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PGR Isoform Modulation via Enhancer Activation Regulates Progesterone Signaling in Human Endometrial Stromal Cells [RNA-Seq]

GSE296931 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2025/09/30 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 18 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
18 samples: 6 conditions, mostly in triplicateGroups 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
Progesterone receptor isoform modulation via enhancer activation regulates progesterone signaling in endometrial stromal cellsF&S science · 2025
Summary (written by the submitters)
Progesterone, acting through its isoform receptors PGR-A and PGR-B, is essential for regulating uterus function. The ratio between these isoforms is dynamic and context-dependent, driving distinct transcriptional programs. The upstream mechanisms controlling the PGR isoform balance and their functional impact in the uterus remain poorly understood.
Read the full summary ↓
In this study, we identified two distal PGR enhancers in endometrial stromal cells located 60 kb and 220 kb upstream of the PGR transcription start site. We found that in comparison to PGR promoter-targeting which favors a PGR-B dominant profile, activation of these enhancers shifts the isoform ratio by increasing PGR-A and decreasing PGR-B expression. Bulk RNA-sequencing revealed that the isoform balance alters the progesterone-regulated transcriptome. PGR-A/B-equivalent cells displayed pro-inflammatory gene signatures, whereas PGR-B-dominant cells exhibited suppression of inflammatory signaling and cell cycle activity. Cut&Run assays identified differential genomic binding patterns associated with each isoform profile, and integration with chromatin interaction maps suggest direct regulation of distinct gene subsets. Upstream, ESR1 indirectly activated the PGR-A isoform dominantly, potentially through cooperation with FOXO1 at the U2 enhancer. This study identifies a novel enhancer-driven mechanism regulating PGR isoform dynamics and sheds light on how their imbalance in the endometrial stroma may reshape progesterone signaling in health and disease.
Published in
Progesterone receptor isoform modulation via enhancer activation regulates progesterone signaling in endometrial stromal cells
Montague Redecke SG, Bell-Hensley A, Yi M et al. · F&S science 2025 · PMID 40848834 · doi:10.1016/j.xfss.2025.08.004
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 GSE296931_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 PRJNA1261952 and SRA study SRP584653. Searching any of these in the dataset finder brings you back here.

Study design
6 conditions, mostly in triplicate
NT gRNA Veh ×3 NT gRNA MPA ×3 U1U2 gRNAs Veh ×3 U1U2 gRNAs MPA ×3 Promoter gRNA Veh ×3 Promoter gRNA MPA ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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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