GEO DataSets

(Submitter supplied) This SuperSeries is composed of the SubSeries listed below.

Organism:

Mus musculus

Type:

Expression profiling by array; Genome binding/occupancy profiling by high throughput sequencing

Platforms:

GPL13112 GPL6246

11 Samples

Download data: CEL

(Submitter supplied) The peroxisome proliferator-activated receptor γ co-activator 1α (PGC-1α) coordinates the transcriptional network response to promote an improved endurance capacity in skeletal muscle, e.g. by co-activating the estrogen-related receptor α (ERRα) 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. more...

Organism:

Mus musculus

Type:

Expression profiling by array

Platform:

GPL6246

9 Samples

Download data: CEL, TXT

(Submitter supplied) The peroxisome proliferator-activated receptor γ co-activator 1α (PGC-1α) coordinates the transcriptional network response to promote an improved endurance capacity in skeletal muscle, e.g. by co-activating the estrogen-related receptor α (ERRα) 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. more...

Organism:

Mus musculus

Type:

Genome binding/occupancy profiling by high throughput sequencing

Platform:

GPL13112

2 Samples

Download data: BED

(Submitter supplied) This SuperSeries is composed of the SubSeries listed below.

Organism:

Mus musculus

Type:

Expression profiling by array; Genome binding/occupancy profiling by high throughput sequencing

Platforms:

GPL11002 GPL10740 GPL9250

20 Samples

Download data: CEL

(Submitter supplied) Skeletal 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 γ coactivator 1α (PGC-1α), a regulatory nexus in endurance training adaptation. more...

Organism:

Mus musculus

Type:

Expression profiling by array

Platform:

GPL10740

10 Samples

Download data: CEL, TXT

(Submitter supplied) Skeletal 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 γ coactivator 1α (PGC-1α), a regulatory nexus in endurance training adaptation. more...

Organism:

Mus musculus

Type:

Expression profiling by array

Platform:

GPL10740

6 Samples

Download data: CEL, TXT

(Submitter supplied) Skeletal 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 γ coactivator 1α (PGC-1α), a regulatory nexus in endurance training adaptation. more...

Organism:

Mus musculus

Type:

Genome binding/occupancy profiling by high throughput sequencing

Platforms:

GPL9250 GPL11002

4 Samples

Download data: BED

(Submitter supplied) In the present study we have studied the mechanistic and functional aspects of NCoR1 function in mouse skeletal muscle. NCoR1 muscle-specific knockout mice exhibited an increased oxidative metabolism. Global gene expression analysis revealed a high overlap between the effects of NCoR1 deletion and peroxisome proliferator-activated receptor (PPAR) gamma coactivator 1alpha (PGC-1alpha) overexpression on oxidative metabolism in skeletal muscle. more...

Organism:

Mus musculus

Type:

Expression profiling by array

Platform:

GPL6246

20 Samples

Download data: CEL

(Submitter supplied) Endurance and resistance exercise training induce specific and profound changes in the skeletal muscle transcriptome. PGC-1a; coactivators are not only among the genes differentially induced by distinct training methods, but also participate in the ensuing signaling cascades that allow skeletal muscle to adapt to each type of exercise. While endurance training preferentially induces PGC-1a1 expression, resistance exercise activates the expression of PGC-1a2, a3, and a4. more...

Organism:

Mus musculus

Type:

Expression profiling by array

Platform:

GPL6096

15 Samples

Download data: CEL

(Submitter supplied) This SuperSeries is composed of the SubSeries listed below.

Organism:

Homo sapiens

Type:

Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by array

Platforms:

GPL11154 GPL570

7 Samples

Download data: BIGWIG, CEL, CHP

(Submitter supplied) Reprogramming of cellular metabolism plays a central role in fuelling malignant transformation, and AMPK as well as the PGC-1α/ERRα axis are key regulators of this process. Intersection of gene expression and binding event datasets in breast cancer cells shows that activation of AMPK significantly increases the expression of PGC-1α/ERRα and promotes the binding of ERRα to its cognate sites. Unexpectedly, the data also reveal that ERRα, in concert with PGC-1α, negatively regulates the expression of several one-carbon metabolism genes resulting in substantial perturbations in purine biosynthesis. more...

