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IFN-gamma signaling early during infection dramatically enhances antiviral programs in epithelial cells

GSE299808 Homo sapiens (human) RNA-seq (gene expression) 45 samples Submitted 2025/12/17 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 45 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
Homo sapiens (human)
Samples
45 samples: 44 distinct titles, 1 of them repeatedGroups 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
Human lung CD8(+) tissue-resident memory T cell-derived interferon-γ orchestrates subset-specific antiviral programming in airway epithelial cellsImmunity · 2025
Summary (written by the submitters)
To examine the impact of IFNγ signaling on human airway epithelial cells during influenza virus infection, we used differentiated air–liquid interface (ALI) cultures of normal human bronchial epithelial cells. Cultures were infected with influenza A/Netherlands/602/2009 (H1N1) and treated with recombinant IFNγ 4 hours post-infection. At 18 hours post-infection, basal, secretory, and ciliated epithelial cells were separated by FACS and analyzed by bulk RNA sequencing.
Read the full summary ↓
IFNγ treatment after infection induced a distinct transcriptional signature across all epithelial subsets compared to infection alone, with basal cells showing the strongest transcriptional response. These data provide insight into epithelial subset–specific responses to IFNγ in the context of viral infection and reveal how early cytokine signaling can enhance antiviral programs in the human airway epithelium.
Published in
Human lung CD8(+) tissue-resident memory T cell-derived interferon-γ orchestrates subset-specific antiviral programming in airway epithelial cells
Mattingly CLR, Jimenez AR, Williams ME et al. · Immunity 2025 · PMID 41308652 · doi:10.1016/j.immuni.2025.11.003
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 GSE299808_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 PRJNA1276554 and SRA study SRP591950. Searching any of these in the dataset finder brings you back here.

Study design
44 distinct titles, 1 of them repeated
Basal.2E ×2

How we read this: Read from 45 sample titles: 44 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

+ 5 more — browse all 45 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.