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Chromatin remodeling in HIF-1a deficient B cell during IgA class switching [ChIP-seq]

GSE228366 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 12 samples Submitted 2025/01/08 Platform GPL17021
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 12 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
12 samples: 3 × K9_WT vs 3 × K9_KO vs 3 × K27_WT vs 3 × K27_KOGroups 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
Metabolic rewiring controlled by HIF-1α tunes IgA-producing B-cell differentiation and intestinal inflammationCellular & molecular immunology · 2025
Summary (written by the submitters)
The interconnection between metabolic programming and chromatin remodeling during IgA class switching suggest that HIF-1a-dependent glycolytic flux may control the epigenetic modification at α class switching region (Sα) in the Igh locus. To test our hypothesis, histone acetylation was analyzed by chromatin immunoprecipitation sequencing (ChIP-seq) (H3K9ac and H3K27ac) in Hif-1a deficient and control B cell during IgA class switching. Chromatin immunoprecipitation DNA-sequencing (ChIP-seq) for histone modifications H3K27ac and H3K9ac in B cell from WT and HIF-1a deficient mice.
Published in
Metabolic rewiring controlled by HIF-1α tunes IgA-producing B-cell differentiation and intestinal inflammation
Meng X, Asadi-Asadabad S, Cao S et al. · Cellular & molecular immunology 2025 · PMID 39543372 · doi:10.1038/s41423-024-01233-y
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 GSE228366_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 PRJNA949562 and SRA study SRP429732. Searching any of these in the dataset finder brings you back here.

Study design
3 × K9_WT vs 3 × K9_KO vs 3 × K27_WT vs 3 × K27_KO

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 of them. 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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