Allelic imbalance sequencing reveals that single-nucleotide polymorphisms frequently alter microRNA-directed repression
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE15675 | GEO | 2009/04/26
SECONDARY ACCESSION(S): PRJNA115619
REPOSITORIES: GEO
Similar Datasets
Project description:Genetic changes that help explain the differences between two individuals might create or disrupt sites complementary to microRNAs (miRNAs), but the extent to which such polymorphic sites influence miRNA-mediated repression is unknown. Here, we describe a method to measure mRNA allelic imbalances associated with a regulatory site found in mRNA transcribed from one allele but not found in that transcribed from the other. Applying this method, called allelic imbalance sequencing, to sites for three miRNAs (miR-1, miR-133 and miR-122) provided quantitative measurements of repression in vivo without altering either the miRNAs or their targets. A substantial fraction of polymorphic sites mediated repression in tissues that expressed the cognate miRNA, and downregulation was correlated with site type and site context. Extrapolating these results to the other broadly conserved miRNAs suggests that when comparing two mouse strains (or two human individuals), polymorphic miRNA sites cause expression of many genes (often hundreds) to differ. There are four distinct samples (pool1-4), each of which is a pool of ~60 distinct PCR or RT-PCR products. The samples were loaded into different segments of the same pyrosequencing plate. Three sequencing runs (run1-3) were performed for each sample pool. Any amplicons of the four pools are for miR-1, miR-122, miR-133 or control sites. To control for allele-specific PCR bias, genomic DNA was also used as a template for generating amplicons.
2009-04-26 | E-GEOD-15675 | 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
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 (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
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:Expression changes of competitive endogenous RNAs (ceRNAs) have been proposed to influence microRNA (miRNA) activity and thereby regulate other transcripts that contain miRNA binding sites. Here, we find that although miRNA levels define the extent of repression, they do not affect the magnitude of the ceRNA expression change required to observe derepression. Canonical 6-nt sites, which typically mediate modest repression, can nonetheless compete for miRNA binding, with potency ~20% of that observed for canonical 8-nt sites. Sites with extensive additional complementarity can be even more potent, but this occurs predominantly through miRNA degradation rather than competition. Cooperative binding of closely spaced sites for different miRNAs can also increase potency. These results provide quantitative insights into the stoichiometric relationship between miRNA and target abundance, target-site spacing and affinity requirements for ceRNA-mediated gene regulation and specify the unusual circumstances in which ceRNA-mediated gene regulation might be observed. Sixty-four mRNA profiles were generated of 1) primary hepatocytes of mice expressing variable levels of a recombinant Adenovirus expressing the transcript of AldolaseA (Ad-AldoA), containing sites matching miR-122, let-7, miR-192, miR-194 or a mutated site (no site) or 2) embryonic stem (ES) cells that were transfected with a Tet-inducible dual-color reporter construct expressing enhanced yellow fluorescent protein (eYFP) and mCherry that contains zero (0s) or three (3s) 8 nt miRNA seed matches for miR-293 or miR-92 in the 3� UTR. ES cells were sorted with a FACSAria IIIu flow cytometer into three bins based on their eYFP fluorescence intensity. All samples were sequenced in duplicates by an Illumina HiSeq 2500. Library preparation and sequencing were performed by Fasteris SA (Switzerland) or by the Functional Genomics Centre Zürich (FGCZ). Three small RNA profiles or either primary hepatocytes or embryonic stem cells were also generated by Solexa sequencing.
2016-10-27 | E-GEOD-76288 | biostudies-arrayexpress
Project description:Cancer cachexia is a multifactorial metabolic syndrome defined by the rapid loss of skeletal muscle mass and the loss of fat mass. Up 80% of cancer patients at the late stage with cachexia suffer from progressive atrophy of adipose tissue. Unlike studies on skeletal muscle wasting, there is limited research on fat loss in cachexia. It was noted that most patients suffer from fat loss as cancer progress. Fat loss precedes muscle loss, is associated with shorter survival, and is variable to timing and intensity in various cancer populations. Increased lipolysis may be the leading cause of fat loss in cancer cachexia. miRNAs are a class of non-coding RNAs of 19~25 nucleotides that regulate gene silencing by interacting with the 3’ untranslated region (UTR) of target mRNA to cause mRNA degradation and translational repression. miRNAs play multifaceted roles in pancreatic cancer proliferation, survival, metastasis, and chemoresistance. Aberrant expression of miRNA in circulating exosomes may play potential roles in modulating fat loss in cancer cachexia. We identified 2 miRNAs, miR-16 and miR-29, which have 2-fold higher expression existed in at PDAC cells. To explore which genes in adipogenesis and lipolysis were directly affected by miR-16-5p or/and miR-29a-3p, we analyzed the targets which were down-regulated in both miR-16-5p and miR-29a-3p-transfected 3T3-L1 cells by mass analysis.
2024-06-13 | PXD037998 | Pride
Project description:Cancer cachexia is a multifactorial metabolic syndrome defined by the rapid loss of skeletal muscle mass and the loss of fat mass. Up 80% of cancer patients at the late stage with cachexia suffer from progressive atrophy of adipose tissue. Unlike studies on skeletal muscle wasting, there is limited research on fat loss in cachexia. It was noted that most patients suffer from fat loss as cancer progress. Fat loss precedes muscle loss, is associated with shorter survival, and is variable to timing and intensity in various cancer populations. Increased lipolysis may be the leading cause of fat loss in cancer cachexia. miRNAs are a class of non-coding RNAs of 19~25 nucleotides that regulate gene silencing by interacting with the 3’ untranslated region (UTR) of target mRNA to cause mRNA degradation and translational repression. miRNAs play multifaceted roles in pancreatic cancer proliferation, survival, metastasis, and chemoresistance. Aberrant expression of miRNA in circulating exosomes may play potential roles in modulating fat loss in cancer cachexia. We identified 2 miRNAs, miR-16 and miR-29, which have 2-fold higher expression existed in at PDAC cells. To explore which genes in adipogenesis and lipolysis were directly affected by miR-16-5p or/and miR-29a-3p, we analyzed the targets which were down-regulated in both miR-16-5p and miR-29a-3p-transfected 3T3-L1 cells by mass analysis.
2024-06-13 | PXD037862 | Pride