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Distinct maternofetal immune signatures delineate preterm birth onset following urinary tract infection

GSE280297 Mus musculus (mouse) RNA-seq (gene expression) 60 samples Submitted 2025/10/23 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 60 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
60 samples: 28 × P vs 18 × B vs 14 × UGroups 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)
Preterm birth is the leading cause of infant mortality resulting in over one million neonatal deaths annually. Maternal urinary tract infection (UTI) during pregnancy increases risk for preterm birth; however, biological processes mediating UTI-associated preterm birth are not well-described. We established a murine maternal UTI model in which challenge with uropathogenic E.
Read the full summary ↓
coli resulted in preterm birth in about half of dams. Dams experiencing preterm birth displayed excessive bladder inflammation and altered uteroplacental T cell polarization compared to non-laboring infected dams, with no differences in bacterial burdens. Additional factors associated with preterm birth included higher proportions of male fetuses and lower maternal serum IL-10. Furthermore, exogenous maternal IL-10 treatment absolved UTI-associated preterm birth but contributed to fetal growth restriction in this model.
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 GSE280297_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 PRJNA1177788 and SRA study SRP540816. Searching any of these in the dataset finder brings you back here.

Study design
28 × P vs 18 × B vs 14 × U

Supports a between-group comparison across 60 samples.

How we read this: 3 replicated groups read from 60 sample titles; they account for 60 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

+ 20 more — browse all 60 samples with per-sample file links →

Datasets on a similar topic

Search all mouse 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.