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Sex difference in mRNA expressions of lungs post bleomycin-induced acute lung injury

GSE325299 Mus musculus (mouse) RNA-seq (gene expression) 20 samples Submitted 2026/04/01 Platform GPL17021
At a glance

RNA-seq (gene expression) · mouse · 20 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
20 samples: 20 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.
Summary (written by the submitters)
We performed mRNA sequencing to comprehensively and unbiasedly examine the transcriptional landscape of lung tissue in female and male rats following bleomycin acute lung injury (ALI). Comparative analysis of bleomycin-induced ALI transcriptional responses demonstrated marked sex differences in both magnitude and directionality. Males exhibited significantly greater transcriptional perturbation with 2,393 differentially expressed genes (DEGs) (1,602 upregulated, 791 downregulated) versus 1,533 DEGs in females (1,129 upregulated, 404 downregulated) (|log2FC| ≥ 1, FDR < 0.05).
Read the full summary ↓
Direct comparison of bleomycin-treated animals identified 826 DEGs (307 female-enriched, 519 male-enriched). Baseline sex differences were minimal, with only 262 DEGs between sham-treated animals (51 female-enriched, 211 male-enriched), indicating that observed transcriptional divergence primarily reflects sex-specific injury responses rather than constitutive sexual dimorphism. Gene Ontology (GO) analysis of these 826 DEGs began to define this polarity. The biological processes with the most divergent expression patterns included proteolysis (GO:0006508) and immune response (GO:0006955). Cellular components included both membrane and extracellular space (GO:0016020, GO:0005615), and molecular functions included protein binding (GO:0005515). KEGG pathway analysis further highlighted the contrast. Direct comparison between females and males revealed divergent pathways, including: cytokine-cytokine receptor interaction (ko04060), complement and coagulation cascades (ko04610), and ECM-receptor interaction (ko04512). A more granular analysis of the DEGs comprising these divergent functional categories and pathways identified male lungs selectively upregulating chemokines (Cxcl10, Cxcl11, Ccl17), complement/coagulation factors, (F7, Plg, C1qa), and components of the acute-phase protease inhibitor system (Timp1, Serpina3a, Tmprss9), whereas females induced BMP signaling genes (Bmpr2, Smad9, Bmp6) and an integrin scaffolding proteins (Itga1/2/9/11, Itgb3, Flrt3) . Notable findings from within-sex analyses showed females with enriched GO and KEGG themes related to extracellular matrix organization and cell-cycle progression, while males were more focused on immune pathways, specifically cytokine induction and viral response modules. A complete list of all DEGs across comparisons is provided in the supplementary materials.
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 GSE325299_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 PRJNA1439409 and SRA study SRP684898. Searching any of these in the dataset finder brings you back here.

Study design
20 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 20 sample titles: 20 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
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