Expression analysis in multiple muscle groups and serum reveals complexity in the microRNA transcriptome of the mdx mouse and implications for therapy
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
SUBMITTER: Emelie Blomberg
PROVIDER: E-GEOD-36257 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
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Project description:MicroRNAs (miRNAs) are a class of small RNAs that regulate gene expression and are implicated in wide-ranging cellular processes and pathological conditions including Duchenne muscular dystrophy (DMD). We have compared differential miRNA expression in proximal and distal limb muscles, diaphragm, heart and serum in the mdx mouse relative to wild-type controls. Global transcriptome analysis revealed muscle-specific patterns of differential miRNA expression as well as a number of changes common between tissues, including previously identified dystromirs. In the case of miR-31 and miR-34c, up-regulation of primary-miRNA transcripts, precursor hairpins and all mature miRNAs derived from the same transcript or miRNA cluster strongly suggests transcriptional regulation of these miRNAs. The most striking differences in differential miRNA expression were between muscle tissue and serum. Specifically, miR-1, miR-133a and miR-206 were highly abundant in serum but down-regulated or modestly up-regulated in muscle, suggesting that these miRNAs are promising disease biomarkers. Indeed, the relative serum levels of these miRNAs were normalised in response to peptide-PMO mediated dystrophin restoration therapy. This study has revealed further complexity in the miRNA transcriptome of the mdx mouse, an understanding of which will be valuable in the development of novel therapeutics and for monitoring their efficacy.
2012-06-12 | GSE36257 | GEO
Project description:Recurrent hepatitis C virus (rHCV) is universal post-liver transplantation (LT), with accelerated fibrosis rates compared to non-transplanted patients. rHCV is associated with increased mortality and morbidity post-transplant and is a leading indication for re-transplantation. We hypothesized that miRNA expression profiles from liver grafts can distinguish severity of HCV recurrence and differentiate this from acute cellular rejection (ACR). Methods Using microarrays, we characterized global microRNA (miRNA) expression from patients with slow HCV fibrosis progression (F<2 Ishak), fast HCV fibrosis progression (FM-bM-^IM-%2 Ishak), ACR and non-HCV transplanted patients. Selected miRNA were analysed by quantitative PCR (qPCR) using both liver tissue and serum samples. Results We demonstrated changes in miRNA expression in patients with slow HCV fibrosis progression that were anti-fibrogenic, anti-angiogenic and anti-inflammatory in comparison to patients with fast HCV fibrosis progression. miRNA-146a, miRNA-19a, miRNA- 20a and miRNA-let-7e expression were increased in the slow HCV fibrosis progression group. In addition, comparison of patients with fast HCV progression against patients with ACR identified pro-fibrogenic pathways. qPCR analysis on liver tissue and serum confirmed the up-regulation of miRNAs in the slow HCV fibrosis progression group. Conclusion We demonstrate specific miRNA expression signatures that distinguish rate of progression of HCV recurrence and ACR post M-bM-^@M-^Sliver transplantation. Pathway analysis indicates that specific miRNA may play a regulatory role in these processes. The miRNAs identified may act as potential biomarkers for HCV recurrence post-LT and help distinguish between ACR and recurrent HCV. We compared 29 patients in total; 11 patients with slow HCV fibrosis progression, 9 patients with fast HCV fibrosis progression, 5 patients with acute cellular rejection and 4 HCV negative patients with normal liver histology that acted as controls. RNA was extracted from archived histology samples of the RG and NRG and miRNA expression was analysed using the affymetrix Genechip miRNA 2.0 assays.
