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High-resolution transcriptomic profiles of kidney distal convoluted tubules in male and female mice

GSE269410 Mus musculus (mouse) RNA-seq (gene expression) 13 samples Submitted 2026/06/30 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 13 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
13 samples: 7 × Male, DCT(early), vs 6 × Female, DCT(early),Groups 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)
Sexual dimorphic responses to physiological factors in the kidney have been emerging as important considerations for understanding kidney physiology and pathophysiology. Here, we report high-resolution transcriptome profiles of distal convoluted tubules isolated from the kidneys of male and female mice. Transcriptomic analysis based on RNA-Seq cooupled with tubule microdissection was carried out in male and female mice.
Read the full summary ↓
To accurately isolate the early DCT (DCT1) segments, microdissection was performed in a Pvalb-cre tdTomato transgenic mouse model. Transcript profiles in male and female DCT1 segments revealed comprehensive sex differences in the molecular features of the early DCT segments. Our data provide a high-resolution DCT1 (early DCT) transcriptome and serve as a reference resource for DCT research.
This dataset
Open GSE269410 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 GSE269410_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 PRJNA1121399 and SRA study SRP512512. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
7 × Male, DCT(early), vs 6 × Female, DCT(early),

Supports a between-group comparison across 13 samples.

How we read this: 2 replicated groups read from 13 sample titles; they account for 13 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
Datasets on a similar topic

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