Genome Scale Analysis of miRNA and mRNA regulation during preterm labor [whole blood]
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE96083 | GEO | 2018/03/01
REPOSITORIES: GEO
Similar Datasets
Project description:The goal of this study was to define relationships between peripheral blood miRNAs and mRNAs of women undergoing idiopathic preterm labor (PTL) and compare network level changes to control women that deliver at term.Using RNA Sequencing we have performed global miRNA and mRNA profiling in both monocytes and whole blood leukocytes of women who underwent PTL (N=15) matched to non-pathological controls (N=30) as a part of the Ontario Birth Study cohort. We have identified differentially expressed miRNAs, mRNAs and pathways associated with PTL. Intriguingly, we found perturbations in many cellular signaling pathways, particularly in interleukin signaling. We also predicted mRNA targets for specific miRNAs and used these predictions to build putative miRNA-mRNA networks. We identified 6 miRNAs significantly associated with PTL whose expression is negatively correlated with expression of 14 predicted mRNA targets that are also significantly associated with PTL.
2018-03-01 | GSE96077 | GEO
Project description:The goal of this study was to define relationships between peripheral blood miRNAs and mRNAs of women undergoing idiopathic preterm labor (PTL) and compare network level changes to control women that deliver at term.Using RNA Sequencing we have performed global miRNA and mRNA profiling in both monocytes and whole blood leukocytes of women who underwent PTL (N=15) matched to non-pathological controls (N=30) as a part of the Ontario Birth Study cohort. We have identified differentially expressed miRNAs, mRNAs and pathways associated with PTL.
2019-03-31 | GSE108877 | GEO
Project description:The goal of this study was to define relationships between peripheral blood miRNAs and mRNAs of women undergoing idiopathic preterm labor (PTL) and compare network level changes to control women that deliver at term.Using RNA Sequencing we have performed global miRNA and mRNA profiling in both monocytes and whole blood leukocytes of women who underwent PTL (N=15) matched to non-pathological controls (N=30) as a part of the Ontario Birth Study cohort. We have identified differentially expressed miRNAs, mRNAs and pathways associated with PTL.
2019-03-31 | GSE108876 | GEO
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:The maintenance of coordinated powerful episodic contractions of the uterus is the crucial factor for normal labor. The uterine contractility is gradually enhanced with the progression of labor, which is related to the gene expression of myometrium, competing endogenous RNA (ceRNA) can also regulate the gene expression. To better understand the role of ceRNA network in labor, transcriptome sequencing was performed on the myometrium of 17 parturients at different labor duration. Furthermore, an correlated analysis was performed to identify mRNA, long non-coding RNA (lncRNA), circular RNA (circRNA), and microRNA (miRNA) which correlated with their expression levels and labor duration. Then, targeting relationships between mRNAs, lncRNAs, circRNAs and miRNAs were predicted, and the ceRNA regulatory network was established.This analysis identified 934 RNAs positively correlated with labor duration (859 mRNAs, 28 lncRNAs, 45 circRNAs, and 2 miRNAs) and 153 RNAs negatively correlated with labor duration (122 mRNAs, 28 lncRNAs, and 3 miRNAs).
2022-01-01 | GSE188407 | GEO
Project description:The maintenance of coordinated powerful episodic contractions of the uterus is the crucial factor for normal labor. The uterine contractility is gradually enhanced with the progression of labor, which is related to the gene expression of myometrium, competing endogenous RNA (ceRNA) can also regulate the gene expression. To better understand the role of ceRNA network in labor, transcriptome sequencing was performed on the myometrium of 17 parturients at different labor duration. Furthermore, an correlated analysis was performed to identify mRNA, long non-coding RNA (lncRNA), circular RNA (circRNA), and microRNA (miRNA) which correlated with their expression levels and labor duration. Then, targeting relationships between mRNAs, lncRNAs, circRNAs and miRNAs were predicted, and the ceRNA regulatory network was established.This analysis identified 934 RNAs positively correlated with labor duration (859 mRNAs, 28 lncRNAs, 45 circRNAs, and 2 miRNAs) and 153 RNAs negatively correlated with labor duration (122 mRNAs, 28 lncRNAs, and 3 miRNAs).
2022-01-01 | GSE188873 | GEO
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