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Defining the microglia transcriptome during disease progression in ALS transgenic mice

GSE43366 Mus musculus (mouse) RNA-seq (gene expression) 42 samples Submitted 2013/07/15 Platform GPL13112
At a glance

RNA-seq (gene expression) · mouse · 42 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
42 samples: 42 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
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)
Purpose: We purified spinal cord microglia utilizing percoll gradients and magnetic beads, followed by transcriptome profiling (RNA-seq) to define microglia expression profiles against other neural, immune cell-types. We next observed how the microglai transcriptomes change during activation in the SOD1-G93A mouse model of motor neuron degeneration at 3 timepoints.
Read the full summary ↓
We also compared these profiles with that induced by LPS injection. Results and conclusions: ALS microglia were found to differ substantially from those activated by LPS and from M1/M2 macrophages by comparison with published datasets. These ALS microglia showing substantial induction of a "neurodegeneration-tailored phenotype", with induction of lysosomal, RNA splicing, and Alzheimer's disease pathway genes. Overall they express a mixture of neuroprotective and neurotoxic factors during activation in ALS mice, showing that neuro-immune activation in the spinal cord is a double-edged sword. We also detected the transcriptional nature of surface marker expression in microglia (CD11b, CD86, CD11c), and substantial T-cell microglia cross-talk using correlative microglia transcriptome/FACS analysis.
This dataset
Open GSE43366 in finder → Find more mouse RNA-seq datasets →
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.

Series matrix ↓
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 GSE43366_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
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.

Raw reads on ENA ↗

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 PRJNA185990 and SRA study SRP017849. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 23850290) ↗
Study design
42 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 42 sample titles: 42 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

+ 2 more — browse all 42 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.