GEO series

Early Developmental Origins of Cortical Disorders Modeled in Human Neural Stem Cells [bulk RNA-seq]

GSE271965 Homo sapiens (human) Single-cell RNA-seq 62 samples Submitted 2025/04/25 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 62 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism: Homo sapiens (human)
Samples: 62 samples: 60 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.
Paper: Early developmental origins of cortical disorders modeled in human neural stem cellsNature communications · 2025

Summary (written by the submitters)

The implications of the early phases of human telencephalic development, involving neural stem cells (NSCs), in the etiology of cortical disorders remain elusive. Here, we explored the expression dynamics of cortical and neuropsychiatric disorder-associated genes in datasets generated from human NSCs across telencephalic fate transitions in vitro and in vivo.

Read the full summary ↓

We identified risk genes expressed in brain organizers and sequential gene regulatory networks across corticogenesis revealing disease-specific critical phases, when NSCs are more vulnerable to gene dysfunctions, and converging signaling across multiple diseases. Moreover, we simulated the impact of risk transcription factor (TF) depletions on different neural cell types spanning the developing human neocortex and observed a spatiotemporal-dependent effect for each perturbation. Finally, single-cell transcriptomics of newly generated autism-affected patient-derived NSCs in vitro revealed recurrent alterations of TFs orchestrating brain patterning and NSC lineage commitment. This work opens new perspectives to explore human brain dysfunctions at the early phases of development.

Published in

Early developmental origins of cortical disorders modeled in human neural stem cells

Mato-Blanco X, Kim SK, Jourdon A et al. · Nature communications 2025 · PMID 40634286 · doi:10.1038/s41467-025-61316-w

This dataset

Open GSE271965 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 GSE271965_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1134217 and SRA study SRP519161. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40634286) ↗

Study design

60 distinct titles, 2 of them repeated

Control,290,Passage2,0.1, ×2 ASD,434,Passage2,20, ×2

How we read this: Read from 62 sample titles: 60 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

GSM8389774 Control,290,DIV 8,rep_1
GSM8389775 Control,311,DIV 8,rep_1
GSM8389776 Control,317,DIV 8,rep_1
GSM8389777 ASD,375,DIV 8,rep_1
GSM8389778 ASD,384,DIV 8,rep_1
GSM8389779 ASD,434,DIV 8,rep_1
GSM8389780 Control,290,DIV 17,rep_1
GSM8389781 Control,311,DIV 17,rep_1
GSM8389782 Control,317,DIV 17,rep_1
GSM8389783 ASD,375,DIV 17,rep_1
GSM8389784 ASD,384,DIV 17,rep_1
GSM8389785 ASD,434,DIV 17,rep_1
GSM8389786 Control,290,DIV 30,rep_1
GSM8389787 Control,311,DIV 30,rep_1
GSM8389788 Control,317,DIV 30,rep_1
GSM8389789 ASD,375,DIV 30,rep_1
GSM8389790 ASD,384,DIV 30,rep_1
GSM8389791 ASD,434,DIV 30,rep_1
GSM8389792 Control,290,DIV 38,rep_1
GSM8389793 Control,311,DIV 38,rep_1
GSM8389794 Control,317,DIV 38,rep_1
GSM8389795 ASD,375,DIV 38,rep_1
GSM8389796 ASD,384,DIV 38,rep_1
GSM8389797 ASD,434,DIV 38,rep_1
GSM8389798 Control,290,Passage2,0.1,rep_1
GSM8389799 Control,290,Passage2,0.1,rep_2
GSM8389800 Control,311,Passage2,0.1,rep_1
GSM8389801 Control,317,Passage2,0.1,rep_1
GSM8389802 ASD,375,Passage2,0.1,rep_1
GSM8389803 ASD,384,Passage2,0.1,rep_1
GSM8389804 ASD,434,Passage2,0.1,rep_1
GSM8389805 Control,290,Passage2,20,rep_1
GSM8389806 Control,311,Passage2,20,rep_1
GSM8389807 Control,317,Passage2,20,rep_1
GSM8389808 ASD,375,Passage2,20,rep_1
GSM8389809 ASD,384,Passage2,20,rep_1
GSM8389810 ASD,434,Passage2,20,rep_1
GSM8389811 ASD,434,Passage2,20,rep_2
GSM8389812 Control,290,Passage4,0.1,rep_1
GSM8389813 Control,311,Passage4,0.1,rep_1

+ 22 more — browse all 62 samples with per-sample file links →

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