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H4K16 acylations fine-tune transcriptional response during metabolic perturbations (ChIP-seq)

GSE275933 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 46 samples Submitted 2025/12/01 Platform GPL21103
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 46 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
46 samples: 46 samples, each with a distinct title — no replicated groupsGroups 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
H4K16 acylations destabilize chromatin architecture and facilitate transcriptional response during metabolic perturbationsMolecular cell · 2026
Summary (written by the submitters)
We studied the combined effects of the H4K16 acylations in vivo using a mouse model of the metabolic disorder propionic acidemia (PA), which causes metabolic challenges and systemic shifts in acyl-CoA ratios. Our findings indicate that H4K16 acylations modulate transcriptional responses in a concerted manner, providing insights into an adaptive chromatin regulation in response to metabolic stress.
Published in
H4K16 acylations destabilize chromatin architecture and facilitate transcriptional response during metabolic perturbations
Nitsch S, Coraor AE, Schauer T et al. · Molecular cell 2026 · PMID 41421336 · doi:10.1016/j.molcel.2025.11.030
This dataset
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.

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 GSE275933_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1153613 and SRA study SRP529210. Searching any of these in the dataset finder brings you back here.

Study design
46 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 46 sample titles: 46 distinct titles with little repetition. 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

+ 6 more — browse all 46 samples with per-sample file links →

Datasets on a similar topic

Search all mouse ChIP / ATAC / CUT&Tag datasets in GEO →

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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.