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Epigenetic determinants of muscle stem cell quiescence and chronological aging

GSE47177 Mus musculus (mouse) Expression microarray 30 samples Submitted 2013/05/23 Platform GPL6246
At a glance

Expression microarray · mouse · 30 samples

What it is
Expression microarrayGene activity read on a chip (the older technology that RNA-seq replaced).
Organism
Mus musculus (mouse)
Samples
30 samples
Data you can get
A processed expression table (series matrix) and the array files, from NCBI.
Summary (written by the submitters)
Skeletal muscle is a post-mitotic tissue that exhibits an extremely low turnover in the absence of disease or injury. At the same time, muscle possesses remarkable regenerative capacity mediated by satellite cells (SCs) that reside in close association with individual myofibers, underneath the fiber’s basal lamina. Consistent with the low turnover of the muscle, SCs in adult animals are mitotically quiescent and therefore provide an excellent model to study stem cell quiescence.
Read the full summary ↓
As an organism grows older, the resident stem cells are exposed to a deteriorating environment and experience chronological aging. In stem cells with high turnover, the effects of chronological aging are superimposed upon the effects of the replicative aging that results from DNA replication and cell division. On the contrary, SCs experience minimal replicative aging due to their low turnover. They are thus a good model to study the consequence of chronological aging of quiescent stem cells. We performed microarray analysis of quiescent and activated SCs from both young and aged mice to understand the global gene expression profile underlying stem cell properties such as quiecence and self-renewal, and to understand how the transcriptome of a quiescent stem cell pouplation changes with age.
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 (GSE47177_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 PRJNA205033. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 23810552) ↗
Samples in this study

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