Integrated analysis of hepatic mRNA and miRNA profiles identified molecular networks and potential biomarkers of NAFLD.
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ABSTRACT:
SUBMITTER: Zhu M
PROVIDER: S-EPMC5955949 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Several studies have investigated miRNA and mRNA co-expression to identify regulatory networks at the transcriptional level. A typical finding of these studies is the presence of both negative and positive miRNA-mRNA correlations. Negative correlations are consistent with the expected, faster degradation of target mRNAs, whereas positive correlations denote the existence of feed-forward regulations mediated by transcription factors. Both mechanisms have been characterized at the molecular level, although comprehensive methods to represent miRNA-mRNA correlations are lacking. At present, genome-wide studies are able to assess the expression of more than 1000 mature miRNAs and more than 35,000 well-characterized human genes. Even if studies are generally restricted to a small subset of genes differentially expressed in specific diseases or experimental conditions, the number of potential correlations remains very high, and needs robust multivariate methods to be conveniently summarized by a small set of data.Nonparametric Kendall correlations were calculated between miRNAs and mRNAs differentially expressed in livers of patients with acute liver failure (ALF) using normal livers as controls. Spurious correlations due to the histopathological composition of samples were removed by partial correlations. Correlations were then transformed into distances and processed by multidimensional scaling (MDS) to map the miRNA and mRNA relationships. These showed: (a) a prominent displacement of miRNA and mRNA clusters in ALF livers, as compared to control livers, indicative of gene expression dysregulation; (b) a clustering of mRNAs consistent with their functional annotations [CYP450, transcription factors, complement, proliferation, HLA class II, monocytes/macrophages, T cells, T-NK cells and B cells], as well as a clustering of miRNAs with the same seed sequence; and (c) a tendency of miRNAs and mRNAs to populate distinct regions of the MDS plot. MDS also allowed to visualize the network of miRNA-mRNA target pairs.Different features of miRNA and mRNA relationships can be represented as thematic maps within the framework of MDS obtained from pairwise correlations. The symmetric distribution of positive and negative correlations between miRNA and mRNA expression suggests that miRNAs are involved in a complex bidirectional molecular network, including, but not limited to, the inhibitory regulation of miRNA targets.
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Project description:BackgroundLong noncoding RNAs (lncRNAs) can regulate gene expression in a cis-regulatory fashion or as "microRNA sponges". However, the expression and functions of lncRNAs during early human immunodeficiency virus (HIV) infection (EHI) remain unclear.Methods3 HAART-naive EHI patients and 3 healthy controls (HCs) were recruited in this study to perform RNA sequencing and microRNA (miRNA) sequencing. The expression profiles of lncRNAs, mRNAs and miRNAs were obtained, and the potential roles of lncRNAs were analysed based on discovering lncRNA cis-regulatory target mRNAs and constructing lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) networks. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on 175 lncRNA-associated differentially expressed (DE) mRNAs to investigate the potential functions of DE lncRNAs in ceRNA networks.ResultsA total of 242 lncRNAs, 1240 mRNAs and 21 mature known miRNAs were determined as differentially expressed genes in HAART-naive EHI patients compared to HCs. Among DE lncRNAs, 44 lncRNAs were predicted to overlap with 41 target mRNAs, and 107 lncRNAs might regulate their nearby DE mRNAs. Two DE lncRNAs might regulate their cis-regulatory target mRNAs BTLA and ZAP70, respectively, which were associated with immune activation. In addition, the ceRNA networks comprised 160 DE lncRNAs, 21 DE miRNAs and 175 DE mRNAs. Seventeen DE lncRNAs were predicted to regulate HIF1A and TCF7L2, which are involved in the process of HIV-1 replication. Twenty DE lncRNAs might share miRNA response elements (MREs) with FOS, FOSB and JUN, which are associated with both immune activation and HIV-1 replication.ConclusionsThis study revealed that lncRNAs might play a critical role in HIV-1 replication and immune activation during EHI. These novel findings are helpful for understanding of the pathogenesis of HIV infection and provide new insights into antiviral therapy.
