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Gfi1 controls the formation of effector CD8+ T cells during chronic infection and cancer [RNA]

GSE261249 Mus musculus (mouse) RNA-seq (gene expression) 31 samples Submitted 2025/04/10 Platform GPL21103
At a glance

RNA-seq (gene expression) · mouse · 31 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
Mus musculus (mouse)
Samples
31 samples: 8 conditions, mostly with about 4 replicates eachGroups 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
Gfi1 controls the formation of effector-like CD8(+) T cells during chronic infection and cancerNature communications · 2025
Summary (written by the submitters)
During chronic infection and tumor progression, CD8+ T cells gradually lose their cytotoxic effector function and become “exhausted”. These “exhausted” CD8+ T cells are highly heterogenous and comprised of various subsets, including a self-renewing progenitor subset that gives rise to Ly108-CX3CR1+ effector cells with some cytotoxic capabilities.
Read the full summary ↓
Generation of these effectors is essential for the control (although limited) of chronic infection and tumor. However, the precise cues and mechanisms directing their formation and maintenance remains incompletely understood. In this study, using genetic mouse models challenged with the LCMV clone 13 infection and syngeneic MB49 urothelial adenocarcinoma, we show that the expression of a transcriptional repressor, growth factor independent 1 (Gfi1) is dynamically regulated in “exhausted” CD8+ T cells. By controlling chromatin accessibility and transcriptomic programs, Gfi1 governs the generation of the effector cells. Deletion of Gfi1 in T cells arrests the progenies from progenitors in a Ly108+CX3CR1+ Transitional state, without further differentiation into effector cells. Given the programmable chromatin profile of these transitional cells, we reason that they are a better target than the highly irreprogrammable terminally differentiated cells for therapeutic interventions to combat chronic infection and cancer. Our results show that Gfi1 is a novel epigenetic and transcriptional regulator of CD8+ T cell exhaustion.
Published in
Gfi1 controls the formation of effector-like CD8(+) T cells during chronic infection and cancer
Ojo OA, Shen H, Ingram JT et al. · Nature communications 2025 · PMID 40374625 · doi:10.1038/s41467-025-59784-1
This dataset
Open GSE261249 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 GSE261249_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 PRJNA1086161 and SRA study SRP494350. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40374625) ↗
Study design
8 conditions, mostly with about 4 replicates each
Progenitor_wildtype_RNA_day30_biol ×4 Transitional_wildtype_RNA_day30_biol ×4 Terminally_exhausted_wildtype_RNA_day30_biol ×4 Naïve_wildtype_RNA_day30_biol ×4 Progenitor_gfi1cko_RNA_day30_biol ×4 Transitional_gfi1cko_RNA_day30_biol ×4 Naïve_gfi1cko_RNA_day30_biol ×4 Effector_wildtype_RNA_day30_biol ×3

Supports a between-group comparison across 31 samples.

How we read this: 8 replicated groups read from 31 sample titles; they account for 31 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
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