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Distinct interactions between pioneer factor Ascl1/E12a and nucleosomes drive cell fate transitions [ATAC-seq]

GSE299923 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 39 samples Submitted 2026/06/02 Platform GPL30882
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 39 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
Homo sapiens (human)
Samples
39 samples: 12 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.
Summary (written by the submitters)
Understanding how pioneer transcription factors target nucleosomal DNA and initiate chromatin accessibility provides insight into the earliest events in cell fate control. We used structural, biophysical, biochemical approaches to assess how the neural pioneer factor Ascl1 heterodimerizing with E12a binds nucleosomes in vitro. The nucleosomal binding, but not free DNA binding, by Ascl1/E12 is enhanced by two types of interactions with core histones.
Read the full summary ↓
We performed ChIP-seq and ATAC-seq to investigate how histone interaction mutants of Ascl12 (called AAA, allRs, and QA respecrively) affect its global chromatin targeting and chromatin opening.
This dataset
Open GSE299923 in finder → Find more human ChIP / ATAC / CUT&Tag 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 GSE299923_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 PRJNA1277335 and SRA study SRP592339. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
12 conditions, mostly in triplicate
ATAC_Ascl1_WT_D2 ×3 ATAC_Ascl1_allRs_D2 ×3 ATAC_Ascl1_AAA_D2 ×3 ATAC_Ascl1_QA_D2 ×3 ATAC_Ascl1_WT_D4 ×3 ATAC_Ascl1_allRs_D4 ×3 ATAC_Ascl1_AAA_D4 ×3 ATAC_Ascl1_QA_D4 ×3 +7 more

Supports a between-group comparison across 36 samples.

How we read this: 12 replicated groups read from 39 sample titles; they account for 36 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
Datasets on a similar topic

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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.