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Toll-like Receptor 4 Induces Trained Innate Immune Tolerance in the Heart in a Model of Stress-induced Cardiomyopathy [ATAC-seq]

GSE305274 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 12 samples Submitted 2025/09/22 Platform GPL34290
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 × Bulk ATAC seq, bone marrow, PBS, vs 3 × Bulk ATAC seq, bone marrow, LPS, vs 3 × Bulk ATAC seq, bone marrow, IFN, vs 3 × Bulk ATAC seq, bone marrow, ISO,Groups 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
Toll-like receptor 4 induces trained innate immune tolerance in the heart in a model of stress-induced cardiomyopathyCardiovascular research · 2025
Summary (written by the submitters)
This study aimed to determine the mechanism by which TLR4 activation establishes cardiac protection in mice subjected to isoproterenol-induced cardiac injury. We performed bulk ATAC sequencing to determine if this was set up through epigenetic means, which would suggest a mechanism consistent with trained innate immune tolerance.
Published in
Toll-like receptor 4 induces trained innate immune tolerance in the heart in a model of stress-induced cardiomyopathy
Lim KRQ, Amrute J, Kovacs A et al. · Cardiovascular research 2025 · PMID 40924855 · doi:10.1093/cvr/cvaf158
This dataset
Open GSE305274 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 GSE305274_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 PRJNA1304972 and SRA study SRP608489. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40924855) ↗
Study design
3 × Bulk ATAC seq, bone marrow, PBS, vs 3 × Bulk ATAC seq, bone marrow, LPS, vs 3 × Bulk ATAC seq, bone marrow, IFN, vs 3 × Bulk ATAC seq, bone marrow, ISO,

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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