 differentially expressed miRNA (DEmiRNAs) between CF and healthy control group. There are 607 DEmRNAs, 379 DElncRNAs and 42 DEmiRNAs between HF and healthy control group. CH and FH shared 146 DEmRNAs, 80 DElncRNAs, and 6 DEmiRNAs. Hsa-miR-144-3p, CCNE2, C9orf72, MAP3K20-AS1, LEF1-AS1, AC243772.2, FLJ46284 and AC239798.2 were keys genes in lncRNA-miRNA-mRNA network. In addition, hsa-miR-144-3p and CCNE2 may be considered as potential diagnostic gene biomarkers in CF and HF.
Project description:Background: Cardiac fibrosis (CF) and heart failure (HF) are familiar heart diseases that are harmful to health, and severe CF can lead to HF. In this study, we tried to find their common potential molecular markers, which may help the diagnosis and treatment of CF and HF. Methods: Firstly, RNA library construction and high-throughput sequencing were performed. In addition, the DESeq2 package in R was used to screen genes with differentially expressed between different samples. Then, take the intersection of the differential mRNA, miRNA and lncRNA obtained for the two diseases. Thirdly, the ConsensusPathDB (CPDB) was used to perform biological functions enrichment for intersection differentially expressed mRNAs (DEmRNAs). Fourthly, construct gene interaction network and screen out key genes. Fifthly, RT-PCR verification was performed. Lastly, GSE104150 and GSE21125 data sets were utilized to validate the expression and diagnostic analysis. Results: There are 1477 DEmRNAs, 502 differentially expressed lncRNA (DElncRNAs) and 36 differentially expressed miRNA (DEmiRNAs) between CF and healthy control group. There are 607 DEmRNAs, 379 DElncRNAs and 42 DEmiRNAs between HF and healthy control group. CH and FH shared 146 DEmRNAs, 80 DElncRNAs, and 6 DEmiRNAs. Hsa-miR-144-3p, CCNE2, C9orf72, MAP3K20-AS1, LEF1-AS1, AC243772.2, FLJ46284 and AC239798.2 were keys genes in lncRNA-miRNA-mRNA network. In addition, hsa-miR-144-3p and CCNE2 may be considered as potential diagnostic gene biomarkers in CF and HF.
Project description:we conducted transcriptome and small RNA sequencing to identify differentially expressed genes (DEGs), miRNAs (DEMs), and lncRNAs (DELs). Function analysis on DEM-target genes can explain the regulatory roles of miRNAs in LC. The lncRNA-miRNA pairs, miRNA-mRNA pairs, and lncRNA-mRNA pairs were identified, which were then combined to construct the interplay of lncRNAs/miRNAs/mRNAs. And we used the online databases to verify the selected DEMs, DELs, and DEGs. Our study identified 2509 DEGs, 34 DEMs, and 432 DELs in LC patients. miRNA-mRNA pairs, including 1 miRNA (hsa-miR-21-5p) and 5 targeted genes (RECK, TIMP3, EHD1, RASGRP1 and ERG), were figured out. We finally found the hub subnetwork (LINC00632/has-miR-21-5p/TIMP3) by combining lncRNA-miRNA pairs, miRNA-mRNA pairs and lncRNA-mRNA pairs.
Project description:We conducted transcriptome and small RNA sequencing to identify differentially expressed genes (DEGs), miRNAs (DEMs), and lncRNAs (DELs). Function analysis on DEM-target genes can explain the regulatory roles of miRNAs in LC. The lncRNA-miRNA pairs, miRNA-mRNA pairs, and lncRNA-mRNA pairs were identified, which were then combined to construct the interplay of lncRNAs/miRNAs/mRNAs. And we used the online databases to verify the selected DEMs, DELs, and DEGs. Our study identified 2509 DEGs, 34 DEMs, and 432 DELs in LC patients. miRNA-mRNA pairs, including 1 miRNA (hsa-miR-21-5p) and 5 targeted genes (RECK, TIMP3, EHD1, RASGRP1 and ERG), were figured out. We finally found the hub subnetwork (LINC00632/has-miR-21-5p/TIMP3) by combining lncRNA-miRNA pairs, miRNA-mRNA pairs and lncRNA-mRNA pairs.
