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Effect of external cues on clock-driven time-of-day specific protection from Influenza A infection

GSE288858 Mus musculus (mouse) RNA-seq (gene expression) 15 samples Submitted 2025/02/08 Platform GPL34328
At a glance

RNA-seq (gene expression) · mouse · 15 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
15 samples: 15 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
Effect of external cues on clock-driven protection from influenza A infectionThe Journal of clinical investigation · 2025
Summary (written by the submitters)
Influenza and other respiratory viral pathogens are leading causes of mortality and morbidity. We have previously shown that circadian rhythms confer temporal protection from influenza infection. Here, we investigate whether the endogenous circadian clocks need optimal cycling of entraining cues to mediate this protection. We used two key entraining factors-- light-dark cycling and meal timing-- to determine their relative importance in allowing the host to benefit from its endogenous circadian rhythms.
Read the full summary ↓
First, we demonstrate that disrupting environmental lighting cues, within a critical window of vulnerability, abrogated the time-of-day specific protection; this poor outcome is mediated by a dysregulated immune response evidenced by the accumulation of inflammatory monocytes and CD8+ cells in the lungs and transcriptomic profile with an exaggerated immune response. Importantly, rhythmic meal timing mitigated the adverse effects of disrupted light cycles. Our findings highlight the crucial interplay between peripheral and central clocks in shaping influenza outcomes, offering significant translational potential for improving the care of critically ill patients with respiratory viral infections.
Published in
Effect of external cues on clock-driven protection from influenza A infection
Paul O, Brooks TG, Shetty A et al. · The Journal of clinical investigation 2025 · PMID 41243965 · doi:10.1172/JCI193133
This dataset
Open GSE288858 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 GSE288858_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 PRJNA1219641 and SRA study SRP561827. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41243965) ↗
Study design
15 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 15 sample titles: 15 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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