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Timecourse of FACS sorted Ly6C+ monocytes, tissue resident alveolar macrophages (trAMs), monocyte derived alveolar macrophages (bmAMs) and epithelial cells from SARS-CoV-2 (maVie16) vs. IAV (PR8) infected mouse lungs

GSE319684 Mus musculus (mouse) RNA-seq (gene expression) 176 samples Submitted 2026/02/23 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 176 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
176 samples: 36 conditions, mostly with about 4 replicates eachGroups 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)
Respiratory viral infections caused by SARS-CoV-2 and Influenza virus pose significant public health concerns, with severe outcomes for at-risk and even healthy patients. While disease severity is often associated with dysregulated monocyte-macrophage activities in patients, emerging evidence highlights the active role of infected epithelial cells in early viral defense with subsequent implications on disease severity.
Read the full summary ↓
We assessed the contribution of monocytes to host defense against respiratory viral infections and discovered that Ccr2-/- mice exhibited a markedly worsened outcome, increased viral load and more severe lung damage following SARS-CoV-2 infection, whereas we found similar disease severity upon Influenza A virus (IAV) infection. Both viral infections prompted early monocyte infiltration in wild-type mice, and longitudinal RNA sequencing of sorted lung monocytes and monocyte-derived macrophages in SARS-CoV-2 and IAV infection revealed transcriptionally similar yet temporally distinct gene expression patterns, including an induction of Interferon (IFN) type I and type II dependent genes. Interestingly, epithelial cell transcriptional responses differed significantly between SARS-CoV-2 and IAV infection. Our findings emphasize the significant role of epithelial cells in shaping the immune response during respiratory viral infections. The distinct interactions between epithelial cells, monocytes, and macrophages can lead to varying antiviral immune outcomes, as observed in SARS-CoV-2 and IAV infections.
This dataset
Open GSE319684 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 GSE319684_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 PRJNA1424955 and SRA study SRP677745. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
36 conditions, mostly with about 4 replicates each
FACS sorted epithelial cells_RNA,PBS,0Dpi, ×12 FACS sorted lung monocytes_RNA,PBS,0Dpi, ×12 FACS sorted alveolar macrophages_RNA,PBS,0Dpi, ×12 FACS sorted monocyte derived AM_RNA,PBS,0Dpi, ×12 FACS sorted epithelial cells_RNA,IAV,2Dpi, ×4 FACS sorted epithelial cells_RNA,IAV,4Dpi, ×4 FACS sorted epithelial cells_RNA,IAV,8Dpi, ×4 FACS sorted epithelial cells_RNA,IAV,28Dpi, ×4 +28 more

Supports a between-group comparison across 176 samples.

How we read this: 36 replicated groups read from 176 sample titles; they account for 176 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

+ 136 more — browse all 176 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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