Expression profiling in four human bladder cancer cell lines
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Yuanbin Ru
PROVIDER: E-MTAB-2610 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:To identify miRNA-target interactions that are important in bladder cancer metastasis, we profiled miRNA and mRNA expression in poorly metastatic cell lines T24 and LUC, and their metastatic derivatives FL4 and LUL2, respectively. We reasoned that miRNAs and genes that expressed differently between parental and derivative cell lines could potentially contribute to their disparity in metastatic competence. We further hypothesized that interactions between these miRNAs and target genes may play an important role in metastatic competence. We have developed the multiMiR R pacakge and database for such integrated analysis of miRNA-target interactions. Here we demonstrate how multiMiR was used to generate testable hypotheses that could be pursued experimentally. The data set here is from the miRNA expression profiling experiment. Please see E-MTAB-2610 ( https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-2610/ ) for the mRNA profiling data set.
2014-07-25 | E-MTAB-2611 | biostudies-arrayexpress
Project description:Proctor2017 - Identifying microRNA for muscle
regeneration during ageing (Mirs_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:
MODEL1704110004.
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 | MODEL1704110004 | 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 (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 (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 (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: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
Project description:We investigated the miRNAome in human melanocyte and melanoma cell lines using high-throughput RNA sequencing. We identified a group of dysregulated miRNAs by comparing the miRNA expression profiles among melanoma cell lines. Target genes of these miRNAs participate in functions associated with the cell cycle and apoptosis. Gene networks were built to investigate the interactions of genes during melanoma progression. We identified that the key genes that regulate melanoma cell proliferation were regulated by miRNAs. Our findings provide further knowledge regarding the mechanisms of melanoma development. miRNA profiles of melanocyte (HEMn-LP), low metastatic melanoma (A375) and high metastatic melanoma (A2058) cell line were generated using Illumina GA
2015-07-13 | E-GEOD-66823 | biostudies-arrayexpress
Project description:Identification of miRNAs that differentially expressed in brain metastatic cells and were predicted to target CDH2. To investigate which miRNAs could regulate CDH2 expression in brain-metastatic lung cancer cells, we examined the miRNA expression profiles in brain-metastatic lung cancer cells and their parental cells using Illumina miRNA microarray. By comparing the endogenous expression of all miRNAs, 146 miRNAs were selected by 2-fold changes in brain-metastatic lung cancer cells. Furthermore, we used several algorithms in miRSystem to predict which miRNA whose target gene was CDH2. There were 44 miRNAs that were predicted to target CDH2. In total, we identified nine miRNAs whose target gene was CDH2 and whose expression was significantly different between the highly metastatic cells and their parental cells (Fig. 2A). Among these miRNAs, four miRNAs were found to be down-regulated and five miRNAs were up-regulated in brain-metastatic lung cancer cells (Fig. 2B).
2016-10-11 | GSE51666 | GEO
Project description:To exert regulatory function, miRNAs guide Argonaute (AGO) proteins to partially complementary sites on target RNAs. Crosslinking and immunoprecipitation (“re state-of-the-art to map AGO binding sites, but assigning the targeting miRNA to these sites relies on bioinformatics predictions and is therefore indirect. To directly and unambiguously identify miRNA:target site interactions, we modified our CLIP methodology in C. elegans to experimentally ligate miRNAs to their target sites. Unexpectedly, ligation reactions also occurred in absence of the exogenous ligase. Our in vivo dataset and re-analysis of published mammalian AGO-CLIP data for miRNA-chimeras yielded >17,000 miRNA:target site interactions. Analysis of interactions and extensive experimental validation of chimera-discovered targets of viral miRNAs suggest that our strategy identifies canonical, non-canonical, and non-conserved miRNA interactions. Our data suggest that ~80% of miRNA:targets have perfect or partial seed complementarity. In summary, analysis of miRNA:target chimeras enables the systematic, context-specific, in vivo discovery of miRNA interactions.
2014-05-23 | GSE56180 | GEO