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Early cell autonomous and niche-mediated alveolar epithelial response to influenza infection in primary lung organoids

GSE327614 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 24 samples Submitted 2026/04/10 Platform GPL24676Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 24 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Homo sapiens (human)
Samples
24 samples: 24 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.
Summary (written by the submitters)
Influenza A virus (IAV) infection is a significant cause of morbidity and mortality for patients worldwide. Alveolar type 2 (AT2) cells are the preferential target of IAV as part of the pathogenesis of viral pneumonia and acute respiratory distress syndrome (ARDS). Early IAV infection of alveolar cells has been challenging to model both in vitro and in vivo.
Read the full summary ↓
To address this challenge, we used a combination of murine and human primary alveolar organoids to define methods for robust IAV infection and evaluated cell-autonomous consequences of IAV using a temporal series of multiome paired single nuclei RNA/ATAC sequencing. Infected AT2 cells undergo conserved changes defined by early loss of surfactant secretion, decreased lipid biogenesis, a rapid burst of antiviral response, and late viral-mediated suppression. Surprisingly, uninfected AT2 cells undergo substantial transcriptional and epigenomic changes in IAV-treated cultures, leading to transition to damage-associated cell states within hours via a process driven by the inflammatory milieu of murine organoids. Together, these data provide new methods for high-fidelity modeling of IAV infection in alveolar cells and define a conserved AT2 cell response signature to IAV with implications for ARDS pathogenesis.
This dataset
Open GSE327614 in finder → Find more 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 GSE327614_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1451530 and SRA study SRP690828. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
24 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 24 sample titles: 24 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
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.