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The role of Cebpb in Alcohol-associated Liver Disease development and resolution

GSE276692 Mus musculus (mouse) RNA-seq (gene expression) 24 samples Submitted 2024/09/12 Platform GPL23479
At a glance

RNA-seq (gene expression) · mouse · 24 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
24 samples
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
Continuous Activation of C/EBPβ Transcription Factor Prevents Fibrosis Resolution After Alcohol CessationCellular and molecular gastroenterology and hepatology · 2025
Summary (written by the submitters)
Abstinence is an important therapeutic intervention for patients with alcohol-associated liver disease (ALD). However, fibrosis improvement after cessation is not uniform and some patients do not improve. We aimed to use scATAC-seq analysis in a mouse model of ALD to define the mechanism of poor ALD resolution. We analyzed differentially accessible regions in livers from control, ALD, or 4 weeks post alcohol cessation mice and identified transcription factors activated in ALD that remained activated after alcohol withdrawal.
Read the full summary ↓
The top hit was C/EBPβ. We found that hepatocyte specific Cebpb knockout prevented ALD development, while knockout at the time of alcohol cessation promoted fibrosis resolution.
Published in
Continuous Activation of C/EBPβ Transcription Factor Prevents Fibrosis Resolution After Alcohol Cessation
Schonfeld M, Nataraj K, Mah S et al. · Cellular and molecular gastroenterology and hepatology 2025 · PMID 40288442 · doi:10.1016/j.jcmgh.2025.101525
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 GSE276692_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: 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 PRJNA1158711 and SRA study SRP531485. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 24 more — browse all 24 samples with per-sample file links →

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