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Circadian Rhythm in Coronavirus Pneumonia Severity

GSE301278 Mus musculus (mouse) RNA-seq (gene expression) 91 samples Submitted 2026/07/01 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 91 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
91 samples: 24 conditions, mostly with about 4 replicates eachGroups 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
Biological Rhythms in Coronavirus Pneumonia PathogenesisJournal of biological rhythms · 2026
Summary (written by the submitters)
The goal of this experiment is to examine how circadian rhythms affect coronavirus pneumonia severity. To this end, we infected mice at different times of day with mouse hepatitis virus-1 (MHV-1), which is a beta-coronavirus native to rodents that produces similar histological features as SARS, MERS, and COVID-19. Bulk RNAseq was used to generate a list of differentially expressed genes (DEGs) based on the circadian time of MHV-1 exposure.
Read the full summary ↓
mice The cells were synchronized with 100nM dexmethosone to produce coherent circadian gene expression patterns in the cultures. Cells were then longitudinally harvested every 4 hours for 48 hours starting 12 hours after dexamethasone treatment. To obtain basic spatial information, we also analyzed lung parenchyma and BAL cells separately, representing the lung parenchyma and luminal airspace compartment that is largely composed of AMs and other luminal macrophages. In both the lung parenchyma and BAL, the number of time-sensitive DEGs also peaked at 2 DPI. DEGs overexpressed with ZT6 infection proved functionally enriched for inflammatory pathways, interferon signaling, and circadian rhythms.
Published in
Biological Rhythms in Coronavirus Pneumonia Pathogenesis
Mok H, Gierasch C, Ostendorf E et al. · Journal of biological rhythms 2026 · PMID 42304657 · doi:10.1177/07487304261449284
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 GSE301278_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 PRJNA1284671 and SRA study SRP596347. Searching any of these in the dataset finder brings you back here.

Study design
24 conditions, mostly with about 4 replicates each
Lung, MHV1 infection, ZT6 time point, collect… ×5 Lung, MHV1 infection, ZT12 time point, collec… ×4 Lung, MHV1 infection, ZT12 time point, collec… ×4 Lung, MHV1 infection, ZT6 time point, collect… ×4 Lung, MHV1 infection, ZT6 time point, collect… ×4 Lung, MHV1 infection, ZT12 time point, collec… ×4 Lung, MHV1 infection, ZT6 time point, collect… ×4 Lung, MHV1 infection, ZT6 time point, collect… ×4 +16 more

Supports a between-group comparison across 91 samples.

How we read this: 24 replicated groups read from 91 sample titles; they account for 91 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

+ 51 more — browse all 91 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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