GEO series

Small non-coding RNAs encapsulating mammalian cells fuels innate immunity

GSE252429 Mus musculus (mouse) Single-cell RNA-seq 24 samples Submitted 2025/12/02 Platform GPL28330Platform GPL24247

At a glance

Single-cell RNA-seq · mouse · 24 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: Mus musculus (mouse)
Samples: 24 samples: 8 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: Deciphering the RNA landscapes on mammalian cell surfacesProtein & cell · 2026

Summary (written by the submitters)

Our study addresses the void in understanding surface RNAs, notably glycan-RNAs, abundant on the cell exterior yet lacking precise mapping, particularly in rare cell populations. We present AMOUR, a technique uniting RNA capture with T7-based linear amplification, facilitating accurate profiling of surface RNAs while maintaining plasma membrane integrity.

Read the full summary ↓

Validation via surface fluorescence in-situ hybridization and RNA aptamer imaging confirms their presence on the outer membrane, autonomously associating in vitro, independent of protein scaffolding. Our work reveals non-coding RNAs as integral components of diverse human and murine hematopoietic cell surface RNAs. Single-cell sequencing of human umbilical cord blood mononuclear cells identifies prevalent Y RNAs on monocyte surfaces. Notably, these Y RNAs interact with histones, critically regulating interleukin-6 (IL-6) gene expression and subsequent protein secretion upon histone stimulation. Highlighting the pivotal role of Y RNAs, our findings clarify their involvement in innate immune activation by capturing and presenting extracellular histones.

Published in

Deciphering the RNA landscapes on mammalian cell surfaces

Jiang X, Xu C, Yang E et al. · Protein & cell 2026 · PMID 40973153 · doi:10.1093/procel/pwaf079

This dataset

Open GSE252429 in finder → Find more mouse 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 GSE252429_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 PRJNA1060636 and SRA study SRP481079. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40973153) ↗

Study design

8 conditions, mostly in triplicate

mouse B cell ×3 mouse T cell ×3 mouse HSPC ×3 mouse NK ×3 mouse Monocyte ×3 ct ×3 WT ×3 Y ×3

Supports a between-group comparison across 24 samples.

How we read this: 8 replicated groups read from 24 sample titles; they account for 24 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

GSM8001264 mouse B cell rep1 mouse B cell
GSM8001265 mouse B cell rep2 mouse B cell
GSM8001266 mouse B cell rep3 mouse B cell
GSM8001267 mouse T cell rep1 mouse T cell
GSM8001268 mouse T cell rep2 mouse T cell
GSM8001269 mouse T cell rep3 mouse T cell
GSM8001270 mouse HSPC rep1 mouse HSPC
GSM8001271 mouse HSPC rep2 mouse HSPC
GSM8001272 mouse HSPC rep3 mouse HSPC
GSM8001273 mouse NK rep1 mouse NK
GSM8001274 mouse NK rep2 mouse NK
GSM8001275 mouse NK rep3 mouse NK
GSM8001276 mouse Monocyte rep1 mouse Monocyte
GSM8001277 mouse Monocyte rep2 mouse Monocyte
GSM8001278 mouse Monocyte rep3 mouse Monocyte
GSM9169194 ct1 ct
GSM9169195 ct2 ct
GSM9169196 ct3 ct
GSM9169197 WT1 WT
GSM9169198 WT2 WT
GSM9169199 WT3 WT
GSM9169200 Y1 Y
GSM9169201 Y2 Y
GSM9169202 Y3 Y

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Search all mouse RNA-seq datasets in GEO →

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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.