Project description:This SuperSeries is composed of the following subset Series: GSE29182: Identification of active microRNA/transcription factor feed-forward loops during human adipogenesis (mRNA) GSE29185: Identification of active microRNA/transcription factor feed-forward loops during human adipogenesis (miRNA) Refer to individual Series
Project description:Post-transcriptional regulation of gene expression accomplished by microRNAs (miRNAs) importantly affects the complex gene regulatory network. In particular, miRNAs are known to be involved in recurrent motifs named miRNA-mediated feed forward loops (FFLs) where a transcription factor (TF) regulates a miRNA and they both regulate the expression level of a target RNA. Here, we focus on the identification of active FFLs during adipogenic differentiation. A list of putative feed-forward loops was generated based on sequence analysis of conserved and overrepresented motifs in the regulatory regions. Since this approach is not specific for adipogenesis and is known to generate false positive feed-forward loops, an experiment was designed to select active ones based on their dynamics using a model-based approach. Microarray time series of gene and miRNA expression data were collected at seven time points on human multipotent adipose-derived stem (hMADS) cells upon adipogenic differentiation. Three different dynamic models, sharing the same FFL topology but incorporating descriptions of increasing complexity of miRNA and mRNA dynamics, are identified on miRNA and mRNA expression data and compared based on identification criteria, namely: goodness of fit, precision of the estimates and comparison with submodels. 24 FFLs, able to properly reproduce data, are selected as active out of the 329 putative ones. This method considerably reduces the search space for new interactions between TFs, miRNAs and mRNAs and provides interesting biological results identifying genes known from the literature to be regulators in adipogenesis and adipocyte-related functions that can be interpreted as positive control of the validity of the apporoach. Therefore, the genes in the selected FFLs that are not yet known to be involved in this context are potential novel players in this regulatory network of adipogenesis and adipocyte function. Two independent cell culture experiments were performed as biological replicates during adipogenic differentiation of human mesenchymal stem cell. Cells where harvested at the pre-confluent stage as reference (day -3) and at seven subsequent time points during human adipogenic differentiation: day -2 and 0 before, and 1, 2, 5, 10, 15 days after induction of differentiation. All hybridizations were repeated with reversed dye assignment (dye-swap).
Project description:Post-transcriptional regulation of gene expression accomplished by microRNAs (miRNAs) importantly affects the complex gene regulatory network. In particular, miRNAs are known to be involved in recurrent motifs named miRNA-mediated feed forward loops (FFLs) where a transcription factor (TF) regulates a miRNA and they both regulate the expression level of a target RNA. Here, we focus on the identification of active FFLs during adipogenic differentiation. A list of putative feed-forward loops was generated based on sequence analysis of conserved and overrepresented motifs in the regulatory regions. Since this approach is not specific for adipogenesis and is known to generate false positive feed-forward loops, an experiment was designed to select active ones based on their dynamics using a model-based approach. Microarray time series of gene and miRNA expression data were collected at seven time points on human multipotent adipose-derived stem (hMADS) cells upon adipogenic differentiation. Three different dynamic models, sharing the same FFL topology but incorporating descriptions of increasing complexity of miRNA and mRNA dynamics, are identified on miRNA and mRNA expression data and compared based on identification criteria, namely: goodness of fit, precision of the estimates and comparison with submodels. 24 FFLs, able to properly reproduce data, are selected as active out of the 329 putative ones. This method considerably reduces the search space for new interactions between TFs, miRNAs and mRNAs and provides interesting biological results identifying genes known from the literature to be regulators in adipogenesis and adipocyte-related functions that can be interpreted as positive control of the validity of the apporoach. Therefore, the genes in the selected FFLs that are not yet known to be involved in this context are potential novel players in this regulatory network of adipogenesis and adipocyte function. Two independent cell culture experiments were performed as biological replicates during adipogenic differentiation of human mesenchymal stem cell. Cells where harvested at the pre-confluent stage as reference (day -3) and at seven subsequent time points during human adipogenic differentiation: day -2 and 0 before, and 1, 2, 5, 10, 15 days after induction of differentiation. All hybridizations were repeated with reversed dye assignment (dye-swap).
Project description:Post-transcriptional regulation of gene expression accomplished by microRNAs (miRNAs) importantly affects the complex gene regulatory network. In particular, miRNAs are known to be involved in recurrent motifs named miRNA-mediated feed forward loops (FFLs) where a transcription factor (TF) regulates a miRNA and they both regulate the expression level of a target RNA. Here, we focus on the identification of active FFLs during adipogenic differentiation. A list of putative feed-forward loops was generated based on sequence analysis of conserved and overrepresented motifs in the regulatory regions. Since this approach is not specific for adipogenesis and is known to generate false positive feed-forward loops, an experiment was designed to select active ones based on their dynamics using a model-based approach. Microarray time series of gene and miRNA expression data were collected at seven time points on human multipotent adipose-derived stem (hMADS) cells upon adipogenic differentiation. Three different dynamic models, sharing the same FFL topology but incorporating descriptions of increasing complexity of miRNA and mRNA dynamics, are identified on miRNA and mRNA expression data and compared based on identification criteria, namely: goodness of fit, precision of the estimates and comparison with submodels. 24 FFLs, able to properly reproduce data, are selected as active out of the 329 putative ones. This method considerably reduces the search space for new interactions between TFs, miRNAs and mRNAs and provides interesting biological results identifying genes known from the literature to be regulators in adipogenesis and adipocyte-related functions that can be interpreted as positive control of the validity of the apporoach. Therefore, the genes in the selected FFLs that are not yet known to be involved in this context are potential novel players in this regulatory network of adipogenesis and adipocyte function.
