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Integrative Single-Cell RNA and ATAC Sequencing Reveals the Impact of Chronic Cigarette Smoking on Lung Epithelial Responses to Influenza and Hyperoxia

GSE294221 Mus musculus (mouse) Single-cell RNA-seq 12 samples Submitted 2025/04/10 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.
Organism
Mus musculus (mouse)
Samples
12 samples: 6 × Multiome, murine lung tissue, GEX vs 6 × Multiome, murine lung tissue, ATACGroups 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)
Cigarette smoking is a significant risk factor for developing acute respiratory distress syndrome (ARDS), but the cellular and molecular mechanisms linking smoking to ARDS susceptibility remain unclear. Our goal was to improve our understanding of these mechanisms. To address this, we established a mouse model comparing long-term cigarette smoke exposure to non-smoking controls, examining responses to influenza infection and hyperoxia-induced lung injury.
Read the full summary ↓
Six mice were divided into two groups: a non-smoking control and a smoking group subjected to cigarette smoke exposure for six months. After exposure, mice underwent infection with influenza virus or were subjected to hyperoxia. Single-cell RNA sequencing (scRNA-seq) and single-cell ATAC sequencing (scATAC-seq) were performed on lung tissues. Quality control analysis using Seurat (v5.1.0) and Signac (v1.13.1) retained 78,402 cells from scRNA-seq and 84,144 cells from scATAC-seq, with 32,305 matched cells identified across both datasets. Differential gene expression analysis revealed significant smoking-associated alterations in cellular responses to influenza infection and hyperoxia exposure. Pathway enrichment indicated heightened immune responses, inflammatory signaling, and cellular survival pathways in smoking-exposed animals. Integration of scRNA-seq and scATAC-seq identified key transcription factors (TFs), including those involved in immune regulation, chromatin remodeling, and cell survival, mediating these responses. Overall, this study underscores the role of chronic cigarette smoke exposure in exacerbating pathways critical to ARDS pathogenesis, providing potential targets for therapeutic intervention.
This dataset
Open GSE294221 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 GSE294221_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: 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 PRJNA1248758 and SRA study SRP577652. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 × Multiome, murine lung tissue, GEX vs 6 × Multiome, murine lung tissue, ATAC

Supports a between-group comparison across 12 samples.

How we read this: 2 replicated groups read from 12 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
Datasets on a similar topic

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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.