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Spatial targeting of the prostaglandin receptor EP2 is essential in driving a sustained PGE2-mediated cAMP signaling in the human endometrium

GSE246497 Homo sapiens (human) RNA-seq (gene expression) 21 samples Submitted 2024/10/27 Platform GPL20301
At a glance

RNA-seq (gene expression) · human · 21 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
21 samples: 7 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.
Summary (written by the submitters)
In a process known as decidualization, progesterone signaling in the human endometrium converges with local cAMP production to drive morphometric and transcriptomic changes that prepare the endometrium for pregnancy. The source of cAMP has been contentious but the prostaglandin PGE2 signaling through EP2, its G-protein coupled receptor, remains a strong candidate.
Read the full summary ↓
Cells often employ additional receptor regulation to diversify and prolong the cAMP signal and its down-steam effects, most notably through internalization and trafficking of receptors through endosomes. Here, we decidualized cultured endometrial stromal cells for 4-days with PGE2 and MPA (a progestin) and compared transcriptomic profiles with those depleted of either GIPC or APPL1, adaptor proteins involved in trafficking and recycling of EP2 respectively.
This dataset
Open GSE246497 in finder → Find more human 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 GSE246497_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 PRJNA1033343 and SRA study SRP469002. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
7 conditions, mostly in triplicate
NT siRNA Untreated ×3 APPL1 siRNA Untreated ×3 GIPC siRNA Untreated ×3 NT siRNA PGE2+MPA treated ×3 APPL1 siRNA PGE2+MPA treated ×3 GIPC siRNA PGE2+MPA treated ×3 NT siRNA 8-bromo-cAMP + MPA treated ×3

Supports a between-group comparison across 21 samples.

How we read this: 7 replicated groups read from 21 sample titles; they account for 21 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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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.