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Transcriptomics of SGLT2-positive early proximal tubule segments in mice: response to type 1 diabetes, SGLT1/2 inhibition or GLP1 receptor agonism

GSE279174 Mus musculus (mouse) RNA-seq (gene expression) 54 samples Submitted 2024/11/14 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 54 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
54 samples
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
Transcriptomics of SGLT2-positive early proximal tubule segments in mice: response to type 1 diabetes, SGLT1/2 inhibition, or GLP1 receptor agonismAmerican journal of physiology. Renal physiology · 2025
Summary (written by the submitters)
SGLT2 inhibitors (SGLT2i) and GLP1 receptor (GLP1R) agonists have kidney protective effects. To better understand their molecular effects, RNA sequencing was performed in SGLT2-positive proximal tubule segments isolated by immunostaining-guided laser capture microdissection. Male adult DBA wildtype (WT) and littermate diabetic Akita mice ± Sglt1 knockout (Sglt1-KO) were given vehicle or SGLT2i dapagliflozin (dapa; 10mg/kg diet) for 2 weeks, and other Akita mice received GLP1R agonist semaglutide (sema; 3nmol/[kg body weight*day], s.c.).
Read the full summary ↓
Dapa (254±11mg/dL) and Sglt1-KO (367±11mg/dL) but not sema (407±44mg/dL) significantly reduced hyperglycemia in Akita mice (480±33mg/dL). The 20,748 detected annotated protein-coding genes included robust enrichment of S1-segment marker genes. Akita showed 198 (~1%) differentially expressed genes vs. WT (DEGs; adjusted p<0.1) including downregulation of anionic transport, unsaturated fatty acid and carboxylic acid metabolism. Dapa changed only 2 genes in WT but restored 43% of DEGs in Akita, including upregulation of lipid metabolic pathway, carboxylic acid metabolism and organic anion transport. In Akita, sema restored ~10% of DEGs, and Sglt1-KO and dapa were synergistic (restored ~61%) possibly involving additive blood glucose effects (193±15mg/dl). Targeted analysis of transporters and channels (t-test p<0.05) revealed that ~10% of 526 detectable transporters and channels were downregulated by Akita, with ~60% restored by dapa. Dapa, dapa+Sglt1-KO and sema also altered Akita-insensitive genes. Among DEGs in Akita, ~30% were unresponsive to any treatment, indicating potential new targets. In conclusion, SGLT2i restored transcription for multiple metabolic pathways and transporters in SGLT2-positive proximal tubule segments in diabetic mice, with a smaller effect also observed for GLP1R agonism.
Published in
Transcriptomics of SGLT2-positive early proximal tubule segments in mice: response to type 1 diabetes, SGLT1/2 inhibition, or GLP1 receptor agonism
Kim YC, Das V, Kanoo S et al. · American journal of physiology. Renal physiology 2025 · PMID 39589189 · doi:10.1152/ajprenal.00231.2024
This dataset
Open GSE279174 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 GSE279174_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 PRJNA1171019 and SRA study SRP537635. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39589189) ↗
Study design
A cohort of 54 individual samples

The grouping that defines any comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Sample titles run LCM54 … LCM74 and carry no group information.

Samples in this study

+ 14 more — browse all 54 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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