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Phenotypically similar but functionally distinct NK cell populations within the human maternal-fetal interface [scRNA-seq]

GSE319493 Homo sapiens (human) Single-cell RNA-seq 15 samples Submitted 2026/03/18 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 15 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Samples
15 samples: 15 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
Phenotypically similar but functionally distinct NK cell populations within the human maternal-fetal interfaceImmunoHorizons · 2026
Summary (written by the submitters)
Natural Killer cell function within tissues extends beyond exerting cytotoxicity, encompassing a range of functions that are just starting to become fully elucidated. In the context of human placentation, NK cells play a key role in enabling initial placentation, which is associated with the acquisition of tolerance-like properties. If and to which extent NK cells maintain these tolerance-like properties over the course of human pregnancy is still poorly understood.
Read the full summary ↓
We have employed a single-cell sequencing approach using the BD RhapsodyTM system to study the transcriptomic profile of Natural Killer (NK) cells in the decidual-placental interface (DPI) and the decidua (in comparison to NK cells from the maternal circulating blood and the cord blood). We found that NK cells from both location had similar transcriptional profile with the presence of resident NK cells. Yet, when stimulated in vitro, CD103+CD69+ tissue-resident NK cells exhibited distinct effector function from one another. Together, our findings reveal the presence of distinct functional resident NK cell populations in two anatomically adjacent tissues at healthy full-term pregnancies.
Published in
Phenotypically similar but functionally distinct NK cell populations within the human maternal-fetal interface
Frutoso M, DeJong CS, Shree R et al. · ImmunoHorizons 2026 · PMID 41808348 · doi:10.1093/immhor/vlag001
This dataset
Open GSE319493 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 GSE319493_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 PRJNA1423618 and SRA study SRP677066. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41808348) ↗
Study design
15 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 15 sample titles: 15 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
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.