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Effect of overexpression of aging-associated transcription factors on epithelial cells.

GSE296787 Homo sapiens (human) RNA-seq (gene expression) 64 samples Submitted 2025/08/07 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 64 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
Homo sapiens (human)
Samples
64 samples: 64 samples, each with a distinct title — no replicated groupsGroups 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
Active chromatin marks and up-regulation of FOXC1 in uterine epithelial cells demarcate the onset of reproductive decline in aging femalesNAR molecular medicine · 2025
Summary (written by the submitters)
RNA-seq profiling of whole, intact uteri at embryonic day 3.5 (E3.5) from young and aged virgin wild-type C57BL/6 mice—each mated with vasectomized wild-type males—identified the transcription factors Foxc1 and Six1 as aging-associated markers. Immunostaining of mouse uteri across an age range of 8 to 41 weeks revealed a progressive upregulation of FOXC1, initially localized to individual stromal cells in the endometrium, followed by prominent expression in both luminal and glandular epithelial cells.
Read the full summary ↓
To investigate the functional role of Foxc1 and Six1, their full-length open reading frames were cloned into a PiggyBac expression vector, sequence-verified, and overexpressed in Ishikawa cells. Phenotypic characterization and RNA-seq analysis of these cells provided a framework for understanding FOXC1-mediated aging-related effects.
Published in
Active chromatin marks and up-regulation of FOXC1 in uterine epithelial cells demarcate the onset of reproductive decline in aging females
Tsolova AO, Lea G, Jadli AS et al. · NAR molecular medicine 2025 · PMID 40922722 · doi:10.1093/narmme/ugaf031
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 GSE296787_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 PRJNA1261051 and SRA study SRP584230. Searching any of these in the dataset finder brings you back here.

Study design
64 samples, each with a distinct title — no replicated groups

Supports a case/control comparison: 24 samples read as cases, 8 as controls.

How we read this: Read from 64 sample titles: 64 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

+ 24 more — browse all 64 samples with per-sample file links →

Datasets on a similar topic

Search all human 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.