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Discovery of Tcf7 regulators with clonally-resolved CRISPR screens identifies Trim28 as a mediator of CD8 T cell differentiation in tumors [RNA-Seq]

GSE334845 Mus musculus (mouse) Single-cell RNA-seq 86 samples Submitted 2026/06/30 Platform GPL30172Platform GPL19057
At a glance

Single-cell RNA-seq · mouse · 86 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
86 samples: 16 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.
Summary (written by the submitters)
Stem-like TCF7+ CD8 T cells sustain anti-tumor responses and support immune checkpoint blockade. We systematically identified regulators of this cell state using genome-wide CRISPR screens in primary T cells in vitro. Using random barcodes to link clonal relationships with guide identity and transcriptional states in single cells, we inferred differentiation trajectories and differentiation rates of CD8 T cells in tumors, while mitigating confounding clonal bias.
Read the full summary ↓
We found that Trim28-deficient T cells in tumors were enriched in the TCF7+ cell state, depleted in cycling and terminal effector states, and uniquely generating a tissue resident memory (TRM)-like state with increased chromatin accessibility at known TRM loci as well as repeat elements. Despite the increase in TCF7+ CD8 T cells, loss of Trim28 did not improve tumor control, likely because of reduced effector differentiation, highlighting the need for tuning the balance and dynamics of stem-like versus effector states for effective tumor clearance.
This dataset
Open GSE334845 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 GSE334845_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 PRJNA1476603 and SRA study SRP708079. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
16 conditions, mostly in triplicate
LCMV D30 untransduced cotransfer control effe… ×10 LCMV D30 fresh control central memory ×10 LCMV D30 fresh control effector memory ×10 LCMV D30 untransduced cotransfer control cent… ×9 LCMV D30 post-transduction no stimulation cen… ×5 LCMV D30 post-transduction no stimulation eff… ×5 LCMV D30 post-transduction with stimulation c… ×5 LCMV D30 post-transduction with stimulation e… ×5 +9 more

Supports a between-group comparison across 85 samples.

How we read this: 16 replicated groups read from 86 sample titles; they account for 85 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

+ 46 more — browse all 86 samples with per-sample file links →

Datasets on a similar topic

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.