← BioTransfer GEO Dataset Finder
GEO series

Gene expression profile for Gpt2 WT and Gpt2 KO mouse brain tissues with vehicle or dm-αKG treatment

GSE325502 Mus musculus (mouse) RNA-seq (gene expression) 36 samples Submitted 2026/08/01 Platform GPL34328
At a glance

RNA-seq (gene expression) · mouse · 36 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
36 samples: 10 × WT, Vehicle, sample vs 10 × ΚΟ, Vehicle, sample vs 8 × WT, dm-αKG, sample vs 8 × ΚΟ, dm-αKG, sampleGroups 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)
Alpha-ketoglutarate (αKG) is required for chromatin demethylation but mechanisms controlling αKG abundance in the nucleus are poorly defined. We designed a biosensor to monitor this metabolite pool in human cells using an αKG-responsive cyanobacterial transcription factor, NtcA, and used it to identify genes that regulate αKG in the nucleus.
Read the full summary ↓
We defined an inter-organelle pathway in which sequential mitochondrial activities of the GPT2 transaminase and SLC25A11 transporter supply nuclear αKG. In a mouse model of GPT2 Deficiency, an inborn error of metabolism, Gpt2 loss caused histone hypermethylation in the brain and dysregulated neurodevelopmental genes. Restoring αKG counteracted these changes and promoted mouse fitness. Our work provides a tool to directly monitor nuclear αKG and reveals nuclear αKG deficiency as a key pathogenic mechanism underlying GPT2 Deficiency.
This dataset
Open GSE325502 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 GSE325502_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 PRJNA1440359 and SRA study SRP685393. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
10 × WT, Vehicle, sample vs 10 × ΚΟ, Vehicle, sample vs 8 × WT, dm-αKG, sample vs 8 × ΚΟ, dm-αKG, sample

Supports a between-group comparison across 36 samples.

How we read this: 4 replicated groups read from 36 sample titles; they account for 36 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
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.