Project description:GCs were collected from HFs and AFs , to use second-generation high-throughput sequencing for whole-transcriptome analysis, respectively. In total, 1861 and 1075 mRNAs, 159 and 24 miRNAs, 123 and 100 lncRNAs, and 58 and 54 circRNAs were identified to be differentially expressed (DE) in up-regulated and down-regulated. Enrichment of functions and signaling pathways of the DEgenes showed that most of DEmRNAs and targets of DEmiRNAs, DElncRNAs and DEcricRNAs were annotated to the categories of ‘PI3K-Akt signaling pathway’, ‘ECM-receptor interaction’, ‘Focal adhesion’, ‘mTOR signaling pathway ’ ‘TGF-beta signaling pathway’, ‘Rap1 signaling pathway’, and ‘Estrogen signaling pathway’. The ceRNA (competing endogenous RNA) network was constructed based on ceRNA theory further revealed regulatory roles of these DERNAs in granulosa cells of buffalo atretic follicles. A large number of mRNAs, lncRNAs, circRNAs, and miRNAs in buffalo granulosa were altered in healthy and atretic follicles, which may play crucial roles in atretic of buffalo follicles through the ceRNA regulatory network.
Project description:For patients with chronic thromboembolic pulmonary hypertension (CTEPH), it can lead to death if left untreated. In this study, we attempted to identify key genes and pathways that could help in the diagnosis and treatment of CTEPH. It also provides research direction for further understanding the molecular mechanism of CTEPH.Firstly, we extract RNA from blood samples to construct the library. Then, qualified libraries were sequenced using PE100 strategy on BGIseq platform. Subsequently, the DESeq2 package in R was used to screen differentially expressed mRNAs (DEmRNAs) and differentially expressed lncRNAs (DElncRNAs) of the CTEPH patient group and the normal control group. Afterwards, we performed functional enrichment and protein-protein interaction analysis of DEmRNAs. In addition, we also performed lncRNA-mRNA co-expression analysis and lncRNA-miRNA-mRNA network construction. A total of 437 DEmRNAs and 192 DElncRNAs were obtained. Subsequently, 205 pairs of interacting DEmRNAs and 232 pairs of lncRNA-mRNA relationship were obtained. Moreover, DEmRNAs were significantly enriched in chemokine signaling pathway, metabolic pathways, arachidonic acid metabolism and MAPK signaling pathway. In addition, only one regulation pathway of SOBP-has-miR-320b-LINC00472 was found through ceRNA network construction. In diagnostic analysis, the area under curve (AUC) of LINC00472, PIK3R6, SCN3A and TCL6 were greater than 0.7, which were 0.964, 0.893, 0.750 and 0.732, respectively. It is indicated that LINC00472, PIK3R6, SCN3A and TCL6 may as the potential diagnostic gene markers in CTEPH.
