GEO series

BMAL1 and YAP cooperate to hijack enhancers and promote inflammation in the aged epidermis [ChIP-Seq 2]

GSE294070 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 15 samples Submitted 2026/06/23 Platform GPL30172

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 15 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: 15 samples: 15 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.

Summary (written by the submitters)

Ageing is characterised by persistent low-grade inflammation that is linked to impaired tissue homeostasis and functionality. However, the molecular mechanisms driving age-associated inflammation remain poorly understood. The mammalian skin is a clinically relevant target of age-driven inflammation associated with compromised barrier function, inefficient wound healing, elevated oxidative stress, and DNA damage accumulation.

Read the full summary ↓

Here, we show that upon ageing a previously uncharacterised BMAL1–YAP transcriptional complex is hijacked from chromatin regions associated with homeostatic genes in adult epidermis and redirected to inflammation-related enhancers, amplifying the transcription of their target genes. Independently of its known role as a core circadian clock component, BMAL1 partners with the mechanosensitive transcriptional cofactor YAP at enhancer regions to regulate epidermal identity genes. In contrast, in aged skin, BMAL1–YAP complexes bind to enhancers of inflammation-related genes, co-regulated by NF-κB. Interestingly, aged pro-inflammatory signals from the IL-17 pathway activate YAP in a Hippo-independent manner. These findings unveil a transcriptional mechanism underlying epidermal ageing, linking chromatin dynamics to inflammatory transcriptional programs through BMAL1–YAP-bound enhancer rewiring. By elucidating how ageing reprograms transcriptional networks, our work highlights potential strategies to counteract chronic inflammation and restore tissue homeostasis across age-related loss of functionality.

This dataset

Open GSE294070 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 GSE294070_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 PRJNA1247994 and SRA study SRP577257. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

15 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 15 sample titles: 15 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

GSM8898282 Old_YAP_input
GSM8898283 Young_YAP_input
GSM8898284 Old_YAP_ChIP
GSM8898285 Young_YAP_ChIP
GSM8898286 ColXIV_KO_YAP_input
GSM8898287 ColXIV_WT_YAP_input
GSM8898288 ColXIV_KO_YAP_ChIP
GSM8898289 ColXIV_WT_YAP_ChIP
GSM8898290 Old_p65_input
GSM8898291 Young_p65_input
GSM8898292 Old_p65_ChIP
GSM8898293 Young_p65_ChIP
GSM8898294 Old_BMAL1_ChIP
GSM8898295 Young_BMAL1_ChIP
GSM8898296 BMAL1_Input

Datasets on a similar topic

GSE294069 BMAL1 and YAP cooperate to hijack enhancers and promote inflammation in the aged epidermis [ChIP-Seq 1] 20 samples shares bmal1, yap, cooperate, enhancers, epidermis, chip-seq, promote, hijack
GSE294389 BMAL1 and YAP cooperate to hijack enhancers and promote inflammation in the aged epidermis 131 samples shares bmal1, yap, cooperate, enhancers, epidermis, promote, hijack
GSE294336 BMAL1 and YAP cooperate to hijack enhancers and promote inflammation in the aged epidermis [RNA-seq Aged_adult] 48 samples shares bmal1, yap, cooperate, enhancers, epidermis, promote, hijack
GSE294339 BMAL1 and YAP cooperate to hijack enhancers and promote inflammation in the aged epidermis [RNA-seq Col14] 48 samples shares bmal1, yap, cooperate, enhancers, epidermis, promote, hijack
GSE300774 H3K9me3 controls epidermis development by repressing RNA Pol II activity on key promoters and enhancers 34 samples shares enhancers, epidermis, promote
GSE277188 Decoding the YAP/TAZ–PPARγ Regulatory Axis in Adipocyte Differentiation and Dedifferentiation [ChIP-seq] 46 samples shares yap, chip-seq
GSE274930 ZMAT1 promotes osteoclast formation and bone loss through TRIM46 mediated YAP1 degradation II 18 samples shares yap, promote
GSE327565 Sustained Yap/Taz activation promotes aberrant alveolar epithelial cell differentiation and drives persistent fibrotic remodeling 14 samples shares yap, promote

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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.