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Pioneering new enhancers by GATA3: role of facilitating transcription factors and chromatin remodeling [ATAC-seq]

GSE280565 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 48 samples Submitted 2025/06/16 Platform GPL18573Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 48 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
48 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.
Paper
Pioneering new enhancers by GATA3: role of facilitating transcription factors and chromatin remodelingNucleic acids research · 2025
Summary (written by the submitters)
The mechanistic details by which pioneer transcription factors interact with partner transcription factors and chromatin modification/remodeling enzymes to activate enhancers remains an emerging area of study. Here, we utilize inducible expression of the pioneer factor GATA3 and study cofactor association and structural alterations in local chromatin.
Read the full summary ↓
ATAC-seq analysis and footprinting revealed co-occurrence of GATA3 with other transcription factors, including AP-1, in newly accessible chromatin. GATA3 and AP-1 co-localize at primed enhancers with p300 and BRG1 where nucleosome positioning is responsive to GATA3 location, not to AP-1. Genetic inhibition of AP-1 binding alters chromatin opening at some, but not most, GATA3-bound loci. Pharmacologic inhibition of SWI/SNF ATPase function results in loss of GATA3-dependent chromatin accessibility, binding, and alterations in local chromatin architecture. We conclude that GATA3-dependent gains in chromatin accessibility require chromatin remodeling and that accessibility at some loci is facilitated by a partner transcription factor, in this case AP-1.
Published in
Pioneering new enhancers by GATA3: role of facilitating transcription factors and chromatin remodeling
Orlando KA, Grimm SA, Wade PA · Nucleic acids research 2025 · PMID 40479714 · doi:10.1093/nar/gkaf473
This dataset
Open GSE280565 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 GSE280565_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 PRJNA1179420 and SRA study SRP541892. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40479714) ↗
Study design
12 conditions, mostly in triplicate
atac.ta1.ctrl ×3 atac.ta1.dox ×3 atac.wt.ctrl ×3 atac.wt.dox ×3 atac.wt.lenti_afos.ctrl ×3 atac.wt.lenti_afos.dox ×3 atac.wt.lenti_empty.ctrl ×3 atac.wt.lenti_empty.dox ×3 +16 more

Supports a between-group comparison across 36 samples.

How we read this: 12 replicated groups read from 48 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

+ 8 more — browse all 48 samples with per-sample file links →

Datasets on a similar topic

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