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Influenza virus-induced type I interferons disrupt alveolar epithelial repair and tight junction integrity in the developing lung

GSE287098 Mus musculus (mouse) RNA-seq (gene expression) 96 samples Submitted 2025/02/22 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 96 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
96 samples: 96 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.
Paper
Influenza virus-induced type I interferons disrupt alveolar epithelial repair and tight junction integrity in the developing lungMucosal immunology · 2025
Summary (written by the submitters)
Type I interferons (IFN-I) are key innate immune mediators which control viral infection in adults. Recently, using a neonatal murine model of influenza A infection (IAV), we demonstrated that IAV-infected murine neonates lacking a functional IFN-I receptor (IFNAR-/-) have significantly improved survival and reduced lung pathology relative to wild-type (WT) neonates.
Read the full summary ↓
However, the opposite is observed in adults, with IAV-infected IFNAR-/- adults exhibiting enhanced morbidity relative to WT adults, indicating an age-specific IFN-I toxicity in neonates. Therefore, we hypothesized that IAV-induced IFN-I signaling in primary neonatal type II alveolar epithelial cells (TIIECs), the main cell type of IAV infection and initiator of host response in the lung, contributed to age-specific viral pathogenesis. To investigate the role of IFN-I signaling in TIIECs, we performed RNA-Seq on purified TIIECs in a multifactorial design, comparing 1. IFNAR-/- and WT genotypes, 2. neonatal and adult ages, 3. IAV-infected and uninfected, 4. over a three-day time course.Analysis of purified TIIECs revealed age, not infection status, as the primary driver of transcriptional differences in TIIECs. Subsequent pathway analysis demonstrated IAV-infected IFNAR-/- neonates significantly upregulate cell proliferation, tissue repair and tight junction genes at 2-days post-infection (dpi), compared to WT neonates. Next, to determine if these growth and repair differences persisted later in infection, targeted analysis of repair gene expression and immunofluorescent quantification of pulmonary sealing tight junction molecules ZO-1 and occludin was performed at 6-dpi. Relative to WT neonates, IFNAR-/- neonates had significantly higher whole lung occludin staining and repair gene expression. Together, our data demonstrates IFN-I signaling is extremely pathogenic in the developing lung because by disrupting alveolar repair and pulmonary barrier integrity.
Published in
Influenza virus-induced type I interferons disrupt alveolar epithelial repair and tight junction integrity in the developing lung
Onufer AP, Mell JC, Cort L et al. · Mucosal immunology 2025 · PMID 39984053 · doi:10.1016/j.mucimm.2025.02.002
This dataset
Open GSE287098 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 GSE287098_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 PRJNA1211121 and SRA study SRP557611. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39984053) ↗
Study design
96 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 96 sample titles: 96 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

+ 56 more — browse all 96 samples with per-sample file links →

Datasets on a similar topic

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