Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Transcriptional network analysis in muscle reveals AP-1 as a partner of PGC-1M-NM-1 in the regulation of the hypoxic gene program [microarray: PGC1a_vs_GFP]

ABSTRACT: 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 M-NM-3 coactivator 1M-NM-1 (PGC-1M-NM-1), a regulatory nexus in endurance training adaptation. By integrating data on genome-wide binding of PGC-1M-NM-1 and gene expression upon PGC-1M-NM-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-1M-NM-1 action. In particular, principal component analysis of TFBSs at PGC-1M-NM-1 binding regions predicts that, besides the well-known role of the estrogen-related receptor M-NM-1 (ERRM-NM-1), the activator protein-1 complex (AP-1) plays a major role in regulating the PGC-1M-NM-1-controlled gene program of hypoxia response. Our findings thus reveal the complex transcriptional network of muscle cell plasticity controlled by PGC-1M-NM-1. We used microarrays to detect changes in gene expression in C2C12 cells following PGC-1alpha over-expression or GFP (control) over-expression. We used 3 biological replicates for each condition.

ORGANISM(S): Mus musculus

SUBMITTER: Christoph Handschin

PROVIDER: E-GEOD-51189 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Transcriptional network analysis in muscle reveals AP-1 as a partner of PGC-1α in the regulation of the hypoxic gene program.

Baresic Mario M Salatino Silvia S Kupr Barbara B van Nimwegen Erik E Handschin Christoph C

Molecular and cellular biology 20140609 16

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. By integrating data on genome-wide binding of PGC-1α and gene expression upon PG ...[more]

PMID: 24912679

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Project description:Mitochondrial oxidative function is tightly controlled to maintain energy homeostasis in response to nutrient and hormonal signals. An important cellular component in the energy sensing response is the target of rapamycin (TOR) kinase pathway; however whether and how mTOR controls mitochondrial oxidative activity is unknown. Here, we show that mTOR kinase activity stimulates mitochondrial gene expression and oxidative function. In skeletal muscle cells and TSC2-/- MEFs, the mTOR inhibitor rapamycin largely decreased gene expression of mitochondrial transcriptional regulators such as PGC-1alpha and the transcription factors ERRalpha and NRFs. As a consequence, mitochondrial gene expression and oxygen consumption were reduced upon mTOR inhibition. Using computational genomics, we identified the transcription factor YY1 as a common target of mTOR and PGC-1alpha that controls mitochondrial gene expression. Inhibition of mTOR resulted in a failure of YY1 to interact and be coactivated by PGC-1alpha. Notably, knock-down of YY1 in skeletal muscle cells caused a significant decrease in mRNAs of mitochondrial regulators and mitochondrial genes that resulted in a decrease in respiration. Moreover, YY1 was required for rapamycin-dependent repression of mitochondrial genes. Thus, we have identified a novel mechanism in which a nutrient sensor (mTOR) balances energy metabolism via transcriptional control of mitochondrial oxidative function. These results have important implications for our understanding of how these pathways might be altered in metabolic diseases and cancer. Experiment Overall Design: Using Affymetrix MOE430 v2 gene chips, biological triplicates of each condition were analyzed: vehicle-treated, rapamycin-treated, gfp-infected, and pgc-1alpha-infected resulting in a total of 12 samples. Experiment Overall Design: Data were analyzed by RMA (with default settings) in BioConductor 1.2 -- one batch for the Rapamycin vs. Vehicle, and another batch for the PGC vs GFP.

Dataset Information

Transcriptional network analysis in muscle reveals AP-1 as a partner of PGC-1M-NM-1 in the regulation of the hypoxic gene program [microarray: PGC1a_vs_GFP]

Publications

Transcriptional network analysis in muscle reveals AP-1 as a partner of PGC-1α in the regulation of the hypoxic gene program.

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