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ChIP-seq of RNA polymerase II and HNF4alpha in mouse liver after cytokine stimulation (WT vs TG)

GSE322777 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 9 samples Submitted 2026/04/01 Platform GPL13112
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 9 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
9 samples: 9 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
Inflammation-Driven Downregulation of CYP2E1 Is Associated with Attenuated Diethylnitrosamine (DEN)-Induced HepatocarcinogenesisCells · 2026
Summary (written by the submitters)
ChIP-seq was performed on liver samples from 6-week-old male mice (WT and TG) following a single intravenous injection of mouse TNFalpha (BioLegend, 7.5 ug/kg) or vehicle. Livers were collected 4 h post-injection. ChIP was carried out using anti-RNA polymerase II (Active Motif) or anti-HNF4alpha (Abcam) with matched input controls. Single-end reads were sequenced on an Illumina HiSeq 2000 platform, aligned to the mouse reference genome (mm10) using Bowtie, and peaks were called using MACS2 (v2.0.10.20120913) with matched input controls.
Published in
Inflammation-Driven Downregulation of CYP2E1 Is Associated with Attenuated Diethylnitrosamine (DEN)-Induced Hepatocarcinogenesis
Tsuchiya Y, Sotomaru Y, Kanai A et al. · Cells 2026 · PMID 41892336 · doi:10.3390/cells15060546
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 GSE322777_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 PRJNA1431464 and SRA study SRP680698. Searching any of these in the dataset finder brings you back here.

Study design
9 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 9 sample titles: 9 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
Datasets on a similar topic

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