Dissecting the genetics of cutaneous miRNA in a mouse model of autoimmune bullous disease
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus synthetic construct
PROVIDER: GSE64276 | GEO | 2014/12/18
SECONDARY ACCESSION(S): PRJNA270619
REPOSITORIES: GEO
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Project description:MicroRNAs (miRNAs) are small endogenous, non-coding RNAs that control genes at post-transcriptional level. They are essential for development and tissue differentiation, and altered miRNA expression patterns are linked to the pathogenesis of inflammation and cancer. There is evidence that miRNA expression is genetically controlled similar to the transcription of protein-coding genes and previous studies identified quantitative trait loci (QTL) for miRNA expression in the liver. So far, little attention has been paid to miRNA expression in the skin. Moreover, there is no data on epistatic control of miRNA expression. In this study, we statistically linked cutaneous miRNA expression patterns to SNP (single nucleotide polymorphism) markers in an advanced murine intercross line (AIL) of three strains (BxD2, NZM and MRL) that are known to be prone to develop autoimmune diseases as well as the wild-derived strain CAST/EiJ. In particular, we screened 100 murine samples for 609 different miRNAs and identified 42 eQTL controlling the expression of 38 cutaneous miRNAs. As a result, we identified two chromosomal hot-spots on chromosome 2 and 8 that control the expression of multiple miRNAs. Moreover, for eight miRNAs, an interacting effect of pairs of SNP was observed. Combining the constraints on genes from the statistical interaction of their loci and further using curated protein interaction networks narrowed down the number of candidate genes controlling miRNAs to a set of several genes. Among the resulting interaction pairs were the genes COMMD3 and COPS5 found to regulate the expression of miR-501-5p. Independently, a network analysis based on co-expression of miRNAs was performed using WGCNA (weighted gene co-expression analysis) to identify clusters (modules) of co-expressed miRNAs. One of these modules significantly correlated with the onset and severity of epidermolysis bullosa acquisita, a cutaneous autoimmune skin blistering disease induced by autoantibodies to type VII collagen. The key miRNAs identified from this analysis were miR-379 and miR-223.This work shows strong evidence for a genetic control of cutaneous miRNA expression. 100 murine skin samples
2014-12-18 | E-GEOD-64276 | biostudies-arrayexpress
Project description:Schmitz2014 - RNA triplex formation
The model is parameterized using the
parameters for gene CCDC3 from Supplementary Table S1. The two
miRNAs which form the triplex together with CCDC3 are miR-551b and
miR-138.
This model is described in the article:
Cooperative gene regulation
by microRNA pairs and their identification using a
computational workflow.
Schmitz U, Lai X, Winter F,
Wolkenhauer O, Vera J, Gupta SK.
Nucleic Acids Res. 2014 Jul; 42(12):
7539-7552
Abstract:
MicroRNAs (miRNAs) are an integral part of gene regulation
at the post-transcriptional level. Recently, it has been shown
that pairs of miRNAs can repress the translation of a target
mRNA in a cooperative manner, which leads to an enhanced
effectiveness and specificity in target repression. However, it
remains unclear which miRNA pairs can synergize and which genes
are target of cooperative miRNA regulation. In this paper, we
present a computational workflow for the prediction and
analysis of cooperating miRNAs and their mutual target genes,
which we refer to as RNA triplexes. The workflow integrates
methods of miRNA target prediction; triplex structure analysis;
molecular dynamics simulations and mathematical modeling for a
reliable prediction of functional RNA triplexes and target
repression efficiency. In a case study we analyzed the human
genome and identified several thousand targets of cooperative
gene regulation. Our results suggest that miRNA cooperativity
is a frequent mechanism for an enhanced target repression by
pairs of miRNAs facilitating distinctive and fine-tuned target
gene expression patterns. Human RNA triplexes predicted and
characterized in this study are organized in a web resource at
www.sbi.uni-rostock.de/triplexrna/.
This model is hosted on
BioModels Database
and identified by:
BIOMD0000000530.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
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.
2024-09-02 | BIOMD0000000530 | BioModels
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2020-07-07 | PXD014261 | 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.\
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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:MicroRNAs (miRNAs) post-transcriptionally regulate gene expression by inhibiting protein synthesis of target messenger RNAs (mRNAs). MicroRNA-142 (miR-142), which has tumor-suppressive properties, was functionally deleted by CRISPR/Cas9 knockout in cell lines derived from diffuse large B-cell lymphoma (DLBCL), a highly aggressive tumor that represents about 30% of non-Hodgkin lymphoma worldwide. Mutations in miR-142 affect about 20% of all cases of DLBCL. By proteome analyses, the miR-142 knockout resulted in a consistent up-regulation of 52 but also down-regulation of 41 proteins in the GC-DLBCL lines BJAB and SUDHL4. Various mitochondrial ribosomal proteins were up-regulated in line with their pro-tumorigenic properties, while proteins necessary for MHC-I presentation were down-regulated in accordance with the finding that miR-142 knockout mice have a defective immune response. Of the deregulated proteins/genes, CFL2, CLIC4, STAU1, and TWF1 are known targets of miR-142, and we could additionally confirm AKT1S1, CCNB1, LIMA1, and TFRC as new targets of miR-142-3p or -5p. We further show that seed-sequence mutations of miR-142 can be used to confirm potential targets and that miRNA knockout cell lines might thus be used to identify novel targets of miRNAs. Due to the complex contribution of miRNAs within cellular regulatory networks, in particular when a miRNA highly present in the RISC complex is deleted and can be replaced by other endogenous miRNAs, primary effects on gene expression may be covered by secondary layers of regulation
2023-03-10 | PXD037148 | Pride
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 (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
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 (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