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Metabolic Atlas of Early Human Cortex Identifies Regulators of Cell Fate Transitions

GSE292425 Homo sapiens (human) RNA-seq (gene expression) 42 samples Submitted 2026/03/01 Platform GPL34328Platform GPL34281
At a glance

RNA-seq (gene expression) · human · 42 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
42 samples: 40 distinct titles, 2 of them repeatedGroups 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)
Cortical development involves rapid progenitor expansion and cell diversification that is likely supported by tightly regulated metabolic programs, yet these programs, particularly in human development remain largely uncharacterized. Here, we generated a metabolic atlas of the early human cortex using primary tissue and stem cell-derived cortical organoids.
Read the full summary ↓
Across developmental stages, we observed dynamic changes in core metabolic functions, including an unexpected increase in glycolysis and pentose phosphate pathway (PPP) activity during late neurogenesis. Manipulation of glucose availability in cortical organoids altered progenitor and neuronal composition, increasing outer radial glia and inhibitory neurons populations. Pharmacological and genetic inhibition of PPP enzymes recapitulated these cell fate changes and promoted radial glial maturation. Ribose was sufficient to rescue the radial glia gene expression changes, revert organoid cell type composition, and restore the levels of ATP and hypotaurine. These data identify a critical role for the PPP in modulating radial glia cell fate specification and generate a resource for future exploration of additional metabolic pathways in human cortical development.
This dataset
Open GSE292425 in finder → Find more 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 GSE292425_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 PRJNA1238381 and SRA study SRP571692. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
40 distinct titles, 2 of them repeated
DMSO_E ×2 ORX_E ×2

How we read this: Read from 42 sample titles: 40 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

+ 2 more — browse all 42 samples with per-sample file links →

Datasets on a similar topic

Search all RNA-seq datasets in GEO →

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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.