Dynamic time course mRNA profiling of human skeletal muscle cell differentiation.
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE53382 | GEO | 2014/12/13
SECONDARY ACCESSION(S): PRJNA231875
REPOSITORIES: GEO
Similar Datasets
Project description:The purpose of this study was to determine the miRNA expression profile of in vitro differentiation of human skeletal muscle cells and to couple changes in individual miRNA expression to effects on target genes by transcriptome profiling of mRNA expression. mRNA expression profiling at three different time points during the in vitro differentiation process of human skeletal muscle cells from three subjects. RNA was harvested from myoblasts before and 4 and 10 days after induction of differentiation. Temporal, time-course design with paired analysis (3 subjects). Biological replicates: 3 at day 0, 3 at day 4, and 3 at day 10. One replicate per array.
2014-12-13 | E-GEOD-53382 | biostudies-arrayexpress
Project description:The purpose of this study was to determine the miRNA expression profile of in vitro differentiation of human skeletal muscle cells and to couple changes in individual miRNA expression to transcriptional output of target genes. miRNA expression profiling at six different time points during the in vitro differentiation process of human skeletal muscle cells from six subjects. RNA was harvested from myoblasts before induction of differentiation and at every other day for 10 following days.
2014-12-13 | GSE53383 | GEO
Project description:The purpose of this study was to determine the miRNA expression profile of in vitro differentiation of human skeletal muscle cells and to couple changes in individual miRNA expression to transcriptional output of target genes. miRNA expression profiling at six different time points during the in vitro differentiation process of human skeletal muscle cells from six subjects. RNA was harvested from myoblasts before induction of differentiation and at every other day for 10 following days. Temporal, time-course design with paired analysis (6 subjects). Biological replicates: 6 at day 0, 6 at day 2, 6 at day 4, 6 at day 6, 6 at day 8, and 5 at day 10. One replicate vs common reference RNA pool per array.
2014-12-13 | E-GEOD-53383 | biostudies-arrayexpress
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 (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 (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:miR-206, miR-1a-1 and miR-1a-2, foundational members of the myomir family, promote skeletal muscle differentiation and have complete identity in the seed sequence, suggesting functional redundancy. To test if the essential role of these three microRNAs in skeletal myogenesis was masked by redundant function of at least one of the three miRNA left in the cells in previous reports, we generated triple KO (tKO) C2C12 cells by CRISPR/Cas9 (in vitro) and triple KO mice (in vivo model). tKO myoblasts differentiate, producing similar levels of promyogenic mRNAs and normal fusion index. RNAseq analysis confirms tKO clones differentiate but also reveals decrease in mRNA levels of genes related to mitochondrial oxidative phosphorylation. Dimished mitochondria function in tKO cells was confirmed using Seahorse assay. The targets of miR-206/-1a are specifically upregulated during differentiation of tKO myoblasts, when the microRNAs are normally induced, confirming the complete loss of the three microRNA genes. Although we observe partial embryonic lethality of tKO mice, the live mice grow normally to adulthood, have the same size of skeletal muscles as control animals, but perform worse on physical activity tests, which may be partially explained by smaller skeletal muscle fiber diameters. Thus these three myomiRs are not essential for skeletal muscle differentiation but are required for optimal differentiation and provide a clear example of the microRNAs not being a switch but a modulator of differentiation.
2020-04-15 | GSE133255 | GEO
Project description:miR-206, miR-1a-1 and miR-1a-2, foundational members of the myomir family, promote skeletal muscle differentiation and have complete identity in the seed sequence, suggesting functional redundancy. To test if the essential role of these three microRNAs in skeletal myogenesis was masked by redundant function of at least one of the three miRNA left in the cells in previous reports, we generated triple KO (tKO) C2C12 cells by CRISPR/Cas9 (in vitro) and triple KO mice (in vivo model). tKO myoblasts differentiate, producing similar levels of promyogenic mRNAs and normal fusion index. RNAseq analysis confirms tKO clones differentiate but also reveals decrease in mRNA levels of genes related to mitochondrial oxidative phosphorylation. Dimished mitochondria function in tKO cells was confirmed using Seahorse assay. The targets of miR-206/-1a are specifically upregulated during differentiation of tKO myoblasts, when the microRNAs are normally induced, confirming the complete loss of the three microRNA genes. Although we observe partial embryonic lethality of tKO mice, the live mice grow normally to adulthood, have the same size of skeletal muscles as control animals, but perform worse on physical activity tests, which may be partially explained by smaller skeletal muscle fiber diameters. Thus these three myomiRs are not essential for skeletal muscle differentiation but are required for optimal differentiation and provide a clear example of the microRNAs not being a switch but a modulator of differentiation.
2020-04-15 | GSE133260 | GEO