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Pervasive nuclear envelope ruptures precede ECM signaling and disease onset without activating cGAS-STING in Lamin cardiomyopathy mice [sci-RNA-seq]

GSE241587 Mus musculus (mouse) RNA-seq (gene expression) 96 samples Submitted 2024/04/26 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 96 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
96 samples: 96 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
Pervasive nuclear envelope ruptures precede ECM signaling and disease onset without activating cGAS-STING in Lamin-cardiomyopathy miceCell reports · 2024
Summary (written by the submitters)
Nuclear envelope (NE) ruptures are emerging observations in Lamin-related dilated cardiomyopathy, an adult-onset disease caused by loss-of-function mutations in Lamin A/C, a nuclear lamina component. Here, we test a prevailing hypothesis that NE ruptures trigger the pathological cGAS-STING cytosolic DNA-sensing pathway using a mouse model of Lamin cardiomyopathy.
Read the full summary ↓
The reduction of Lamin A/C in cardiomyocytes of adult mice causes pervasive NE ruptures in cardiomyocytes, preceding inflammatory transcription, fibrosis, and fatal dilated cardiomyopathy. NE ruptures are followed by DNA damage accumulation without causing immediate cardiomyocyte death. However, cGAS-STING-dependent inflammatory signaling remains inactive. Deleting cGas or Sting does not rescue cardiomyopathy. The lack of cGAS-STING activation is likely due to the near absence of cGAS expression in adult cardiomyocytes at baseline. Instead, extracellular matrix (ECM) signaling is activated and predicted to initiate pro-inflammatory communication from Lamin-reduced cardiomyocytes to fibroblasts. Our work nominates ECM signaling, not cGAS-STING, as a potential inflammatory contributor in Lamin cardiomyopathy.
Published in
Pervasive nuclear envelope ruptures precede ECM signaling and disease onset without activating cGAS-STING in Lamin-cardiomyopathy mice
En A, Bogireddi H, Thomas B et al. · Cell reports 2024 · PMID 38814785 · doi:10.1016/j.celrep.2024.114284
This dataset
Open GSE241587 in finder → Find more mouse 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 GSE241587_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 PRJNA1008736 and SRA study SRP456772. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38814785) ↗
Study design
96 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 96 sample titles: 96 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

+ 56 more — browse all 96 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.