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Epigenetic priming of embryonic enhancer elements coordinates developmental gene networks [CUT&TAG]

GSE290517 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 45 samples Submitted 2025/05/29 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 45 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
45 samples: 22 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
Epigenetic priming of mammalian embryonic enhancer elements coordinates developmental gene networksGenome biology · 2025
Summary (written by the submitters)
Embryonic development requires the accurate spatiotemporal execution of cell lineage-specific gene expression programs, which are controlled by transcriptional enhancers. Developmental enhancers adopt a primed chromatin state prior to their activation; however how this primed enhancer state is established, maintained, and how it affects the regulation of developmental gene networks remains poorly understood.
Read the full summary ↓
Here, we use comparative multi-omic analyses of human and mouse early embryonic development to identify subsets of post-gastrulation lineage-specific enhancers which are epigenetically primed ahead of their activation, marked by the histone modification H3K4me1 within the epiblast. We show that epigenetic priming occurs at lineage-specific enhancers for all three germ layers, and that epigenetic priming of enhancers confers lineage-specific regulation of key developmental gene networks. Surprisingly in some cases, lineage-specific enhancers are epigenetically marked already in the zygote, weeks before their activation during lineage specification. Moreover, we outline a generalisable strategy to use naturally occurring human genetic variation to delineate important sequence determinants of primed enhancer function. Our findings identify an evolutionarily conserved program of enhancer priming and begin to dissect the temporal dynamics and mechanisms of its establishment and maintenance during early mammalian development.
Published in
Epigenetic priming of mammalian embryonic enhancer elements coordinates developmental gene networks
Todd CD, Ijaz J, Torabi F et al. · Genome biology 2025 · PMID 40682180 · doi:10.1186/s13059-025-03658-8
This dataset
Open GSE290517 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 GSE290517_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 PRJNA1228550 and SRA study SRP566422. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40682180) ↗
Study design
22 conditions, mostly in duplicate
HIPSCI_CNT_HIPSCI_bima1_k27ac ×2 HIPSCI_CNT_HIPSCI_bima1_k4me1 ×2 HIPSCI_CNT_HIPSCI_kolf2_k27ac ×2 HIPSCI_CNT_HIPSCI_kolf2_k4me1 ×2 HIPSCI_CNT_HIPSCI_kolf3_k27ac ×2 HIPSCI_CNT_HIPSCI_kolf3_k4me1 ×2 HIPSCI_CNT_HIPSCI_kucg2_k27ac ×2 HIPSCI_CNT_HIPSCI_kucg2_k4me1 ×2 +15 more

Supports a between-group comparison across 44 samples.

How we read this: 22 replicated groups read from 45 sample titles; they account for 44 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

+ 5 more — browse all 45 samples with per-sample file links →

Datasets on a similar topic

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