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Mutant GFAP alters lineage commitment of neural organoids [AxDorganoids_bulk_experiment2]

GSE267990 Homo sapiens (human) RNA-seq (gene expression) 47 samples Submitted 2025/07/13 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 47 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
47 samples: 47 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.
Summary (written by the submitters)
Glial fibrillary acidic protein (GFAP) is a type-3 intermediate filament protein mainly expressed in astrocytes in the central nervous system. Mutations in GFAP cause Alexander Disease (AxD), a rare and fatal neurological disorder. How exactly mutant GFAP eventually leads to white and grey matter deterioration in AxD remains unknown. GFAP is also expressed in radial glial cells, which are neural stem cells in the developing brain.
Read the full summary ↓
Here, we used AxD patient-derived induced pluripotent stem cells (iPSCs) to explore the impact of mutant GFAP during neurodifferentiation. Our results show that GFAP is already expressed in iPSCs. Moreover, we have found that mutations in GFAP can severely affect neural organoid development through altering lineage commitment in embryoid bodies. Together, these results support a key role for GFAP as an early modulator of neurodevelopment.
This dataset
Open GSE267990 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 GSE267990_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 PRJNA1114005 and SRA study SRP508976. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
47 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 47 sample titles: 47 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

+ 7 more — browse all 47 samples with per-sample file links →

Datasets on a similar topic

Search all human 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.