2013-09-17 | E-GEOD-40113 | biostudies-arrayexpress
Project description:Measurements were performed on serum using 6 month old C57/B10 control (n=6) and mdx (n=8) mice. 1D proton and carbon spectra were collected on these samples
2014-09-15 | ST000099 | MetabolomicsWorkbench
Project description:The liverM-bM-^@M-^Ys remarkable capacity to regenerate allows it to carry out vital life-supporting functions despite unrelenting pathogen and toxin-induced injury. Unchecked, this capability also leads to cirrhosis, a burgeoning global disease burden. Existing animal models only partially recapitulate human liver regeneration, which hitherto has not been systematically studied. We investigated human liver regeneration in a unique model of liver transplantation. Here we show coordinated changes in expression of microRNA (miRNA) during regeneration that drive proliferation, innate immunity and angiogenesis. Failed regeneration is associated with distinct miRNAs enforcing cell cycle inhibition and DNA methylation. The miRNA expression associated with successful or failed regeneration when recapitulated in vitro, triggered expression of cardinal regeneration-linked genes promoting cell cycle entry or inhibition, respectively. Furthermore, inhibition of three miRNAs whose downregulation is associated with successful regeneration, induced proliferation in vitro. Our data indicate that human liver regeneration is orchestrated by distinct miRNAs determining cell cycle fate. Their manipulation may obviate the need for transplantation by enforcing successful regeneration in the liver and other solid organs. We compared a group of seven patients with successful regeneration (RG) after auxiliary liver transplant (ALT) to four patients who also had ALT but failed to regenerate (NRG). Regeneration was quantified by volume expansion using radiographic imaging; functional recovery was assessed using nuclear isotope scanning and hepatocellular regeneration using histology. Based on histological assessment, three time points were selected for both groups (RG and NRG). Biopsies were taken at the time of transplant and at different intervals post-transplant. Since sample acquisition was driven by clinical necessity, widely discrepant time intervals existed between T=1, T=2 and T=3 for the patients. RNA was extracted from archived histology samples of the RG and NRG, and miRNA expression was analysed using the Affymetrix GeneChip miRNA 1.0 assays. This submission does not include NRG samples taken at time point 3.
2013-05-06 | E-GEOD-36146 | biostudies-arrayexpress
Project description:Clear cell renal cell carcinomas (ccRCC) are characterized by arm-wide chromosomal alterations. Loss at 14q is associated with disease aggressiveness in ccRCC, which responds poorly to chemotherapeutics. The 14q locus contains one of the largest miRNA clusters in the human genome; however, little is known about the contribution of these miRNAs to ccRCC pathogenesis. In this regard, we investigated the expression pattern of selected miRNAs at the 14q32 locus in TCGA kidney tumors and in ccRCC cell lines. We validated that the miRNA cluster is downregulated in ccRCC (and cell lines) as well as in papillary kidney tumors relative to normal kidney tissues and primary renal proximal tubule epithelial (RPTEC) cells. We demonstrated that agents modulating expression of DNMT1 (e.g., 5-Aza-deoxycytidine) could modulate miRNA expression in ccRCC cell lines. Lysophosphatidic acid (LPA, a Lysophospholipid mediator elevated in ccRCC) not only increased labile iron content but also modulated expression of 14q32 miRNAs. Through an overexpression approach targeting a subset of 14q32 miRNAs (specifically at subcluster A: miR-431, miR-432, miR-127, and miR-433) in 769-P cells, we uncovered changes in cellular viability and claudin-1, a tight junction marker. A global proteomic approach was implemented using these miRNA overexpressing cell lines which uncovered ATXN2 as a highly downregulated target, which has a role in chronic kidney disease pathogenesis. Collectively, these findings support a contribution of miRNAs at 14q32 in ccRCC pathogenesis.
2023-05-10 | PXD036428 | Pride
Project description:MiRNAs regulate posttranscriptional gene expression and are widely implicated in the pathogenesis of complex diseases. We aim to elucidate miRNA regulation of the atrial mRNA signatures that associate with AF. This may provide novel mechanistical insights and candidate targets for therapies using miRNA mimics or antimiRs.
We present combined miRNAs-mRNAs sequencing in atrial tissues of patient without AF (n=22), with paroxysmal AF (n=22) and with persistent AF (n=20). MiRNA and mRNA signatures followed an ordinal scale from nonAF to paroxysmal to persistent AF patients. The previously reported mRNA sequencing identified 5228 differentially expressed genes involved in epithelial to mesenchymal transition, endothelial cell proliferation and extracellular matrix remodelling involving collagens, glycoproteins and proteoglycans. We discovered 103 differentially expressed miRNAs. Key downregulated miRNAs included miR-135b-5p, miR-138-5p, miR-200a-3p, miR-200b-3p and miR-31-5p and key upregulated miRNAs were miR-144-3p, miR-15b-3p, miR-182-5p miR-18b-5p, miR-4306 and miR-206. The expression levels of differentially expressed miRNAs were negatively correlated with the expression levels of their predicted target mRNAs. The downregulated miRNAs demonstrated a more profound transcriptome effect than the upregulated miRNAs. Upregulated biological processes enriched in miRNAs targets related to epithelial and endothelial cell migration and glycosaminoglycan biosynthesis, in line with the processes discovered by the mRNA sequencing analysis.
