Dynamic microRNA regulatory networks in establishing the Cellular specificity of developing human brains (mRNA-seq)
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE107467 | GEO | 2018/11/21
REPOSITORIES: GEO
Similar Datasets
Project description:MicroRNAs (miRNAs) regulate many neurodevelopmental events, including proliferation, neurogenesis, neuronal migration, and cell survival. Individual miRNAs interact with hundreds of mRNA transcripts, but the precise landscape of these interactions in the context of cell-type-specificity has not been determined. Here, we used multiple parallel approaches, including AGO2-HITS-CLIP, combined mRNA and miRNA single-cell profiling and bipartite network analysis, to reveal a non-uniformity of miRNA-mRNA interactions that supports both defined cell-type identities as well as their dynamic transitions during human brain development at stages of peak neurogenesis. miRNA-mRNA clusters dynamically exploit the redundancy of the miRNA target code to differentially cluster across transitions in brain development. Using cell-type-specific functional properties of miRNA-mRNA interactions, we identify the role of great ape-specific miR-2115 in regulating cortical progenitor cell proliferation by targeting a radial glia enriched gene, origin recognition complex subunit 4 (ORC4). Together, our study suggests that miRNAs contribute to cell identity by regulating the expression of cell-type-specific transcripts.
2018-11-21 | GSE107466 | GEO
Project description:Acute pulmonary embolism (APE) remains among the most formidable challenges facing public health practice in the 21st century. Accurate diagnosis of APE is severely hindered by the lack of biomarkers with both high sensitivity and specificity. MicroRNAs (miRNAs) involve various pathophysiologic processes underlying multitudinous diseases. Accmulating evidences point to the fact that miRNAs may serve as ideal biomarkers.The aim of the present study was to explore the potential of plasma miRNAs as biomarkers for diagnosis of APE. Two TaqMan miRNA arrays were performed on plasma of 10 APE patients and 10 healthy controls.
2013-08-08 | E-GEOD-24149 | biostudies-arrayexpress
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
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:As the fetal heart develops, cardiomyocyte proliferation potential decreases while fatty acid oxidative capacity increases, a highly regulated transition known as cardiac maturation. Small noncoding RNAs, such as microRNAs (miRNAs), contribute to the establishment and control of tissue-specific transcriptional programs. However, small RNA expression dynamics and genome wide miRNA regulatory networks controlling maturation of the human fetal heart remain poorly understood. Transcriptome profiling of small RNAs revealed the temporal expression patterns of miRNA, piRNA, circRNA, snoRNA, snRNA and tRNA in the developing human heart between 8 and 19 weeks of gestation. Our analysis revealed that miRNAs were the most dynamically expressed small RNA species throughout mid-gestation. Cross-referencing differentially expressed miRNAs and mRNAs predicted 6,200 mRNA targets, 2134 of which were upregulated and 4066 downregulated as gestation progresses. Moreover, we found that downregulated targets of upregulated miRNAs predominantly control cell cycle progression, while upregulated targets of downregulated miRNAs are linked to energy sensing and oxidative metabolism. Furthermore, integration of miRNA and mRNA profiles with proteomes and reporter metabolites revealed that proteins encoded in mRNA targets, and their associated metabolites, mediate fatty acid oxidation and are enriched as the heart develops.This study revealed the small RNAome of the maturing human fetal heart. Furthermore, our findings suggest that coordinated activation and repression of miRNA expression throughout mid-gestation is essential to establish a dynamic miRNA-mRNA-protein network that decreases cardiomyocyte proliferation potential while increasing the oxidative capacity of the maturing human fetal heart.
2024-01-26 | PXD044936 | Pride
Project description:miRNAs are short regulatory single stranded RNA sequences that upon complementary binding to mRNAs lead to the inhibition or degradation of their targets. This regulatory mechanisms has been shown to play crucial roles throughout the whole life cycle of animals and plants as well as in disease. While a plethora of methods exist to predict targets of miRNA, which suggest that up to 80% of the genome is miRNA regulated, it has recently been reported that many of these predictions are false positives, cell type specific or represent non-functional binding. In order to identify the subset of real functional miRNAs and their targets, we established miRNA pathway mutants in mouse embryonic stem cells (mESC), allowing the dissection of canonical and non-canonical functions of pathway members. Additional data integration of downstream regulatory layers (CLIP-seq, ribosome profiling and MS) enabled us to follow and track down real functional miRNA-gene interactions, which reduced the miRNA genome regulation to approximately 1%.
2022-08-31 | PXD014484 | Pride
Project description:Neural stem cell regulation is essential for the formation of the central nervous system and homeostatic neurogenesis in the adult mammalian brain. The RNAseIII Drosha, a key component of the miRNA microprocessor, plays a central role in regulating NSC maintenance partially through a miRNA-independent mechanism. Drosha controls mRNA expression levels by targeting and cleaving evolutionary conserved stem-loop hairpins located in the mRNAs of stem cell-related transcription factors. However, it is unknown how the Drosha-mediated endonucleolytic cleavage of mRNA is regulated. Here, we identify novel Drosha and NFIB interactors in hippocampal NSCs by in vitro pull-down assays followed by Mass Spectrometry. We unravel the RNA binding proteins implicated in Drosha-mediated regulation of neurogenesis and we find Scaffold Attachment Factor B1 to play a novel and essential role in NFIB mRNA regulation during neural stem cell differentiation.
2024-06-03 | PXD017677 | Pride