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Project description:Diabetic foot ulcer (DFU) is a common and serious complication of diabetes mellitus, which influences patients' quality of life. Recently, circRNA regulated the mRNA levels by functioning as miRNA sponge in various disease, including diabetes mellitus. Nevertheless, the circRNA-miRNA-mRNA regulatory network involved in DFU remains obscure. The aim of this study is to construct a competing endogenous RNA (ceRNA) network and screen biological indicators as diagnostic factors in DFU. All the differentially expressed circRNAs, miRNAs and mRNAs were derived from Gene Expression Omnibus database. Furthermore, circRNAs identified by cytoHubba analysis and miRNAs obtained by human miRNA-disease database were used to construct DFU-specific ceRNA network with intersection of mRNAs. Functional enrichment analysis displayed the function and pathway of dysregulated mRNAs. Hub genes with high diagnostic value were screened by ClusterONE, GO semantic similarity and receiver operating characteristic (ROC) curve. Here, the ceRNA network consisted of 8 circRNAs, 11 miRNAs and 91 mRNAs. Functional enrichment analysis demonstrated diabetic complications-related pathway including TGF-beta, FoxO and Wnt signaling pathway. GO semantic similarity and ROC curve analysis showed 6 hub genes with high diagnostic value (the area under the ROC curve ≥ 0.8) in patients with DFU, including BCL2, CCND1, IRAK4, SMAD4, SP1 and SUFU, which were identified as potential target genes for DFU diagnosis. In conclusion, the present study looked at a circRNA-miRNA-mRNA regulatory network with DFU and screened the potential function of mRNA, then identified novel diagnostic biomarkers and therapeutic targets for patients with DFU.
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Project description:BackgroundGlioblastoma multiforme (GBM) is the most seriously brain tumor with extremely poor prognosis. Recent research has demonstrated that competitive endogenous RNA (ceRNA) network which long noncoding RNAs (lncRNAs) act as microRNA (miRNA) sponges to regulate mRNA expression were closely related to tumor development. However, the regulatory mechanisms and functional roles of ceRNA network in the pathogenesis of GBM are remaining poorly understood.MethodsIn this study, we systematically analyzed the expression profiles of lncRNA and mRNA (GSE51146 dataset) and miRNA (GSE65626 dataset) from GEO database. Then, we constructed a ceRNA network with the dysregulated genes by bioinformatics methods. The TCGA and GSE4290 dataset were used to confirm the expression and prognostic value of candidate mRNAs.ResultsIn total, 3413 differentially expressed lncRNAs and mRNAs, 305 differentially expressed miRNAs were indentified in GBM samples. Then a ceRNA network containing 3 lncRNAs, 5 miRNAs, and 60 mRNAs was constructed. The overall survival analysis of TCGA databases indicated that two mRNAs (C1s and HSD3B7) were remarkly related with the prognosis of GBM.ConclusionThe ceRNA network may increase our understanding to the pathogenesis of GBM. In general, the candidate mRNAs from the ceRNA network can be predicted as new therapeutic targets and prognostic biomarkers for GBM.
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Project description:Background: The complicated molecular mechanisms underlying the therapeutic effect of electroacupuncture (EA) on ischemic stroke are still unclear. Recently, more evidence has revealed the essential role of the microRNA (miRNA)-mRNA networks in ischemic stroke. However, a systematic analysis of novel key genes, miRNAs, and miRNA-mRNA networks regulated by EA in ischemic stroke is still absent. Methods: We established a middle cerebral artery occlusion (MCAO) mouse model and performed EA therapy on ischemic stroke mice. Behavior tests and measurement of infarction area were applied to measure the effect of EA treatment. Then, we performed RNA sequencing to analyze differentially expressed genes (DEGs) and functional enrichment between the EA and control groups. In addition, a protein-protein interaction (PPI) network was built, and hub genes were screened by Cytoscape. Upstream miRNAs were predicted by miRTarBase. Then hub genes and predicted miRNAs were verified as key biomarkers by RT-qPCR. Finally, miRNA-mRNA networks were constructed to explore the potential mechanisms of EA in ischemic stroke. Results: Our analysis revealed that EA treatment could significantly alleviate neurological deficits in the affected limbs and reduce infarct area of the MCAO model mice. A total of 174 significant DEGs, including 53 upregulated genes and 121 downregulated genes, were identified between the EA and control groups. Functional enrichment analysis showed that these DEGs were associated with the FOXO signaling pathway, NF-kappa B signaling pathway, T-cell receptor signaling pathway, and other vital pathways. The top 10 genes with the highest degree scores were identified as hub genes based on the degree method, but only seven genes were verified as key genes according to RT-qPCR. Twelve upstream miRNAs were predicted to target the seven key genes. However, only four miRNAs were significantly upregulated and indicated favorable effects of EA treatment. Finally, comprehensive analysis of the results identified the miR-425-5p-Cdk1, mmu-miR-1186b-Prc1, mmu-miR-434-3p-Prc1, and mmu-miR-453-Prc1 miRNA-mRNA networks as key networks that are regulated by EA and linked to ischemic stroke. These networks might mainly take place in neuronal cells regulated by EA in ischemic stroke. Conclusion: In summary, our study identified key DEGs, miRNAs, and miRNA-mRNA regulatory networks that may help to facilitate the understanding of the molecular mechanism underlying the effect of EA treatment on ischemic stroke.
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