GEO series

Mechanism-guided identification of antidepressant G protein-coupled receptor drug targets

GSE264279 Mus musculus (mouse) RNA-seq (gene expression) 20 samples Submitted 2026/04/30 Platform GPL30172

At a glance

RNA-seq (gene expression) · mouse · 20 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: 20 samples: 20 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.
Paper: Mechanism-guided identification of antidepressant G protein-coupled receptor drug targetsCell · 2026

Summary (written by the submitters)

Depression is a psychiatric disorder that is widely thought to be driven by dysregulation at the molecular and synaptic levels that disrupts the function of discrete neural circuits which, ultimately, drive behavioral symptoms. While therapeutic approaches have typically been based on the serendipitous identification of symptom-alleviating compounds, a deeper understanding of the mechanisms underlying the pathophysiology and treatment of depression is needed to guide the development of new therapeutics.

Read the full summary ↓

Here we decipher mechanisms of action of the fast-acting antidepressant ketamine to enable the identification of new G protein-coupled receptor (GPCR) antidepressant targets. We find that the behavioral effects of ketamine rely on agonism of mu-opioid receptors, which are enriched in somatostatin-expressing interneurons (Sst+ INs) in the medial prefrontal cortex (mPFC). Chronic stress drives presynaptic hypertrophy of mPFC Sst+ INs and excessive inhibition of pyramidal neurons, which is rescued by ketamine. Driven by these findings, we use RNA sequencing to identify a plethora of mPFC Sst+ IN-enriched GPCRs and validate the antidepressant potential of novel GPCR targets. Synergistic targeting of multiple Sst+ IN-enriched GPCRs enables potent antidepressant-like responses with a reduced side effect profile compared to ketamine. Together this study provides new mechanistic insights with promise to improve antidepressant strategies while revealing a general approach to identifying new therapeutic GPCR targets for brain disorders.

Published in

Mechanism-guided identification of antidepressant G protein-coupled receptor drug targets

Munguba H, Arefin A, Hasegawa R et al. · Cell 2026 · PMID 42030928 · doi:10.1016/j.cell.2026.04.006

This dataset

Open GSE264279 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 GSE264279_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 PRJNA1101850 and SRA study SRP504140. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42030928) ↗

Study design

20 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 20 sample titles: 20 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

GSM8215391 E06-Control
GSM8215392 E12-Control
GSM8215393 E16-Control
GSM8215394 E18-Control
GSM8215395 E08-CUS
GSM8215396 E10-CUS
GSM8215397 E20-CUS
GSM8215398 E22-CUS
GSM8215399 E24-CUS
GSM8215400 CK1-Control
GSM8215401 CK2-Control
GSM8215402 CK3-Control
GSM8215403 CK4-Control
GSM8215404 CK5-Control
GSM8215405 C01-CUS
GSM8215406 C02-CUS
GSM8215407 C03-CUS
GSM8215408 C04-CUS
GSM8215409 C05-CUS
GSM8215410 C06-CUS

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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.