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BMP, MEK and WNT modulation with NGN2 expression for rapid neuron differentiation from hiPSC amenable to regional patterning [BMWi]

GSE253508 Homo sapiens (human) RNA-seq (gene expression) 69 samples Submitted 2025/06/19 Platform GPL21697
At a glance

RNA-seq (gene expression) · human · 69 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
69 samples: 21 conditions, mostly in triplicateGroups 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
BMP, MEK, and WNT inhibition with NGN2 expression for rapid generation of hiPSC-derived neurons amenable to regional patterningStem cell reports · 2025
Summary (written by the submitters)
hiPSCs aid in studying neurological diseases and developing therapies. Interventions, such as dual SMAD inhibition or NGN2 overexpression (“iNGN2”), can direct hiPSCs towards neurons. Starting directly from hiPSCs, iNGN2 shortens the time to a neuronal stage but leads to neurons resembling peripheral or posterior fates. We applied an accelerated induction paradigm that is only dependent on inhibition of BMP, MEK and WNT pathways (“BMWi”), to commit iPSCs before to rostral neuroectoderm.
Read the full summary ↓
The resulting neurons showed strong expression of telencephalic, cortical markers, with decreased levels of peripheral and posterior marker genes compared to iNGN2 alone. The resulting cortical neurons are suitable for a tau aggregation assay. Furthermore, we could demonstrate that during BMWi treatment, the cells are amenable to regional patterning clues. This allowed the generation of neurons from different regions of the CNS and PNS, which will significantly improve existing in vitro models for neurodegenerative disorders.
Published in
BMP, MEK, and WNT inhibition with NGN2 expression for rapid generation of hiPSC-derived neurons amenable to regional patterning
Habich C, Kowalski A, Wachter A et al. · Stem cell reports 2025 · PMID 40541177 · doi:10.1016/j.stemcr.2025.102539
This dataset
Open GSE253508 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 GSE253508_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 PRJNA1065913 and SRA study SRP484278. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40541177) ↗
Study design
21 conditions, mostly in triplicate
BMWi_NMMmin_final_hiPSC_3 ×5 BMWi_NMMmin_final_hiPSC_2 ×4 iNGN2_NMMmin_final_hiPSC_3 ×4 BMWi_D4_hiPSC_3 ×3 BMWi_D4_hiPSC_2 ×3 BMWi_NMMmin_final_hiPSC_1 ×3 BMWi_D6_hiPSC_1 ×3 BMWi_D6_hiPSC_3 ×3 +17 more

Supports a between-group comparison across 65 samples.

How we read this: 21 replicated groups read from 69 sample titles; they account for 65 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

+ 29 more — browse all 69 samples with per-sample file links →

Datasets on a similar topic

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