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The expression order determines the pioneer functions of Ngn3 and NeuroD1 in pancreatic endocrine differentiation

GSE270915 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 3745 samples Submitted 2025/02/15 Platform GPL24247Platform GPL17021Platform GPL21103
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 3745 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Mus musculus (mouse)
Samples
3745 samples: 21 conditions, mostly in duplicateGroups 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
The expression order determines the pioneer functions of NGN3 and NEUROD1 in pancreatic endocrine differentiationScience advances · 2025
Summary (written by the submitters)
This study investigates the roles of Ngn3 and NeuroD1 in pancreatic endocrine differentiation. Using a new mouse model, we mapped NGN3 binding sites by CUT&RUN and demonstrated its pioneering role in making chromatin accessible by scATAC-seq. According to conditional knock-out and over-expression experiments and scRNA-seq, we domonstrated that NGN3's pioneering function was dose tolerance, with low doses sufficing, while NeuroD1, as a conventional TF, has no significant pioneer effects under normal phenomena.
Read the full summary ↓
But when NGN3 was absent, NeuroD1 can alternatively acted as a pioneer factor, and sequential expression of NeuroD1 ahead of Ngn3 predominantly drives α-cell generation.
Published in
The expression order determines the pioneer functions of NGN3 and NEUROD1 in pancreatic endocrine differentiation
Yang L, Yu XX, Wang X et al. · Science advances 2025 · PMID 40138419 · doi:10.1126/sciadv.adt4770
This dataset
Open GSE270915 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 GSE270915_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1129023 and SRA study SRP516539. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40138419) ↗
Study design
21 conditions, mostly in duplicate
Ngn3CreNeurod1OEHZ_E15.5 ×183 ATAC_E15.5Neurod1KO ×3 ATAC_E15.5WT ×3 ATAC_E17.5Neurod1KO ×3 ATAC_E17.5WT ×3 Ngn3_E13.5Ngn3H ×2 Ngn3_E13.5Ngn3L ×2 P300_E13.5Ngn3H ×2 +186 more

Supports a between-group comparison across 227 samples.

How we read this: 21 replicated groups read from the first 400 of 3745 sample titles; they account for 227 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

+ 3705 more — browse all 3745 samples with per-sample file links →

Datasets on a similar topic

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