This SuperSeries is composed of the SubSeries listed below.
Transcriptional network analysis in muscle reveals AP-1 as a partner of PGC-1α in the regulation of the hypoxic gene program.
Specimen part, Treatment
View SamplesSkeletal muscle tissue shows an extraordinary cellular plasticity, but the underlying molecular mechanisms are still poorly understood. Here we use a combination of experimental and computational approaches to unravel the complex transcriptional network of muscle cell plasticity centered on the peroxisome proliferator-activated receptor coactivator 1 (PGC-1), a regulatory nexus in endurance training adaptation. By integrating data on genome-wide binding of PGC-1 and gene expression upon PGC-1 over-expression with comprehensive computational prediction of transcription factor binding sites (TFBSs), we uncover a hitherto underestimated number of transcription factor partners involved in mediating PGC-1 action. In particular, principal component analysis of TFBSs at PGC-1 binding regions predicts that, besides the well-known role of the estrogen-related receptor (ERR), the activator protein-1 complex (AP-1) plays a major role in regulating the PGC-1-controlled gene program of hypoxia response. Our findings thus reveal the complex transcriptional network of muscle cell plasticity controlled by PGC-1.
Transcriptional network analysis in muscle reveals AP-1 as a partner of PGC-1α in the regulation of the hypoxic gene program.
Treatment
View SamplesThe peroxisome proliferator-activated receptor co-activator 1 (PGC-1) coordinates the transcriptional network response to promote an improved endurance capacity in skeletal muscle, e.g. by co-activating the estrogen-related receptor (ERR) in the regulation of oxidative substrate metabolism. Despite a close functional relationship, the interaction between these two proteins has not been studied on a genomic level. We now mapped the genome-wide binding of ERR to DNA in skeletal muscle cell line with elevated PGC-1 and linked the DNA recruitment to global PGC-1 target gene regulation. We found that, surprisingly, ERR co-activation by PGC-1 is only observed in the minority of all PGC-1 recruitment sites. Nevertheless, a majority of PGC-1 target gene expression is dependent on ERR. Intriguingly, the interaction between these two proteins is controlled by the genomic context of response elements, in particular the relative GC and CpG content, monomeric and dimeric repeat binding site configuration for ERR, and adjacent recruitment of the transcription factor SP1. These findings thus not only reveal an unprecedented insight into the regulatory network underlying muscle cell plasticity, but also strongly link the genomic context of DNA response elements to control transcription factor - co-regulator interactions.
The Genomic Context and Corecruitment of SP1 Affect ERRα Coactivation by PGC-1α in Muscle Cells.
Specimen part
View SamplesSkeletal muscle tissue shows an extraordinary cellular plasticity, but the underlying molecular mechanisms are still poorly understood. Here we use a combination of experimental and computational approaches to unravel the complex transcriptional network of muscle cell plasticity centered on the peroxisome proliferator-activated receptor coactivator 1 (PGC-1), a regulatory nexus in endurance training adaptation. By integrating data on genome-wide binding of PGC-1 and gene expression upon PGC-1 over-expression with comprehensive computational prediction of transcription factor binding sites (TFBSs), we uncover a hitherto underestimated number of transcription factor partners involved in mediating PGC-1 action. In particular, principal component analysis of TFBSs at PGC-1 binding regions predicts that, besides the well-known role of the estrogen-related receptor (ERR), the activator protein-1 complex (AP-1) plays a major role in regulating the PGC-1-controlled gene program of hypoxia response. Our findings thus reveal the complex transcriptional network of muscle cell plasticity controlled by PGC-1.
Transcriptional network analysis in muscle reveals AP-1 as a partner of PGC-1α in the regulation of the hypoxic gene program.
No sample metadata fields
View SamplesThis SuperSeries is composed of the SubSeries listed below.
The Genomic Context and Corecruitment of SP1 Affect ERRα Coactivation by PGC-1α in Muscle Cells.
Specimen part
View SamplesPurpose: Here we describe the modulation of a gene expression program involved in cell fate. Methods: We depleted U2AF1 in human induced pluripotent stem cells (hiPSCs) to the level found in differentiated cells using an inducible shRNA system, followed by high-throughput RNAseq, revealing a gene expression program involved in cell fate determination. Results: Approximately 85% of the total raw reads were mapped to the human genome sequence (GRCh37), giving an average of 200 million human reads per sample for total RNA and 15 million human reads per sample for small RNA libraries. Conclusions: Our results show that transcriptional control of gene expression in hiPSCs can be set by the CSF U2AF1, establishing a direct link between transcription and AS during cell fate determination. Overall design: hiPSCs were differentiated into the three germ layers following the described protocol in the study (Gifford et al., 2013).
The core spliceosomal factor U2AF1 controls cell-fate determination via the modulation of transcriptional networks.
No sample metadata fields
View SamplesThe purpose of the experiment was to generate a time course of gene expression following irradiation. The goal was then to model this data to extract hidden variables - chiefly, the activity profiles of the p53 transcription factor. Using this information the aim was to predict which transcripts changed by IR were targets of p53. Cells in log phase (1 x 106 ml-1) were ?-irradiated with 5 Gy at room temperature (RT) at a dose rate of 2.45 Gy per minute with a 137Cs ?-irradiator. Cells were harvested at 0, 2, 4, 6, 8, 10 and 12 hours, and RNA and protein were extracted (Trizol, Invitrogen). Affymetrix U133A arrays were hybridized as standard (www.affymetrix.co.uk). Array quality was determined using R and GCOS .rpt file values. The time course was replicated three times from independent cell preparations.
Ranked prediction of p53 targets using hidden variable dynamic modeling.
Specimen part, Disease, Cell line, Time
View SamplesIn this study we used Genome Wide Transcriptional Modelling (GWTM) to investigate the temporal transcriptional changes during CD4 Th0, Th1 and Th2 differentiation in the first 24 hours after T cell activation. We measured the transcriptional response by RNA seq every four hours for a 24 hour time course. Overall design: WT CD4 T cells were isolated and purified from adult murine spleen. The purified CD4 cells were then set up in culture under three different conditions: Th0, Th1 and Th2. Cells were extracted at 4 hour timepoints during a 24hour timecourse and RNA was extracted for each timepoint under each condition. This RNA was further sequenced to analyse the genome wide transcriptional changes through time under each of the three conditions.
IFITM proteins drive type 2 T helper cell differentiation and exacerbate allergic airway inflammation.
Cell line, Subject
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Vitamin C supplementation modulates gene expression in peripheral blood mononuclear cells specifically upon an inflammatory stimulus: a pilot study in healthy subjects.
Specimen part
View SamplesA role of vitamin C (ascorbic acid) as an antioxidant molecule has been recognized, largely based on in vitro studies. However, more recently, the concept of antioxidant molecule has been reconsidered and its biological function is no longer considered to be simply due to its ability to act as electron donors, rather, it appears to act by modulating signaling and gene expression.
Vitamin C supplementation modulates gene expression in peripheral blood mononuclear cells specifically upon an inflammatory stimulus: a pilot study in healthy subjects.
Specimen part
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