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Diabetes induces exacerbated SARS-CoV-2 replication partly associated with ineffective pulmonary interferon responses, delayed cell-mediated immunity, and disruption of leptin receptor signaling

GSE270802 Mus musculus (mouse) RNA-seq (gene expression) 24 samples Submitted 2025/02/19 Platform GPL30172
At a glance

RNA-seq (gene expression) · mouse · 24 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
24 samples: 21 distinct titles, 3 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
Diabetes exacerbates SARS-CoV-2 replication through ineffective pulmonary interferon responses, delayed cell-mediated immunity, and disruption of leptin signalingFrontiers in cellular and infection microbiology · 2025
Summary (written by the submitters)
We evaluated the susceptibility and lung responses of type 2 diabetic and lean mice following intranasal SARS-CoV-2 infection using the mouse-adapted MA10 strain
Published in
Diabetes exacerbates SARS-CoV-2 replication through ineffective pulmonary interferon responses, delayed cell-mediated immunity, and disruption of leptin signaling
Thieulent CJ, Balasuriya UBR, Tseng A et al. · Frontiers in cellular and infection microbiology 2025 · PMID 40125513 · doi:10.3389/fcimb.2025.1513687
This dataset
Open GSE270802 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 GSE270802_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 PRJNA1128525 and SRA study SRP516198. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40125513) ↗
Study design
21 distinct titles, 3 of them repeated
HET_M_01_OD ×2 HET_M_03_OD ×2 HET_M_04_OD ×2

How we read this: Read from 24 sample titles: 21 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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