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DEVELOPMENTAL LANDMARKS AND CELLULAR TRANSITIONS DURING EXTRAVILLOUS TROPHOBLAST CELL DIFFERENTIATION [bulk_rna_seq_kds]

GSE307761 Homo sapiens (human) Single-cell RNA-seq 18 samples Submitted 2026/04/22 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 18 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
18 samples: 9 × Human TS cells (CT27), control shRNA treated, vs 3 × Human TS cells (CT27), CEBPB shRNA treated, vs 3 × Human TS cells (CT27), ADAMTS20 shRNA treated, vs 3 × Human TS cells (CT27), CCNB1 shRNA treated,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.
Paper
Developmental landmarks and cellular transitions during extravillous trophoblast cell differentiationProceedings of the National Academy of Sciences of the United States of America · 2026
Summary (written by the submitters)
Human trophoblast stem (TS) can be captured, maintained in vitro under specific conditions, and differentiated into extravillous trophoblast (EVT) cells. The regulatory mechanisms that govern the self-renewal and differentiation of human TS cells into EVT cells are largely unknown. In this study, bulk RNA-sequencing (RNA-seq) and single cell RNA-seq (scRNA-seq) were performed on human TS cells maintained in the stem state and on cells progressing from the stem state into EVT cells (differentiation days 3, 6, and 8).
Read the full summary ↓
Distinct bulk and single cell transcript profiles were identified for each day of analysis. Day 3 of EVT cell differentiation represented a striking transition point and was readily distinguished from stem state and days 6 and 8 of EVT cell differentiation. Analysis of scRNA-seq led to the identification of several unique cell populations. Trophoblast cell developmental state-specific regulons and trajectories. We elucidated functional roles of key regulators of EVT cell development: cyclin B1, CCAAT/enhancer-binding protein beta, and ADAM metallopeptidase with thrombospondin type 1 motif 20. Collectively, we have defined developmental landmarks and transitional cell populations during EVT cell differentiation. These findings provide a valuable resource and foundation for future investigations into regulatory mechanisms controlling TS cell differentiation into the EVT cell lineage
Published in
Developmental landmarks and cellular transitions during extravillous trophoblast cell differentiation
Moreno-Irusta A, Basu MK, Dominguez EM et al. · Proceedings of the National Academy of Sciences of the United States of America 2026 · PMID 42090250 · doi:10.1073/pnas.2529836123
This dataset
Open GSE307761 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 GSE307761_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1327280 and SRA study SRP619120. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42090250) ↗
Study design
9 × Human TS cells (CT27), control shRNA treated, vs 3 × Human TS cells (CT27), CEBPB shRNA treated, vs 3 × Human TS cells (CT27), ADAMTS20 shRNA treated, vs 3 × Human TS cells (CT27), CCNB1 shRNA treated,

Supports a between-group comparison across 18 samples.

How we read this: 4 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
Datasets on a similar topic

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