Combined analysis of miRNA and mRNA sequencing uncovered miRNAs with a broad transcriptional effect in human AF. Epithelial to mesenchymal transition and endothelial cell proliferation were processes controlled by downregulated miR-135b-5p, miR-138-5p, miR-200a-3p, miR-200b-3p and miR-31-5p, which in turn may contribute to (myo)fibroblast activation and structural remodeling.\
| EGAS00001005296 | EGA
Project description:Proctor2017 - Identifying microRNA for muscle regeneration during ageing (Mir378_in_muscle)
This model is described in the article:
Using computer simulation
models to investigate the most promising microRNAs to improve
muscle regeneration during ageing
Carole J. Proctor & Katarzyna
Goljanek-Whysall
Scientific Reports
Abstract:
MicroRNAs (miRNAs) regulate gene expression through
interactions with target sites within mRNAs, leading to
enhanced degradation of the mRNA or inhibition of translation.
Skeletal muscle expresses many different miRNAs with important
roles in adulthood myogenesis (regeneration) and myofibre
hypertrophy and atrophy, processes associated with muscle
ageing. However, the large number of miRNAs and their targets
mean that a complex network of pathways exists, making it
difficult to predict the effect of selected miRNAs on
age-related muscle wasting. Computational modelling has the
potential to aid this process as it is possible to combine
models of individual miRNA:target interactions to form an
integrated network. As yet, no models of these interactions in
muscle exist. We created the first model of miRNA:target
interactions in myogenesis based on experimental evidence of
individual miRNAs which were next validated and used to make
testable predictions. Our model confirms that miRNAs regulate
key interactions during myogenesis and can act by promoting the
switch between quiescent/proliferating/differentiating
myoblasts and by maintaining the differentiation process. We
propose that a threshold level of miR-1 acts in the initial
switch to differentiation, with miR-181 keeping the switch on
and miR-378 maintaining the differentiation and miR-143
inhibiting myogenesis.
This model is hosted on
BioModels Database
and identified by:
MODEL1704110002.
To cite BioModels Database, please use:
Chelliah V et al. BioModels: ten-year
anniversary. Nucl. Acids Res. 2015, 43(Database
issue):D542-8.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2017-09-26 | MODEL1704110002 | BioModels
Project description:Proctor2017 - Identifying microRNA for muscle regeneration during ageing (Mir1_in_muscle)
This model is described in the article:
Using computer simulation
models to investigate the most promising microRNAs to improve
muscle regeneration during ageing
Carole J. Proctor & Katarzyna
Goljanek-Whysall
Nature Scientific Reports
Abstract:
MicroRNAs (miRNAs) regulate gene expression through
interactions with target sites within mRNAs, leading to
enhanced degradation of the mRNA or inhibition of translation.
Skeletal muscle expresses many different miRNAs with important
roles in adulthood myogenesis (regeneration) and myofibre
hypertrophy and atrophy, processes associated with muscle
ageing. However, the large number of miRNAs and their targets
mean that a complex network of pathways exists, making it
difficult to predict the effect of selected miRNAs on
age-related muscle wasting. Computational modelling has the
potential to aid this process as it is possible to combine
models of individual miRNA:target interactions to form an
integrated network. As yet, no models of these interactions in
muscle exist. We created the first model of miRNA:target
interactions in myogenesis based on experimental evidence of
individual miRNAs which were next validated and used to make
testable predictions. Our model confirms that miRNAs regulate
key interactions during myogenesis and can act by promoting the
switch between quiescent/proliferating/differentiating
myoblasts and by maintaining the differentiation process. We
propose that a threshold level of miR-1 acts in the initial
switch to differentiation, with miR-181 keeping the switch on
and miR-378 maintaining the differentiation and miR-143
inhibiting myogenesis.
