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Macrophage-derived oncostatin M repairs the lung epithelial barrier during inflammatory damage

GSE287742 Mus musculus (mouse) RNA-seq (gene expression) 11 samples Submitted 2025/07/10 Platform GPL19057
At a glance

RNA-seq (gene expression) · mouse · 11 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
11 samples
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)
Tissue repair programs must function alongside antiviral immunity to restore the lung epithelial barrier following infection. We found that macrophage-derived oncostatin M (OSM) counteracted the pathological effects of type I interferon (IFN-I) during infection and damage in mice. At baseline, OSM-deficient mice exhibited altered alveolar type II (ATII) epithelial cell states.
Read the full summary ↓
In response to influenza or viral mimic challenge, mice lacking OSM exhibited heightened IFN-I responses and increased mortality. Furthermore, OSM promoted organoid formation despite the growth-inhibitory effects of IFN-I. These findings identify OSM as an indispensable macrophage-derived growth factor that maintains the homeostasis of lung epithelial cells and promotes their proliferation to overcome IFN-I-mediated immunopathology.
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 GSE287742_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: 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 PRJNA1214361 and SRA study SRP559218. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 11 more — browse all 11 samples with per-sample file links →

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