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Spatially clustered type I interferon responses at injury borderzones

GSE269054 Mus musculus (mouse) RNA-seq (gene expression) 37 samples Submitted 2024/08/06 Platform GPL34290Platform GPL24676Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 37 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
37 samples: 37 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
Spatially clustered type I interferon responses at injury borderzonesNature · 2024
Summary (written by the submitters)
Sterile inflammation after myocardial infarction (MI) is classically credited to myeloid cells interacting with dead cell debris in the infarct zone (IZ). Here, we show that borderzone cardiomyocytes are the dominant initiators of a novel type I interferon (IFN) response in the infarct borderzone zone (BZ).
Read the full summary ↓
Using spatial transcriptomics analysis of mice and humans, we find that MI induces colonies of interferon induced cells (IFNICs) expressing interferon stimulated genes (ISGs) decorating the BZ, where cardiomyocytes experience mechanical stress, nuclear rupture, and escape of chromosomal DNA. Cardiomyocyte-selective deletion of interferon regulatory factor 3 (Irf3) abrogated IFNIC colonies, whereas mice lacking Irf3 in fibroblasts, macrophages, neutrophils, or endothelial cells; Ccr2-deficient mice; or plasmacytoid dendritic cell-depleted mice did not. IFNs blunted the protective matricellular programs and contractile function of BZ fibroblasts, and increased vulnerability to pathologic remodeling. In mice that died after MI, IFNIC colonies were immediately adjacent to sites of ventricular rupture, while mice lacking IFNICs were protected from rupture and exhibited improved survival. Together, these results reveal a pathologic BZ niche characterized by a cardiomyocyte-initiated innate immune response. We suggest that selective inhibition of Irf3 activation in non-immune cells of the borderzone could limit ischemic cardiomyopathy while avoiding broad immunosuppression.
Published in
Spatially clustered type I interferon responses at injury borderzones
Ninh VK, Calcagno DM, Yu JD et al. · Nature 2024 · PMID 39198639 · doi:10.1038/s41586-024-07806-1
This dataset
Open GSE269054 in finder → Find more 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 GSE269054_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 PRJNA1120028 and SRA study SRP511768. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39198639) ↗
Study design
37 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 37 sample titles: 37 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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