Project description:Adiponectin (APN) is an endogenous adipokine secreted from adipocytes that exerts an anti-inflammation property. AdipoAI is an orally active adiponectin receptor agonist identified by our group, which can emulate APN's anti-inflammatory properties through mechanisms not fully understood. To explore AdipoAI function, we used lncRNA microarray and got differential lncRNA/mRNA expression medicated by AdipoAI. Identified as one kind of non-coding RNA with more than 200bp length, lncRNA has been demonstrated to have abundance biological functions, including anti-inflammatory response. In the current study, we performed an lncRNA microarray in LPS-induced Raw264.7 cells which pre-stimulated with AdipoAI, and screened 110 DElncRNAs and 190 DEmRNAs. Enrichment analyses were conducted to total mRNAs and DEmRNAs, including GSVA, ssGSEA, GO/KEGG, GSEA and PPI analysis. Among all these processes, endocytosis was significantly enriched. A co-expression analysis was built based on DElncRNAs and DEmRNAs. Then, using Targetscan and miRwalk to predict related microRNAs of DElncRNAs and DEmRNAs respectively, we established competing endogenous RNA (ceRNA) networks including 54 mRNAs from 8 GO items. Furthermore, 33 m6A methylation related marker genes were obtained from previous study and used for the construction of m6A related-lncRNA network using the co-expression analysis. We identified FTO as the hub gene of the network, and 14 lncRNAs that interacted with it. The expression levels of 10 lncRNAs selected from ceRNA and FTO- related lncRNAs networks were validated with qRT-PCR. Finally, Macrophage phenotype scores showed that AdipoAI could attenuate the M2b and M2c polarization of macrophage and correlate with the above lncRNAs. Our work reveals that lncRNA might involve in the anti-inflammation process of AdipoAI in LPS-induced macrophages through ceRNA network and epigenetic regulation of m6A. Mechanistically, these lncRNAs associated with AdipoAI might be related to endocytosis and polarization in macrophage, and provide new candidates for the anti-inflammatory application of APN and its receptor agonist.
Project description:Some ceRNA associated with lncRNA have been considered as possible diagnostic and therapeutic biomarkers for obstructive sleep apnea (OSA). We intend to identify the potential hub genes for the development of OSA, which will provide a foundation for the study of the molecular mechanism underlying OSA and for the diagnosis and treatment of OSA.We collected plasma samples from OSA patients and healthy controls for the detection of ceRNA using a chip. Based on the differential expression of lncRNA, we identified the target genes of miRNA that bind to lncRNAs. We then constructed lncRNA-related ceRNA networks, performed functional enrichment analysis and protein-protein interaction analysis, and performed internal and external validation of the expression levels of stable hub genes. Then, we conducted LASSO regression analysis on the stable hub genes, selected relatively significant genes to construct a simple and easy-to-use nomogram, validated the nomogram, and constructed the core ceRNA sub-network of key genes.We successfully identified 282 DElncRNAs and 380 DEmRNAs through differential analysis, and we constructed an OSA-related ceRNA network consisting of 292 miRNA-lncRNAs and 41 miRNA-mRNAs. Through PPI and hub gene selection, we obtained 7 additional robust hub genes, CCND2, WT1, E2F2, IRF1, BAZ2A, LAMC1, and DAB2. Using LASSO regression analysis, we created a nomogram with four predictors (CCND2, WT1, E2F2, and IRF1), and its area under the curve (AUC) is 1. Finally, we constructed a core ceRNA sub-network composed of 74 miRNA-lncRNA and 7 miRNA-mRNA nodes.Our study provides a new foundation for elucidating the molecular mechanism of lncRNA in OSA and for diagnosing and treating OSA.
Project description:Acute lung injury (ALI) is associated with a high mortality rate; however, the underlying molecular mechanisms are poorly understood. The purpose of this study was to investigate the expression profile and related networks of long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and mRNAs in lung tissue exosomes obtained from sepsis-induced ALI. A mouse model of sepsis was established using the cecal ligation and puncture method. RNA sequencing was performed using lung tissue exosomes obtained from mice in the sham and CLP groups. Hematoxylin-eosin staining, western blotting, immunofluorescence, quantitative real-time polymerase chain reaction, and nanoparticle tracking analysis were performed to identify relevant phenotypes, and bioinformatic algorithms were used to evaluate competitive endogenous RNA (ceRNA) networks.Thirty lncRNA-miRNA-mRNA interactions were identified, including two upregulated lncRNAs, 30 upregulated miRNAs, and two downregulated miRNAs. Based on the expression levels of DEmRNAs, DELncRNAs, and DEmiRNAs, 30 ceRNA networks were constructed. This study revealed, for the first time, biomarkers of lung tissue exosome RNA and the related networks of lncRNA in sepsis-induced ALI. We revealed a novel molecular mechanism of sepsis-induced ALI, which may support the diagnosis and treatment of sepsis-induced ALI.