GEO series

Bulk transcriptome analysis of wildtype, TREM2 knockout, GPR34 knock-out or TREM2/GPR34 double knock-out iPSC-derived human microglia treated either with PBS or myelin.

GSE293037 Homo sapiens (human) RNA-seq (gene expression) 32 samples Submitted 2026/07/21 Platform GPL21697

At a glance

RNA-seq (gene expression) · human · 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: Homo sapiens (human)
Samples: 32 samples: 8 conditions, mostly with about 4 replicates eachGroups 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)

Microglia are broadly implicated in modifying disease risk in the central nervous system (CNS). Identifying regulators of microglia state is critical for elucidating their role in disease and identifying novel drug targets. GPR34 is a G-protein coupled receptor expressed in homeostatic microglia where its function is not well understood.

Read the full summary ↓

Like TREM2, GPR34 detects lipid ligands. Here, we report that GPR34 knockout (KO) maintains lipid homeostasis and rescues dysregulated cholesterol metabolism in TREM2 KO human iPSC-derived microglia (iMG). Loss of GPR34 reduced ERK signaling in iMG, which has been implicated as a signaling pathway dysregulated in AD, with GPR34 agonism shown to promote GPR34 interaction with ERK in a matter consistent with endosomal signaling. In both healthy and amyloid mouse models, Gpr34 KO accelerated microglial state transcriptionally and histologically consistent conversion of homeostatic microglia to a disease-associated microglia (DAM) state. Shifts in microglial state were accompanied by increased expression of multiple metabolic gene sets.

This dataset

Open GSE293037 in finder → Find more human 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 GSE293037_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 PRJNA1242395 and SRA study SRP573366. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

8 conditions, mostly with about 4 replicates each

WT, PBS, ×4 WT, Myelin, ×4 GPR34KO, PBS, ×4 GPR34KO, Myelin, ×4 TREM2KO, PBS, ×4 TREM2KO, Myelin, ×4 GPR34, TREM2KO, PBS, ×4 GPR34, TREM2KO, Myelin, ×4

Supports a between-group comparison across 32 samples.

How we read this: 8 replicated groups read from 32 sample titles; they account for 32 of them. 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

GSM8874380 WT, PBS, rep 1 WT, PBS,
GSM8874381 WT, Myelin, rep 1 WT, Myelin,
GSM8874382 GPR34KO, PBS, rep 1 GPR34KO, PBS,
GSM8874383 GPR34KO, Myelin, rep 1 GPR34KO, Myelin,
GSM8874384 TREM2KO, PBS, rep 1 TREM2KO, PBS,
GSM8874385 TREM2KO, Myelin, rep 1 TREM2KO, Myelin,
GSM8874386 GPR34, TREM2KO, PBS, rep 1 GPR34, TREM2KO, PBS,
GSM8874387 GPR34, TREM2KO, Myelin, rep 1 GPR34, TREM2KO, Myelin,
GSM8874388 WT, PBS, rep 2 WT, PBS,
GSM8874389 WT, Myelin, rep 2 WT, Myelin,
GSM8874390 GPR34KO, PBS, rep 2 GPR34KO, PBS,
GSM8874391 GPR34KO, Myelin, rep 2 GPR34KO, Myelin,
GSM8874392 TREM2KO, PBS, rep 2 TREM2KO, PBS,
GSM8874393 TREM2KO, Myelin, rep 2 TREM2KO, Myelin,
GSM8874394 GPR34, TREM2KO, PBS, rep 2 GPR34, TREM2KO, PBS,
GSM8874395 GPR34, TREM2KO, Myelin, rep 2 GPR34, TREM2KO, Myelin,
GSM8874396 WT, PBS, rep 3 WT, PBS,
GSM8874397 WT, Myelin, rep 3 WT, Myelin,
GSM8874398 GPR34KO, PBS, rep 3 GPR34KO, PBS,
GSM8874399 GPR34KO, Myelin, rep 3 GPR34KO, Myelin,
GSM8874400 TREM2KO, PBS, rep 3 TREM2KO, PBS,
GSM8874401 TREM2KO, Myelin, rep 3 TREM2KO, Myelin,
GSM8874402 GPR34, TREM2KO, PBS, rep 3 GPR34, TREM2KO, PBS,
GSM8874403 GPR34, TREM2KO, Myelin, rep 3 GPR34, TREM2KO, Myelin,
GSM8874404 WT, PBS, rep 4 WT, PBS,
GSM8874405 WT, Myelin, rep 4 WT, Myelin,
GSM8874406 GPR34KO, PBS, rep 4 GPR34KO, PBS,
GSM8874407 GPR34KO, Myelin, rep 4 GPR34KO, Myelin,
GSM8874408 TREM2KO, PBS, rep 4 TREM2KO, PBS,
GSM8874409 TREM2KO, Myelin, rep 4 TREM2KO, Myelin,
GSM8874410 GPR34, TREM2KO, PBS, rep 4 GPR34, TREM2KO, PBS,
GSM8874411 GPR34, TREM2KO, Myelin, rep 4 GPR34, TREM2KO, Myelin,

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