GEO series

Deletion of SWI/SNF ATPase activity in hepatocytes of adult liver disrupts circadian gene expression and central liver functions [RNAseq]

GSE266938 Mus musculus (mouse) RNA-seq (gene expression) 82 samples Submitted 2025/12/01 Platform GPL24247

At a glance

RNA-seq (gene expression) · mouse · 82 samples

What it is: RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism: Mus musculus (mouse)
Samples: 82 samples: 82 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)

The circadian rhythm in the murine liver governs the activity of numerous enhancers which in turn coordinates diurnal gene expression. This process is controlled by oscillating activities of specific transcription factors (TFs) and recruitment of co-regulators, including histone modifying enzymes and chromatin remodeling complexes. Several circadian controlled TFs interact with the SWI/SNF family of chromatin remodeling complexes to control chromatin accessibility.

Read the full summary ↓

To unravel the significance of SWI/SNF ATPase subunits in circadian chromatin remodeling, we mapped chromatin accessibility, SWI/SNF occupancy, and gene expression throughout a day in murine liver. We found remarkable remodeling during fasting-to-fed transitions, and a third of circadian enhancers exhibited circadian SWI/SNF occupancy and accessibility. Intriguingly, genetic disruption of either of the two mutually exclusive ATPases of SWI/SNF had minor effects on chromatin accessibility in circadian enhancers, indicating redundancy. However, simultaneous disruption of both ATPases caused a collapse of the chromatin landscape, liver damage and inflammation. This disruption abolishes rhythmic expression of metabolic genes without affecting oscillation of the core circadian clock. In summary, this suggests an indispensable role of SWI/SNF-mediated chromatin remodeling of enhancers for circadian transcriptomic rhythms and basic liver function.

This dataset

Open GSE266938 in finder → Find more mouse RNA-seq 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 GSE266938_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1108748 and SRA study SRP506275. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

82 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 82 sample titles: 82 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

GSM8257107 liver, WT, ZT2, rep1, RNA-seq
GSM8257108 liver, WT, ZT2, rep2, RNA-seq
GSM8257109 liver, WT, ZT2, rep3, RNA-seq
GSM8257110 liver, WT, ZT6, rep1, RNA-seq
GSM8257111 liver, WT, ZT6, rep2, RNA-seq
GSM8257112 liver, WT, ZT6, rep3, RNA-seq
GSM8257113 liver, WT, ZT10, rep1, RNA-seq
GSM8257114 liver, WT, ZT10, rep2, RNA-seq
GSM8257115 liver, WT, ZT10, rep3, RNA-seq
GSM8257116 liver, WT, ZT14, rep1, RNA-seq
GSM8257117 liver, WT, ZT14, rep2, RNA-seq
GSM8257118 liver, WT, ZT14, rep3, RNA-seq
GSM8257119 liver, WT, ZT18, rep1, RNA-seq
GSM8257120 liver, WT, ZT18, rep2, RNA-seq
GSM8257121 liver, WT, ZT18, rep3, RNA-seq
GSM8257122 liver, WT, ZT22, rep1, RNA-seq
GSM8257123 liver, WT, ZT22, rep2, RNA-seq
GSM8257124 liver, WT, ZT22, rep3, RNA-seq
GSM8257125 liver, BRG1/BRM, rep1, RNA-seq
GSM8257126 liver, BRG1/BRM, rep2, RNA-seq
GSM8257127 liver, BRG1/BRM, rep3, RNA-seq
GSM8257128 liver, BRG1/BRM, rep4, RNA-seq
GSM8257129 liver, BRMKO, rep1, RNA-seq
GSM8257130 liver, BRMKO, rep2, RNA-seq
GSM8257131 liver, BRMKO, rep3, RNA-seq
GSM8257132 liver, BRMKO, rep4, RNA-seq
GSM8257133 liver, L-BRG1KO, rep1, RNA-seq
GSM8257134 liver, L-BRG1KO, rep2, RNA-seq
GSM8257135 liver, L-BRG1KO, rep3, RNA-seq
GSM8257136 liver, L-BRG1KO, rep4, RNA-seq
GSM8257137 liver, dKO, rep1, RNA-seq
GSM8257138 liver, dKO, rep2, RNA-seq
GSM8257139 liver, dKO, rep3, RNA-seq
GSM8257140 liver, dKO, rep4, RNA-seq
GSM8257141 liver, BRMKO, ZT2, rep1, RNA-seq
GSM8257142 liver, BRMKO, ZT2, rep2, RNA-seq
GSM8257143 liver, BRMKO, ZT2, rep3, RNA-seq
GSM8257144 liver, BRMKO, ZT2, rep4, RNA-seq
GSM8257145 liver, dKO, ZT2, rep1, RNA-seq
GSM8257146 liver, dKO, ZT2, rep2, RNA-seq

+ 42 more — browse all 82 samples with per-sample file links →

Datasets on a similar topic

GSE248369 The Swi/Snf chromatin remodeling complex regulates pancreatic endocrine cell expansion and differentiation in vivo 10 samples shares swi, snf
GSE242803 SWI/SNF directed epigenetic and transcriptional response during macrophage inflammatory activation. 134 samples shares swi, snf
GSE272849 EOMES establishes mesoderm and endoderm differentiation potential through SWI/SNF-mediated global enhancer remodeling 119 samples shares swi, snf
GSE226954 SWI/SNF-dependent genes are defined by their chromatin landscape 61 samples shares swi, snf
GSE268206 CRISPR screen decodes SWI/SNF chromatin remodeling complex assembly 56 samples shares swi, snf
GSE253379 Differential roles of copper-binding transcription factors and the subfamilies of the SWI/SNF complex in the transcriptional regulation of the skeletal muscle lineage 36 samples shares swi, snf
GSE249211 SWI/SNF-dependent genes are defined by their chromatin landscape [ChIP-seq_2] 24 samples shares swi, snf
GSE274357 Precise modulation of mSWI/SNF identified dosage-sensitive chromatin regulation [ATAC-Seq] 14 samples shares swi, snf

Search all mouse RNA-seq 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.