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The sleep–wake history contributes to rhythmic BMAL1 chromatin binding in the cerebral cortex but not in the liver

GSE299933 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 95 samples Submitted 2025/11/27 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 95 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
95 samples: 95 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
The sleep-wake history contributes to rhythmic BMAL1 chromatin binding in the cerebral cortex but not in the liverProceedings of the National Academy of Sciences of the United States of America · 2025
Summary (written by the submitters)
The timing and quality of sleep is regulated by circadian- and sleep–wake-driven processes. The core clock gene Bmal1 not only affects the circadian timing of sleep, but also the response to sleep deprivation (SD), which, in turn, causes long-term changes in cortical Bmal1 expression. We aimed at separating the circadian- and sleep–wake-driven contributions to BMAL1 binding to its target genes in the cerebral cortex by scheduling 6 SDs at 4 h intervals across the daily 12 h light/12 h dark cycle.
Read the full summary ↓
We show that BMAL1 rhythmically bound its tissue-specific targets with tissue-specific dynamics, reaching peak binding 2 to 4 h later in the cortex than in the liver, while trough times did not differ. The SDs affected BMAL1 binding most significantly in the cortex, causing 80% of rhythmically bound regions to lose rhythmicity, suggesting BMAL1 binding has a prominent sleep–wake-driven component in this tissue. Analyses of the promoters of other core clock-genes indicate that BMAL1 binding to Bhlhe41 and Nr2d1 have a strong sleep–wake-driven component, while for Per2 two binding regions were identified one with circadian- and the other with sleep–wake-driven binding dynamics. Our results attest to a nonadditive interaction of time-of-day and time-spent-awake affecting the core molecular circadian circuitry. It further highlights that rhythms in gene expression in peripheral tissues are an emergent property of molecular interactions beyond that of the core molecular clock circuitry.
Published in
The sleep-wake history contributes to rhythmic BMAL1 chromatin binding in the cerebral cortex but not in the liver
Neves C, Hor CN, Jimenez S et al. · Proceedings of the National Academy of Sciences of the United States of America 2025 · PMID 41296730 · doi:10.1073/pnas.2515047122
This dataset
Open GSE299933 in finder → Find more mouse 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 GSE299933_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 PRJNA1277555 and SRA study SRP592476. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41296730) ↗
Study design
95 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 95 sample titles: 95 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

+ 55 more — browse all 95 samples with per-sample file links →

Datasets on a similar topic

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