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Prototype LNP-mRNA vaccine candidates [SC_RNAseq]

GSE207141 Mus musculus (mouse) Single-cell RNA-seq 14 samples Submitted 2025/07/30 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 14 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
14 samples: 4 × LNP-mRNA vaccine, panLow vs 4 × LNP-mRNA vaccine, panHigh vs 3 × LNP-mRNA vaccine, pbs vs 3 × LNP-mRNA vaccine, deltaGroups 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)
We developed prototype LNP-mRNA vaccine candidates against SARS-CoV-2 Delta, SARS-CoV and MERS-CoV, and test how multiplexing LNP-mRNAs can induce effective immune responses in animal models. Triplex and Duplex LNP-mRNA vaccination induced antigen-specific antibody responses against SARS-CoV-2, SARS-CoV and MERS-CoV. Single cell RNA-seq profiled the global systemic immune repertoires and respective transcriptome signatures of vaccinated animals, revealing systemic increase in activated B cells, and differential gene expression across major adaptive immune cells.
Read the full summary ↓
Sequential vaccination showed potent antibody responses against all three species, significantly stronger than simultaneous vaccination in mixture. These data demonstrated feasibility, antibody responses and single cell immune profiles of multi-species coronavirus vaccination. The direct comparison between simultaneous and sequential vaccination offers insights on optimization of vaccination schedules to provide broad and potent antibody immunity against three major pathogenic coronavirus species.
This dataset
Open GSE207141 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 GSE207141_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 PRJNA853803 and SRA study SRP384059. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
4 × LNP-mRNA vaccine, panLow vs 4 × LNP-mRNA vaccine, panHigh vs 3 × LNP-mRNA vaccine, pbs vs 3 × LNP-mRNA vaccine, delta

Supports a between-group comparison across 14 samples.

How we read this: 4 replicated groups read from 14 sample titles; they account for 14 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.