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TREM2 is a global regulator of microglia energetic and biosynthetic metabolism during steady state and in Alzheimer’s disease

GSE98563 Mus musculus (mouse) RNA-seq (gene expression) 32 samples Submitted 2017/08/15 Platform GPL17021
At a glance

RNA-seq (gene expression) · mouse · 32 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
32 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)
The most common form of senile dementia, Alzheimer’s disease (AD), is characterized by Aβ plaques and neurofibrillary tangles in the CNS. AD genetic studies have identified high-risk hypomorphic variants in TREM2, a myeloid cell surface receptor that enables concerted microglial responses to Aβ plaques and neuronal cell death, including proliferation, survival, clustering and phagocytosis.
Read the full summary ↓
How TREM2 promotes these responses is not known. Here, we demonstrate that TREM2 drives mTOR signaling, which maintains high ATP levels, supports biosynthetic pathways and suppresses AMPK phosphorylation and autophagy. In vitro, TREM2-deficient macrophages undergo dramatically increased autophagy and die in response to growth factor limitation or ER stress. Excessive autophagy is also evident in microglia from Trem2-/- 5XFAD mice and in post-mortem specimens from AD patients carrying TREM2 risk variants. Metabolic derailment, autophagy and cell death can be circumvented by engaging alternative energy production pathways. Thus, restoring microglial energetic and anabolic levels may be a future therapeutic avenue for TREM2-associated neurological disease.
This dataset
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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 GSE98563_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 PRJNA385524 and SRA study SRP106492. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 28802038) ↗
Samples in this study

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