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A longitudinal atlas of post-viral lung regeneration reveals persistent injury-associated cell states

GSE262927 Mus musculus (mouse) RNA-seq (gene expression) 33 samples Submitted 2024/12/16 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 33 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
33 samples: 12 conditions, mostly in duplicateGroups 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
Longitudinal single-cell profiles of lung regeneration after viral infection reveal persistent injury-associated cell statesCell stem cell · 2025
Summary (written by the submitters)
Functional regeneration of the lung’s gas exchange surface following injury requires the coordination of a complex series of cell behaviors within the alveolar niche. Using a multi-modal approach, we have mapped the temporal sequencing of mouse lung regeneration after acute viral injury, demonstrating that this response is asynchronously phased across different cellular compartments.
Read the full summary ↓
This longitudinal atlas of regeneration has produced a catalogue of new cell states that reflect transient and persistent transcriptional alterations in daughter cells as they transit across axes of differentiation. These new cell states include an injury-induced capillary endothelial cell (iCAP) that arises after injury, persists indefinitely, and shares transcriptional hallmarks with both developing lung endothelium and the endothelial aberrations found in degenerative human lung diseases. This comprehensive atlas of lung regeneration provides a foundational resource to understand the complexity of the cellular and molecular responses to injury, reveals the critical importance of capillary endothelium in maintaining and rebuilding the alveolar niche after injury, and correlates these responses to those found in development and human lung diseases.
Published in
Longitudinal single-cell profiles of lung regeneration after viral infection reveal persistent injury-associated cell states
Niethamer TK, Planer JD, Morley MP et al. · Cell stem cell 2025 · PMID 39818203 · doi:10.1016/j.stem.2024.12.002
This dataset
Open GSE262927 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 GSE262927_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 PRJNA1094929 and SRA study SRP499028. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39818203) ↗
Study design
12 conditions, mostly in duplicate
KitMCM_H1N1_tam-pre_sac19 ×3 EdnrbCre_H1N1_tam-pre_sac19 ×3 Ki67Cre_H1N1_tam02_sac06 ×2 Ki67Cre_H1N1_tam07_sac11 ×2 Ki67Cre_H1N1_tam14_sac19 ×2 Ki67Cre_H1N1_tam21_sac25 ×2 Ki67Cre_H1N1_tam02_sac42 ×2 Ki67Cre_H1N1_tam07_sac42 ×2 +11 more

Supports a between-group comparison across 26 samples.

How we read this: 12 replicated groups read from 33 sample titles; they account for 26 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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