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Siglec-F Protects Against Elastase-induced Lung Inflammation and Emphysema in Mice

GSE307353 Mus musculus (mouse) RNA-seq (gene expression) 27 samples Submitted 2026/02/24 Platform GPL28330
At a glance

RNA-seq (gene expression) · mouse · 27 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
27 samples: 3 × RAM_BAL_WT_naive vs 3 × RAM_BAL_KO_naive vs 3 × RAM_BAL_WT_d21 vs 3 × RAM_BAL_KO_d21Groups 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
Siglec-F Protects Against Elastase-induced Lung Inflammation and Emphysema in MicebioRxiv : the preprint server for biology · 2025
Summary (written by the submitters)
Airspace macrophages (AMs) are essential for maintaining lung homeostasis. Their activity must be tightly controlled to prevent excessive immune responses and tissue damage, such as emphysematous alveolar destruction. Siglec-F is a canonical marker of AMs, but its functional role in lung disease remains unclear. Here, we investigated the role of Siglec-F in a murine model of elastase-induced emphysema.
Read the full summary ↓
We found that Siglec-F-deficient mice exhibited worsened emphysematous phenotypes, along with accumulation and transcriptional reprogramming of resident AMs (RAMs). Transcriptomic profiling of Siglec-F-deficient RAMs revealed dysregulation of key pathways involved in tissue repair, including extracellular matrix degradation, TGF-β signaling, and phagocytosis. These findings demonstrate that Siglec-F is critical for restraining RAM activity and preserving alveolar integrity during injury. Our study provides new insight into the immunoregulatory function of Siglec-F in a tissue-destructive context and highlights the potential protective roles of Siglec signaling in chronic lung disease.
Published in
Siglec-F Protects Against Elastase-induced Lung Inflammation and Emphysema in Mice
Ye Q, Hara N, Hu Y et al. · bioRxiv : the preprint server for biology 2025 · PMID 41000867 · doi:10.1101/2025.09.16.674299
This dataset
Open GSE307353 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 GSE307353_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 PRJNA1316976 and SRA study SRP617616. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41000867) ↗
Study design
3 × RAM_BAL_WT_naive vs 3 × RAM_BAL_KO_naive vs 3 × RAM_BAL_WT_d21 vs 3 × RAM_BAL_KO_d21

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from the first 12 of 27 sample titles; they account for 12 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

+ 15 more — browse all 27 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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