GEO series

mTOR pathway controls mitochondrial gene expression and respiration through the YY1/PGC-1alpha transcriptional complex

GSE5332 Mus musculus (mouse) Expression microarray 12 samples Submitted 2007/12/01 Platform GPL1261

At a glance

Expression microarray · mouse · 12 samples

What it is: Expression microarrayGene activity read on a chip (the older technology that RNA-seq replaced).
Organism: Mus musculus (mouse)
Samples: 12 samples
Data you can get: A processed expression table (series matrix) and the array files, from NCBI.

Summary (written by the submitters)

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.

Read the full summary ↓

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. Keywords: comparative genomics, drug treatment response

This dataset

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Download · which file do I need?

Direct links to NCBI, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need.

All supplementary files ↗

3 · The original raw files

Whole study · RAW.tar

Everything the authors deposited as one archive (GSE5332_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

Whole study · RAW.tar ↓

What the files usually look like: For arrays the series matrix is normally the normalised expression table you want; the raw array files (CEL and similar) are in the RAW.tar.

Also filed as BioProject PRJNA96347. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 18046414) ↗

Samples in this study

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+ 12 more — browse all 12 samples with per-sample file links →

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