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Y665F variant of mouse STAT5b protects against acute kidney injury through transcriptomic shifts in renal gene expression

GSE289432 Mus musculus (mouse) Single-nucleus RNA-seq 32 samples Submitted 2025/08/22 Platform GPL24247
At a glance

Single-nucleus RNA-seq · mouse · 32 samples

What it is
Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue). Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
32 samples: 8 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
Y665F variant of mouse Stat5b protects against acute kidney injury through transcriptomic shifts in renal gene expressionScientific reports · 2025
Summary (written by the submitters)
The impact of single nucleotide polymorphisms (SNP) on physiology is often underestimated. One amino acid change can result in a variety of phenotypes apparent only in response to disease or injury. Even known pathogenic SNPs have widespread effects that are currently unaccounted for. In this study, we investigated the impact of the known activating and pathogenic STAT5bY665F mutation in a renal injury context in mice carrying this variant.
Read the full summary ↓
Using ischemia-reperfusion model of acute kidney injury, immunohistochemistry, RNA-seq and ChIP-seq, we establish the protective role of STAT5b activation in renal epithelium and showcase the shifts in transcriptomic landscape in a tissue not associated with the usual human phenotype of the STAT5bY665F mutation. Our data indicate new links between the JAK/STAT pathway and known kidney injury markers, contribute to the understanding of the sexual dimorphism of renal disease, and provide new potential targets for JAK inhibitor- and amino acid transport modulation-based therapies.
Published in
Y665F variant of mouse Stat5b protects against acute kidney injury through transcriptomic shifts in renal gene expression
Jankowski J, Lee HK, Hennighausen L · Scientific reports 2025 · PMID 40841451 · doi:10.1038/s41598-025-15812-0
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 GSE289432_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1222896 and SRA study SRP563498. Searching any of these in the dataset finder brings you back here.

Study design
8 conditions, mostly with about 4 replicates each
Mouse, kidney, female, WT, ×4 Mouse, kidney, female, Y665F HET, ×4 Mouse, kidney, male, WT, ×4 Mouse, kidney, male, Y665F HET, ×4 Mouse, kidney, female, WT, IRI, ×4 Mouse, kidney, female, Y665F HET, IRI, ×4 Mouse, kidney, male, WT, IRI, ×4 Mouse, kidney, male, Y665F HET, IRI, ×4

Supports a between-group comparison across 32 samples.

How we read this: 8 replicated groups read from 32 sample titles; they account for 32 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
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