Project description:Post-transcriptional regulation of gene expression accomplished by microRNAs (miRNAs) importantly affects the complex gene regulatory network. In particular, miRNAs are known to be involved in recurrent motifs named miRNA-mediated feed forward loops (FFLs) where a transcription factor (TF) regulates a miRNA and they both regulate the expression level of a target RNA. Here, we focus on the identification of active FFLs during adipogenic differentiation. A list of putative feed-forward loops was generated based on sequence analysis of conserved and overrepresented motifs in the regulatory regions. Since this approach is not specific for adipogenesis and is known to generate false positive feed-forward loops, an experiment was designed to select active ones based on their dynamics using a model-based approach. Microarray time series of gene and miRNA expression data were collected at seven time points on human multipotent adipose-derived stem (hMADS) cells upon adipogenic differentiation. Three different dynamic models, sharing the same FFL topology but incorporating descriptions of increasing complexity of miRNA and mRNA dynamics, are identified on miRNA and mRNA expression data and compared based on identification criteria, namely: goodness of fit, precision of the estimates and comparison with submodels. 24 FFLs, able to properly reproduce data, are selected as active out of the 329 putative ones. This method considerably reduces the search space for new interactions between TFs, miRNAs and mRNAs and provides interesting biological results identifying genes known from the literature to be regulators in adipogenesis and adipocyte-related functions that can be interpreted as positive control of the validity of the apporoach. Therefore, the genes in the selected FFLs that are not yet known to be involved in this context are potential novel players in this regulatory network of adipogenesis and adipocyte function.
Project description:Pluripotent stem cells can be isolated from early embryos or induced by cell fusion, somatic nuclear transfer, or expression of a selected set of transcription factors. Embryonic stem (ES) cells are characterized by an open chromatin configuration and high transcription levels achieved via autoregulatory and feed-forward transcription factor loops. How the general transcription machinery is involved in pluripotency is unclear. Here, we show that TFIID knockdown affected the pluripotent circuitry in ES cells and inhibited reprogramming of fibroblasts. TFIID and pluripotency factors form a feed-forward loop to induce and maintain a stable transcription state. Strikingly, transient expression of TFIID subunits greatly enhanced reprogramming by Oct4, Sox2, Klf4 and c-Myc reaching efficiencies upto 50%. These results show that TFIID is a critical and selective component for transcription factor-mediated reprogramming. We anticipate that by creating plasticity in gene expression programs, basal transcription complexes such as TFIID assist reprogramming into different cellular states. Three iPS lines, iPS#1, iPS#4, and iPS#5 were used in duplicate for microarray analysis against a pool of RNA from ES-cells.
Project description:Pluripotent stem cells can be isolated from early embryos or induced by cell fusion, somatic nuclear transfer, or expression of a selected set of transcription factors. Embryonic stem (ES) cells are characterized by an open chromatin configuration and high transcription levels achieved via autoregulatory and feed-forward transcription factor loops. How the general transcription machinery is involved in pluripotency is unclear. Here, we show that TFIID knockdown affected the pluripotent circuitry in ES cells and inhibited reprogramming of fibroblasts. TFIID and pluripotency factors form a feed-forward loop to induce and maintain a stable transcription state. Strikingly, transient expression of TFIID subunits greatly enhanced reprogramming by Oct4, Sox2, Klf4 and c-Myc reaching efficiencies upto 50%. These results show that TFIID is a critical and selective component for transcription factor-mediated reprogramming. We anticipate that by creating plasticity in gene expression programs, basal transcription complexes such as TFIID assist reprogramming into different cellular states. Two Taf5 knockdown cell lines and two control knockdown lines were each grown in duplicate and analysed on microarray against a pool of RNA from the parental ES-cells
Project description:Characterization of pluripotent states, in which cells can both self-renew or differentiate, with the irreversible loss of pluripotency, are important research areas in developmental biology. Although microRNAs (miRNAs) have been shown to be crucial for embryonic stem (ES) self-renewal maintenance and cellular differentiation, the role of miRNAs integrated into gene regulatory networks and its dynamic changes during these state transitions remain elusive. Here we describe the dynamic transcriptional regulatory circuitry of ES cells that incorporate protein-coding and miRNA genes based on microRNA array expression and quantitative sequencing of short transcripts upon the downregulation of the Estrogen Related Receptor Beta (Esrrb). The data reveals how Esrrb, a key stem cell transcription factor, regulates a specific ES cell miRNA expression program and integrates dynamic changes of feed forward loops contributing to the exit of the pluripotency state upon its downregulation. Together these findings provide new insights on the architecture of the combined transcriptional post-transcriptional regulatory network in stem cells.