This model is hosted on
BioModels Database
and identified by:
MODEL1704110000.
To cite BioModels Database, please use:
Chelliah V et al. BioModels: ten-year
anniversary. Nucl. Acids Res. 2015, 43(Database
issue):D542-8.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2017-09-26 | MODEL1704110000 | BioModels
Project description:Proctor2017 - Identifying microRNA for muscle
regeneration during ageing (Mir143_in_muscle)
This model is described in the article:
Using computer simulation
models to investigate the most promising microRNAs to improve
muscle regeneration during ageing
Carole J. Proctor & Katarzyna
Goljanek-Whysall
Scientific Reports
Abstract:
MicroRNAs (miRNAs) regulate gene expression through
interactions with target sites within mRNAs, leading to
enhanced degradation of the mRNA or inhibition of translation.
Skeletal muscle expresses many different miRNAs with important
roles in adulthood myogenesis (regeneration) and myofibre
hypertrophy and atrophy, processes associated with muscle
ageing. However, the large number of miRNAs and their targets
mean that a complex network of pathways exists, making it
difficult to predict the effect of selected miRNAs on
age-related muscle wasting. Computational modelling has the
potential to aid this process as it is possible to combine
models of individual miRNA:target interactions to form an
integrated network. As yet, no models of these interactions in
muscle exist. We created the first model of miRNA:target
interactions in myogenesis based on experimental evidence of
individual miRNAs which were next validated and used to make
testable predictions. Our model confirms that miRNAs regulate
key interactions during myogenesis and can act by promoting the
switch between quiescent/proliferating/differentiating
myoblasts and by maintaining the differentiation process. We
propose that a threshold level of miR-1 acts in the initial
switch to differentiation, with miR-181 keeping the switch on
and miR-378 maintaining the differentiation and miR-143
inhibiting myogenesis.
This model is hosted on
BioModels Database
and identified by:
MODEL1704110003.
To cite BioModels Database, please use:
Chelliah V et al. BioModels: ten-year
anniversary. Nucl. Acids Res. 2015, 43(Database
issue):D542-8.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2017-09-26 | MODEL1704110003 | BioModels
Project description:Proctor2017 - Identifying microRNA for muscle
regeneration during ageing (Mir181_in_muscle)
This model is described in the article:
Using computer simulation
models to investigate the most promising microRNAs to improve
muscle regeneration during ageing
Carole J. Proctor & Katarzyna
Goljanek-Whysall
Scientific Reports
Abstract:
MicroRNAs (miRNAs) regulate gene expression through
interactions with target sites within mRNAs, leading to
enhanced degradation of the mRNA or inhibition of translation.
Skeletal muscle expresses many different miRNAs with important
roles in adulthood myogenesis (regeneration) and myofibre
hypertrophy and atrophy, processes associated with muscle
ageing. However, the large number of miRNAs and their targets
mean that a complex network of pathways exists, making it
difficult to predict the effect of selected miRNAs on
age-related muscle wasting. Computational modelling has the
potential to aid this process as it is possible to combine
models of individual miRNA:target interactions to form an
integrated network. As yet, no models of these interactions in
muscle exist. We created the first model of miRNA:target
interactions in myogenesis based on experimental evidence of
individual miRNAs which were next validated and used to make
testable predictions. Our model confirms that miRNAs regulate
key interactions during myogenesis and can act by promoting the
switch between quiescent/proliferating/differentiating
myoblasts and by maintaining the differentiation process. We
propose that a threshold level of miR-1 acts in the initial
switch to differentiation, with miR-181 keeping the switch on
and miR-378 maintaining the differentiation and miR-143
inhibiting myogenesis.
This model is hosted on
BioModels Database
and identified by:
MODEL1704110001.
To cite BioModels Database, please use:
Chelliah V et al. BioModels: ten-year
anniversary. Nucl. Acids Res. 2015, 43(Database
issue):D542-8.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2017-09-26 | MODEL1704110001 | BioModels