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Egr1 is a master regulator of regenerative senescence and cardiac repair

GSE255181 Mus musculus (mouse) Single-cell RNA-seq 12 samples Submitted 2024/05/06 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 12 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
12 samples: 2 × Egr1_KO_Agrin vs 2 × Egr1_WT_Agrin vs 2 × Egr1 WT_PBS vs 2 × Egr1 KO_PBSGroups 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.
Summary (written by the submitters)
Senescence plays a key role in various physiological and pathological processes. We reported that injury-induced transient senescence correlates with heart regeneration, yet the multi-omics profile and molecular underpinnings of regenerative senescence remain obscure. Using proteomics and single-cell RNA-sequencing, here we report the regenerative senescence multi-omic signature in the adult mouse heart and establish its role in neonatal heart regeneration and Agrin-mediated cardiac repair in adult mice.
Read the full summary ↓
We identified early growth response protein 1 (Egr1) as a regulator of regenerative senescence in both models. In the neonatal heart, Egr1 facilitates angiogenesis and cardiomyocyte proliferation. In adult hearts, Agrin-induced senescence and repair require Egr1, activated by the integrin/FAK-ERK/Akt1 axis in cardiac fibroblasts. We also identified cathepsins as injury-induced senescence-associated secretory phenotype (SASP) components that promote ECM degradation and potentially assist in reducing fibrosis. Altogether, we uncovered the molecular signature and functional benefits of regenerative senescence during heart regeneration, with Egr1 orchestrating the process.
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 GSE255181_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1073899 and SRA study SRP488489. Searching any of these in the dataset finder brings you back here.

Study design
2 × Egr1_KO_Agrin vs 2 × Egr1_WT_Agrin vs 2 × Egr1 WT_PBS vs 2 × Egr1 KO_PBS

Supports a between-group comparison across 8 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 8 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
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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.