GEO series

RAG recombinase expression discriminates the development of natural killer cells

GSE283274 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2025/07/25 Platform GPL24676

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: RAG recombinase expression discriminates the development of natural killer cellsFrontiers in immunology · 2025

Summary (written by the submitters)

V(D)J recombination initiated by recombination-activating gene (RAG) endonucleases is a crucial process for the generation of diversified antigen receptors of T and B lymphocytes but regarded dispensable for the generation of innate natural killer (NK) lymphocytes that lack clonotypic receptors. However, a fraction of human and murine NK cells derives from RAG-expressing progenitors, which have non-productive rearrangements within their Ig and TCR loci.

Read the full summary ↓

An impact of V(D)J rearrangements on maturation and function of NK cells has been suggested by mouse and human models. We studied the impact of RAG expression ontogeny on NK cell maturation and function by using RAG-fate mapping reporter permanently labeling NK progenitors and mature NK cells.

Published in

RAG recombinase expression discriminates the development of natural killer cells

Sprissler J, Pannicke U, Rump EM et al. · Frontiers in immunology 2025 · PMID 40787451 · doi:10.3389/fimmu.2025.1607664

This dataset

Open GSE283274 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 GSE283274_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 PRJNA1193006 and SRA study SRP548657. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40787451) ↗

Study design

6 conditions, mostly in triplicate

NK cells, GFP-, week 1, ×3 NK cells, GFP+, week 1, ×3 NK cells, GFP-, week 2, ×3 NK cells, GFP+, week 2, ×3 NK cells, GFP-, week 3, ×3 NK cells, GFP+, week 3, ×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

GSM8659006 NK cells, GFP-, week 1, replicate 1 NK cells, GFP-, week 1,
GSM8659009 NK cells, GFP-, week 1, replicate 2 NK cells, GFP-, week 1,
GSM8659011 NK cells, GFP-, week 1, replicate 3 NK cells, GFP-, week 1,
GSM8659013 NK cells, GFP+, week 1, replicate 1 NK cells, GFP+, week 1,
GSM8659015 NK cells, GFP+, week 1, replicate 2 NK cells, GFP+, week 1,
GSM8659017 NK cells, GFP+, week 1, replicate 3 NK cells, GFP+, week 1,
GSM8659019 NK cells, GFP-, week 2, replicate 1 NK cells, GFP-, week 2,
GSM8659021 NK cells, GFP-, week 2, replicate 2 NK cells, GFP-, week 2,
GSM8659023 NK cells, GFP-, week 2, replicate 3 NK cells, GFP-, week 2,
GSM8659024 NK cells, GFP+, week 2, replicate 1 NK cells, GFP+, week 2,
GSM8659025 NK cells, GFP+, week 2, replicate 2 NK cells, GFP+, week 2,
GSM8659026 NK cells, GFP+, week 2, replicate 3 NK cells, GFP+, week 2,
GSM8659027 NK cells, GFP-, week 3, replicate 1 NK cells, GFP-, week 3,
GSM8659028 NK cells, GFP-, week 3, replicate 2 NK cells, GFP-, week 3,
GSM8659029 NK cells, GFP-, week 3, replicate 3 NK cells, GFP-, week 3,
GSM8659030 NK cells, GFP+, week 3, replicate 1 NK cells, GFP+, week 3,
GSM8659031 NK cells, GFP+, week 3, replicate 2 NK cells, GFP+, week 3,
GSM8659032 NK cells, GFP+, week 3, replicate 3 NK cells, GFP+, week 3,

Datasets on a similar topic

GSE269629 Metabolic programs drive function of therapeutic natural killer (NK) cells in low oxygen tumor microenvironments 63 samples shares natural, killer
GSE287754 Defining the Effects of PKC Modulator HIV Latency-Reversing Agents on Natural Killer Cells 39 samples shares natural, killer
GSE309453 EBV infection in epithelial malignancies induces resistance to the anti-tumor function of natural killer cells via CD73-mediated metabolism of AMP [NK cells] 18 samples shares natural, killer
GSE309452 EBV infection in epithelial malignancies induces resistance to the anti-tumor function of natural killer cells via CD73-mediated metabolism of AMP [cell line] 12 samples shares natural, killer
GSE254188 Tim-3 on natural killer cells regulates immune response via antibody dependent cellular cytotoxicity in HER2-positive gastric cancer 11 samples shares natural, killer
GSE309020 Stem Cell Engineering for the Generation of Allogeneic CAR-Directed Natural Killer T Cells Targeting Endometrial Carcinoma 7 samples shares natural, killer
GSE261930 CRISPR/Cas9 mutagenesis screening identifies PRDM1 as a key regulator of the natural killer T cell central memory program and effector function 51 samples shares natural, killer
GSE264122 Characterization and comparative analysis of multifunctional natural killer cell engagers (NKCEs) during antitumor responses 45 samples shares natural, killer

Search all human RNA-seq datasets in GEO →

Share this dataset

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.