Dataset Information

Dynamically regulated miRNA-mRNA networks revealed by exercise.

ABSTRACT: BACKGROUND: 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 the subsequent recovery period. RESULTS: Here we monitored the transcriptome changes using microarray analysis of the whole blood of eight highly trained athletes before and 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 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. CONCLUSIONS: We have identified metabolic pathways involved in response to exercise and revealed four miRNA-mRNA networks dynamically regulated following exercise. This work is the first study to monitor miRNAs and mRNAs in parallel into the recovery period. The results provide a novel insight into the regulatory role of miRNAs in stress adaptation.

SUBMITTER: Tonevitsky AG

PROVIDER: S-EPMC3681679 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Dynamically regulated miRNA-mRNA networks revealed by exercise.

Tonevitsky Alexander G AG Maltseva Diana V DV Abbasi Asghar A Samatov Timur R TR Sakharov Dmitry A DA Shkurnikov Maxim U MU Lebedev Alexey E AE Galatenko Vladimir V VV Grigoriev Anatoly I AI Northoff Hinnak H

BMC physiology 20130607

<h4>Background</h4>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 the subsequent recovery period.<h4>Results</h4>Here we monitored the transcriptome changes using microarray analysis of the whole blood of eight highly trained athletes before and after 30 min of moderate exercise followed by 30 min and 60 min of recovery period. We combined expression profiling and bioinformat ...[more]

PMID: 24219008

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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:Chronic obstructive pulmonary disease (COPD) is characterized by expiratory airflow limitation and symptoms such as shortness of breath. Although many studies have demonstrated dysregulated microRNA (miRNA) and gene (mRNA) expression in the pathogenesis of COPD, how miRNAs and mRNAs systematically interact and contribute to COPD development is still not clear. To gain a deeper understanding of the gene regulatory network underlying COPD pathogenesis, we used Sparse Multiple Canonical Correlation Network (SmCCNet) to integrate whole blood miRNA and RNA-sequencing data from 404 participants in the COPDGene study to identify novel miRNA-mRNA networks associated with COPD-related phenotypes including lung function and emphysema. We hypothesized that phenotype-directed interpretable miRNA-mRNA networks from SmCCNet would assist in the discovery of novel biomarkers that traditional single biomarker discovery methods (such as differential expression) might fail to discover. Additionally, we investigated whether adjusting -omics and clinical phenotypes data for covariates prior to integration would increase the statistical power for network identification. Our study demonstrated that partial covariate adjustment for age, sex, race, and CT scanner model (in the quantitative emphysema networks) improved network identification when compared with no covariate adjustment. However, further adjustment for current smoking status and relative white blood cell (WBC) proportions sometimes weakened the power for identifying lung function and emphysema networks, a phenomenon which may be due to the correlation of smoking status and WBC counts with the COPD-related phenotypes. With partial covariate adjustment, we found six miRNA-mRNA networks associated with COPD-related phenotypes. One network consists of 2 miRNAs and 28 mRNAs which had a 0.33 correlation (p = 5.40E-12) to forced expiratory volume in 1 s (FEV1) percent predicted. We also found a network of 5 miRNAs and 81 mRNAs that had a 0.45 correlation (p = 8.80E-22) to percent emphysema. The miRNA-mRNA networks associated with COPD traits provide a systems view of COPD pathogenesis and complements biomarker identification with individual miRNA or mRNA expression data.

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Dynamically regulated miRNA-mRNA networks revealed by exercise.

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Dynamically regulated miRNA-mRNA networks revealed by exercise.

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