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Influenza-induced activation of recruited alveolar macrophages during the early inflammatory phase drives lung injury and lethality

GSE182637 Mus musculus (mouse) RNA-seq (gene expression) 27 samples Submitted 2024/08/01 Platform GPL19057
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: 8 conditions, mostly in triplicateGroups 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 identify gene expression patterns associated with three distinct phases (Infiltrating, Early Inflammatory, Late Inflammatory) in the influenza A virus response of recruited alveolar macrophages. In the Early Inflammatory phase, recruited macrophages begin expressing pro-inflammatory genes, driving cytokine-mediated lung damage and contributing to the morbidity observed in influenza-infected wild-type mice.
Read the full summary ↓
In mice lacking vimentin (Vim-/-), genes associated with the Early Inflammatory phase are suppressed, while the expression of the Infiltrating Phase genes is maintained, which is associated with protection from influenza-induced injury. Using a bone-marrow chimera mouse model, we validate that Vim-/- recruited alveolar macrophages are sufficient to confer protection from influenza-induced mortality. Our results define the temporal dynamics of gene expression in recruited alveolar macrophages, which shape the host response to infection with respiratory viruses.
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 GSE182637_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 PRJNA757241 and SRA study SRP333843. Searching any of these in the dataset finder brings you back here.

Study design
8 conditions, mostly in triplicate
MoAM WT D6 ×4 MoAM VimKO D3 ×4 MoAM VimKO D6 ×4 MoAM WT D2 ×3 MoAM WT D3 ×3 MoAM WT D4 ×3 MoAM VimKO D2 ×3 MoAM VimKO D4 ×3

Supports a between-group comparison across 27 samples.

How we read this: 8 replicated groups read from 27 sample titles; they account for 27 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
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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.