Muscle miRNAs are influenced by sex at baseline and in response to exercise
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE242861 | GEO | 2023/10/05
REPOSITORIES: GEO
Similar Datasets
Project description:iPSC-derived neurons were treated with mimics and inhibitors of the miRNAs miR-150-5p, hsa-mir-193a-3p and hsa-miR-19b-3p.
RNA-sequencing was then performed to examine the effects of miRNA up-regulation and inhibition.
| EGAD00001006844 | EGA
Project description:Background: Laryngeal squamous cell carcinoma (LSCC) is the most common type in head and neck squamous cell carcinoma (HNSCC), and the development of LSCC are multistep processes accompanied by changes of molecular biology. Objective: The purpose of this study was to investigate the miRNAs basis of tumorigenesis in LSCC, and analyze the microRNAs dysregulation related with the six targeted genes (CDK1,CDK2, CDK4, MCM2, MCM3, MCM4) which were related to tumorigenesis from the screened miRNAs. Methods: A total number of 5 patients who underwent surgery for primary laryngeal squamous cell carcinoma were recruited for miRNA array analysis. LSCC tissues compared with corresponding adjacent non-neoplastic tissues were analysed by the Affymetrix GeneChip miRNA Array 3.0 to screen effective miRNAs, then mirfocus 3.0 database (http://mirfocus.org/index.php) was adopted to select putative regulated miRNAs of the six targeted genes. Moreover, the selected putative regulated miRNAs were also validated by qRT-PCR in another 36 patients diagnosed for LSCC. Results: Analysed by the miRNAs arrays, there were 127 miRNAs significantly related to tumorigenesis ,and 78 showed a higher expression in tumor than in non-tumor tissue while 49 presented the contrasting pattern(P<0.01).Then analyzed by mirfocus 3.0 database, there were 2 putative regulated miRNAs, hsa-miR-24-3p and hsa-miR-183-5p, corresponding to three of the six targeted genes. Among the 2 putative miRNAs, hsa-miR-24-3p regulated MCM4,CDK1 and CDK4,while hsa-miR-183-5p regulated MCM4 only. Another miRNA we should focus on is hsa-miR-30a-5p, a tumor-suppressive factor, which was down-expressed obviously analysed by the miRNAs arrays. The expression of the 3 putative regulated miRNAs were also validated by qRT-PCR in another 36 patients (P<0.05). Conclusions: The research revealed 127 miRNAs expression signature of tumorigenesis in laryngeal squamous cell carcinoma,and analyzed 3 putative regulated miRNAs, hsa-miR-24-3p, hsa-miR-183-5p and hsa-miR-30a-5p, as potential diagnostic and therapeutic markers in LSCC. The result will contribute to the understanding of the molecular basis of LSCC and help to improve the treatment.
2014-10-30 | GSE62819 | GEO
Project description:Microglia were derived from iPSCs and treated with mimics and inhibitors of the miRNAs hsa-miR-150-5p, hsa-miR-193a-3p and hsa-miR-19b-3p. RNA-sequencing was then performed to examine the effects of up- and down-regulation of the respective miRNAs.
| EGAD00001006842 | EGA
Project description:Background. Human Metapneumovirus (HMPV) and Respiratory Syncytial Virus (RSV), are responsible for respiratory diseases mostly in children. In spite of the resemblance between these two pneumoviruses, they elicit a different extent of immune response. miRNAs are small non coding RNAs that regulate gene expression and are involved in numerous cellular processes including the immune system. Methodology. Human monocyte-derived dendritic cells (moDC) were differentiated from peripheral blood mononuclear cells and infected at an MOI of 3 for 24h. RNA was isolated to analyze the miRNAs transcription by high throughput sequencing using illumina technology. Principal findings. Infection with HMPV up-regulated the expression of hsa-miR-4448, while RSV infection induced significant expression of hsa-miR-30a-5p, hsa-miR-182-5p, hsa-miR-1913, hsa37, miR-4448 and hsa-miR-4634. Conclusions/Significance. In human monocyte derived dendritic cells (moDC), RSV and HMPV induced different profiles of miRNA expression. Understanding the changes of miRNA expression profiles by RSV and HMPV in immune cells will further our understanding of the differential immune response induced by these respiratory viruses
2018-12-10 | GSE111732 | 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 (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: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:Studies of the miRNA expression profiles associated with the postnatal late growth, development and aging of skeletal muscle are lacking in sika deer. To understand the molecular mechanisms of the growth and development of sika deer skeletal muscle, we used de novo RNA-seq analyses to determine the differential expression of miRNAs from skeletal muscle tissues at 1, 3, 5, and 10-year-old in sika deer. A total of 171 known miRNAs and 60 novel miRNAs were identified based on four small RNA libraries. 11 miRNAs were differentially expressed between adolescence and juvenile sika deer, 4 miRNAs were differentially expressed between adult and adolescence sika deer, and 1 miRNAs were differentially expressed between aged and adult sika deer. GO and KEGG analyses showed that miRNA were mainly related to energy and substance metabolism, processes that are closely associate with growth, development and aging of skeletal muscle. We also constructed mRNA-mRNA and miRNA-mRNA interaction networks related to growth, development and aging of skeletal muscle. The results showed that miR-133a, miR-133c, miR-192, miR-151-3p etc. may play important roles in muscle growth and development, and miR-17-5p, miR-378b, miR-199a-5p, miR-7 etc. may have key roles in muscle aging. In this study, we determined the dynamic miRNA in muscle tissue for the first time in sika deer. The age-dependent miRNAs identified will offer insights into the molecular mechanism underlying muscle development, growth and maintenance and also provide valuable information for sika deer genetic breeding.
2020-01-11 | GSE142978 | GEO