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Progranulin Deficiency Promotes Circuit-Specific Synaptic Pruning by Microglia via Complement Activation

GSE75083 Mus musculus (mouse) Expression microarray 169 samples Submitted 2016/03/31 Platform GPL10787Platform GPL6885
At a glance

Expression microarray · mouse · 169 samples

What it is
Expression microarrayGene activity read on a chip (the older technology that RNA-seq replaced).
Organism
Mus musculus (mouse)
Samples
169 samples
Data you can get
A processed expression table (series matrix) and the array files, from NCBI.
Summary (written by the submitters)
Microglia repair injury and maintain homeostasis in the brain, but whether aberrant microglial activation can contribute to neurodegeneration remains unclear. Here, we use transcriptome profiling to demonstrate that deficiency in frontotemporal dementia (FTD) gene progranulin (Grn) leads to an age-dependent, progressive up-regulation of lysosomal and innate immunity genes, increased complement production, and synaptic pruning activity in microglia.
Read the full summary ↓
During aging, Grn-/- mice show profound accumulation of microglia and preferential elimination of inhibitory synapses in the ventral thalamus, which contribute to hyperexcitability in the thalamocortical circuits and obsessive-compulsive disorder (OCD)-like grooming behaviors. Remarkably, blocking complement activation by deleting C1qa gene significantly reduces synaptic pruning by Grn-/- microglia, and mitigates neurodegeneration, behavioral phenotypes and premature mortality in Grn-/- mice. These results uncover a previously unrecognized role of progranulin in suppressing microglia activation during aging, and support the idea that blocking complement activation is a promising therapeutic target for neurodegeneration caused by progranulin deficiency.
This dataset
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.

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 (GSE75083_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

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 PRJNA302422. Searching any of these in the dataset finder brings you back here.

Samples in this study

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