Organism:

Homo sapiens

Type:

Genome binding/occupancy profiling by high throughput sequencing

Platform:

GPL11154

3 Samples

Download data: BIGWIG, XLSX

(Submitter supplied) Reprogramming of cellular metabolism plays a central role in fuelling malignant transformation, and AMPK as well as the PGC-1α/ERRα axis are key regulators of this process. Intersection of gene expression and binding event datasets in breast cancer cells shows that activation of AMPK significantly increases the expression of PGC-1α/ERRα and promotes the binding of ERRα to its cognate sites. Unexpectedly, the data also reveal that ERRα, in concert with PGC-1α, negatively regulates the expression of several one-carbon metabolism genes resulting in substantial perturbations in purine biosynthesis. more...

Organism:

Homo sapiens

Type:

Expression profiling by array

Platform:

GPL570

4 Samples

Download data: CEL, CHP

(Submitter supplied) This SuperSeries is composed of the SubSeries listed below.

Organism:

Mus musculus

Type:

Expression profiling by high throughput sequencing; Other

Platforms:

GPL21626 GPL24247

35 Samples

Download data: BW

(Submitter supplied) Although PGC 1α is well-established as a transcriptional coactivator for the metabolic adaptation of mammalian cells to diverse physiological stresses, its molecular dynamics at the start and during gene transcription are incompletely understood. Previously, we defined a CBP80-binding motif (CBM) within PGC 1α that binds CBP80 at the 5′-cap of nascent transcripts deriving from PGC 1α-responsive genes. more...

Organism:

Mus musculus

Type:

Expression profiling by high throughput sequencing

Platform:

GPL21626

9 Samples

Download data: BW

(Submitter supplied) Although PGC 1α is well-established as a transcriptional coactivator for the metabolic adaptation of mammalian cells to diverse physiological stresses, its molecular dynamics at the start and during gene transcription are incompletely understood. Previously, we defined a CBP80-binding motif (CBM) within PGC 1α that binds CBP80 at the 5′-cap of nascent transcripts deriving from PGC 1α-responsive genes. more...

Organism:

Mus musculus

Type:

Expression profiling by high throughput sequencing

Platform:

GPL24247

9 Samples

Download data: BW

(Submitter supplied) Although PGC 1α is well-established as a transcriptional coactivator for the metabolic adaptation of mammalian cells to diverse physiological stresses, its molecular dynamics at the start and during gene transcription are incompletely understood. Previously, we defined a CBP80-binding motif (CBM) within PGC 1α that binds CBP80 at the 5′-cap of nascent transcripts deriving from PGC 1α-responsive genes. more...

Organism:

Mus musculus

Type:

Expression profiling by high throughput sequencing

Platform:

GPL21626

9 Samples

Download data: BW

(Submitter supplied) Although PGC 1α is well-established as a transcriptional coactivator for the metabolic adaptation of mammalian cells to diverse physiological stresses, its molecular dynamics at the start and during gene transcription are incompletely understood. Previously, we defined a CBP80-binding motif (CBM) within PGC 1α that binds CBP80 at the 5′-cap of nascent transcripts deriving from PGC 1α-responsive genes. more...

Organism:

Mus musculus

Type:

Other

Platform:

GPL24247

8 Samples

Download data: BW

(Submitter supplied) This RNA-seq dataset was generated to identify genes whose transcription relies on the CBP80-binding motif (CBM) of PGC-1α in C2C12 mouse myoblasts.

Organism:

Mus musculus

Type:

Expression profiling by high throughput sequencing

Platform:

GPL17021

12 Samples

Download data: TXT

(Submitter supplied) This SuperSeries is composed of the SubSeries listed below.

Organism:

Mus musculus

Type:

Expression profiling by high throughput sequencing; Other

Platforms:

GPL19057 GPL17021

13 Samples

Download data

(Submitter supplied) PGC-1alpha has been proposed to couple gene transcription and RNA processing via SR-rich domains and an RNA recognition motif located at the C-terminal domain (CTD). However, the full extent by which the CTD of PGC-1alpha regulates its function in gene expression and RNA processing remains largely unknown. Here, we used RNA-seq to evaluate the effects of CTD deletion (dCTD) on PGC-1alpha function. We found that deletion of the CTD of PGC-1alpha virtually abolished its effects on transcriptome remodeling and the resulting increase in oxidative capacity in skeletal muscle cells. more...

Organism:

Mus musculus

Type:

Other

Platform:

GPL19057

4 Samples

Download data: BIGWIG, XLSX