Project description:The expression of Glis3 in C3H10T1/2 cells promotes osteoblastic differentiation as indicated by the the induction of increase in alkaline phosphatase activity, an early marker of osteoblast differentiation, and increased expression of osteopontin, a late marker of osteogenesis. Glis3 acts synergistically with bone morphogenic protein 2 (BMP-2). In contrast, expression of Glis3 inhibits the induction of adipocyte differentiation. Microarray analysis identified the fibroblast growth factor 18 (FGF18) as one of the genes induced by Glis3 in C3H10T1/2 cells directly. Keywords: Glis3, osteoblast differentiation, adipocyte differentiation, FGF18, BMP2
Project description:Extensive changes in post-translational histone modifications accompany the rewiring of the transcriptional program during stem cell differentiation. However, the mechanisms controlling the changes in specific chromatin modifications and their function during differentiation remain only poorly understood. We show that histone H2B monoubiquitination (H2Bub1) significantly increases during differentiation of human mesenchymal stem cells (hMSCs), various lineage-committed precursor cells and in diverse organisms. Furthermore, the H2B ubiquitin ligase RNF40 is required for the induction of differentiation markers and transcriptional reprogramming of hMSC. This function is dependent upon CDK9 and the WAC adaptor protein, which are required for H2B monoubiquitination. Finally, we show that RNF40 is required for the resolution of the H3K4me3/H3K27me3 bivalent poised state on lineage-specific genes during the transition from an inactive to active chromatin conformation. Thus, these data indicate that H2Bub1 is required for maintaining multipotency of hMSC cells and plays a central role in controlling stem cell differentiation. This set contains 29 microarray samples and includes the following 5 conditions: undifferentiated hMSCs, 2 day osteoblast differentiation, 5 day osteoblast differentiation, 2 day adipocyte differentiation, and 5 day adipocyte differentiation. 3 siRNA control samples and 3 RNF40 knockdown samples for each condition (except two control siRNA samples for 2 days osteoblast differentiation).
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.
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.