Dataset Information

Identification of dynamically regulated microRNA and mRNA networks in developing oligodendrocytes.

ABSTRACT: MicroRNAs (miRNAs) play important roles in modulating gene expression at the posttranscriptional level. In postnatal oligodendrocyte lineage cells, the miRNA expression profile ("microRNAome") contains 43 miRNAs whose expression dynamically changes during the transition from A2B5(+) oligodendrocyte progenitor cells to premyelinating GalC(+) cells. The combination of microRNAome profiling with analyses of the oligodendrocyte transcriptome reveals a target bias for a class of miRNAs which includes miR-9. We show that miR-9 is downregulated during oligodendrocyte differentiation. In addition, miR-9 expression level inversely correlates with the expression of its predicted targets, among which is the peripheral myelin protein PMP22. We found that PMP22 mRNA but not protein is detectable in oligodendrocytes, whereas Schwann cells producing PMP22 protein lack miR-9. We demonstrate that miR-9 interacts with the 3' untranslated region of PMP22 and downregulates its expression. Our results support models in which miRNAs can act as guardians of the transcriptome.

SUBMITTER: Lau P

PROVIDER: S-EPMC2646797 | biostudies-literature | 2008 Nov

REPOSITORIES: biostudies-literature

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Identification of dynamically regulated microRNA and mRNA networks in developing oligodendrocytes.

Lau Pierre P Verrier Jonathan D JD Nielsen Joseph A JA Johnson Kory R KR Notterpek Lucia L Hudson Lynn D LD

The Journal of neuroscience : the official journal of the Society for Neuroscience 20081101 45

MicroRNAs (miRNAs) play important roles in modulating gene expression at the posttranscriptional level. In postnatal oligodendrocyte lineage cells, the miRNA expression profile ("microRNAome") contains 43 miRNAs whose expression dynamically changes during the transition from A2B5(+) oligodendrocyte progenitor cells to premyelinating GalC(+) cells. The combination of microRNAome profiling with analyses of the oligodendrocyte transcriptome reveals a target bias for a class of miRNAs which includes ...[more]

PMID: 18987208

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Project description:MiRNAs are essential mediators of many biological processes. The aim of this study was to investigate the dynamics of miRNA-mRNA regulatory networks during exercise and subsequent recovery period. Here we monitored the transcriptome changes by microarray analysis of the whole blood of eight highly trained athletes after 30 min of moderate exercise followed by 30 min and 60 min of recovery period. We combined expression profiling and bioinformatics and analysed metabolic pathways enriched with differentially expressed mRNAs and then mRNAs which are known to be validated targets of differentially expressed miRNAs. Finally we revealed four dynamically regulated networks comprising differentially expressed miRNAs and their known target mRNAs with anti-correlated expression profiles over time. The data suggest that hsa-miR-21-5p regulated TGFBR3, PDGFD and PPM1L mRNAs. Hsa-miR-24-2-5p was likely to be responsible for MYC and KCNJ2 genes and hsa-miR-27a-5p for ST3GAL6. The targets of hsa-miR-181a-5p included ROPN1L and SLC37A3. All these mRNAs are involved in processes highly relevant to exercise response, including immune function, apoptosis, membrane traffic of proteins and transcription regulation. We have identified four miRNA-mRNA networks dynamically regulated following exercise. This work is the first study to monitor miRNAs and mRNAs in parallel into recovery period. The results provide a novel insight into the regulatory role of miRNAs in stress adaptation. Each subject performed a treadmill test with an incremental step protocol until exhaustion. Blood samples were taken from the antecubital vein using indwelling catheter before (T1), immediately after ramp test to exaustion (T2) and after 30 min of recovery (T3). Two weeks later, athletes participated in the main exercise, consisting of running at 80% VO2 peak for 30 min on a treadmill. Blood samples were taken from the antecubital vein using indwelling catheter before (T4), immediately after running at 80% VO2 peak for 30 min on a treadmill (T5), after 30 min (T6) and 60 min (T7) of recovery.

Project description:BackgroundPeriodontitis is a complex infectious disease with various causes and contributing factors. The aim of this study was to identify key genes, microRNAs (miRNAs) and transcription factors (TFs) and construct a miRNA-mRNA-TF regulatory networks to investigate the underlying molecular mechanism in periodontitis.MethodsThe GSE54710 miRNA microarray dataset and the gene expression microarray dataset GSE16134 were downloaded from the Gene Expression Omnibus database. The differentially expressed miRNAs (DEMis) and mRNAs (DEMs) were screened using the "limma" package in R. The intersection of the target genes of candidate DEMis and DEMs were considered significant DEMs in the regulatory network. Next, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted. Subsequently, DEMs were uploaded to the STRING database, a protein-protein interaction (PPI) network was established, and the cytoHubba and MCODE plugins were used to screen out key hub mRNAs and significant modules. Ultimately, to investigate the regulatory network underlying periodontitis, a global triple network including miRNAs, mRNAs, and TFs was constructed using Cytoscape software.Results8 DEMis and 121 DEMs were found between the periodontal and control groups. GO analysis showed that mRNAs were most significantly enriched in positive regulation of the cell cycle, and KEGG pathway analysis showed that mRNAs in the regulatory network were mainly involved in the IL-17 signalling pathway. A PPI network was constructed including 81 nodes and 414 edges. Furthermore, 12 hub genes ranked by the top 10% genes with high degree connectivity and five TFs, including SRF, CNOT4, SIX6, SRRM3, NELFA, and ONECUT3, were identified and might play crucial roles in the molecular pathogenesis of periodontitis. Additionally, a miRNA-mRNA-TF coregulatory network was established.ConclusionIn this study, we performed an integrated analysis based on public databases to identify specific TFs, miRNAs, and mRNAs that may play a pivotal role in periodontitis. On this basis, a TF-miRNA-mRNA network was established to provide a comprehensive perspective of the regulatory mechanism networks of periodontitis.

Dataset Information

Identification of dynamically regulated microRNA and mRNA networks in developing oligodendrocytes.

Publications

Identification of dynamically regulated microRNA and mRNA networks in developing oligodendrocytes.

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