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Single cell RNA sequencing of TCF-1+ P14 precursor cells sorted 3.25 days after infection with LCMV Armstrong [scRNA-Seq BD Rhapsody]

GSE278805 Mus musculus (mouse) Single-cell RNA-seq 1 samples Submitted 2025/02/21 Platform GPL34290
At a glance

Single-cell RNA-seq · mouse · 1 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Samples
1 samples
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
Precursors of exhausted T cells are pre-emptively formed in acute infectionNature · 2025
Summary (written by the submitters)
T-cell exhaustion limits effector T-cell function in chronic infection and tumors. The development of these hypofunctional T-cells and of their precursors was considered to require stimulatory conditions met only upon persisting exposure to antigen and inflammation. In sharp contrast, we found similar T-cell populations in the early phase of acute infections.
Read the full summary ↓
At that stage early developing TCF1+ precursor population shows an unexpected diversity, which includes precursors of normal memory T-cells but also cells with a phenotype, gene-expression, and epigenetic profile that resembles precursors of exhausted T-cells found in chronic infections. We demonstrate that high ligand affinity promotes, and PD-1 signaling restricts the development of these precursors. While these exhausted precursors are initially frequently found, they decline without being completely lost in infections the immune system resolves. We therefore concluded that precursor T-cells with at least two distinct phenotypes are preemptively generated irrespectively of the outcome of the infection. In this experiment, cells from day 3.25 pi were analyzed to determine if the different subsets could be detected.
Published in
Precursors of exhausted T cells are pre-emptively formed in acute infection
Chu T, Wu M, Hoellbacher B et al. · Nature 2025 · PMID 39778709 · doi:10.1038/s41586-024-08451-4
This dataset
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.

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 GSE278805_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1168959 and SRA study SRP536647. Searching any of these in the dataset finder brings you back here.

Samples in this study

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