← BioTransfer GEO Dataset Finder
GEO series

Epigenetic and genetic changes during mouse hematopoietic stem cell aging [RNA-Seq]

GSE47817 Mus musculus (mouse) RNA-seq (gene expression) 8 samples Submitted 2014/04/30 Platform GPL13112
At a glance

RNA-seq (gene expression) · mouse · 8 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Mus musculus (mouse)
Samples
8 samples
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Summary (written by the submitters)
To investigate the global transcriptome changes in mouse hematopoietic stem cell aging, we performed high-throughput sequencing of Poly A+ RNA (RNA-Seq) from purified 4 month, and 24 month-old HSCs (SP-KSL-CD150+). With biological duplicates, more than 200 million reads in total for each age of HSC were obtained. Comparison of the young and old HSC transcriptomes revealed that 1,337 genes that were up-regulated, and 1,297 genes were down-regulated with HSC aging.
Read the full summary ↓
The most highly represented upstream regulator was growth factor TGFB1, accounting for ~ 19% of differential gene expression in young versus old HSC (p-value = 1.96E-33). Gene ontology (GO) analyses indicated that up-regulated genes in 24mo HSCs are highly enriched in Regulation of Cell Adhesion, Regulation of Cell Proliferation and Ribosome, while down-regulated genes are enriched in DNA Base Excision Repair, DNA replication and Cell Cycle. RNA-seq also allowed us to examine alternative isoforms with aging including alternative splicing, promoter usage and pre-mRNA abundance.
This dataset
Download · which file do I need?

Direct links to NCBI and ENA, 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.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE47817_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA208010 and SRA study SRP025153. Searching any of these in the dataset finder brings you back here.

Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 8 more — browse all 8 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.