GEO series

Distinct activation programs in naïve and memory CD8 T cells govern progeny stemness and effector persistence (bulk experiment, NupHox mice, Lm-OVA infection)

GSE339513 Mus musculus (mouse) RNA-seq (gene expression) 15 samples Submitted 2026/07/22 Platform GPL19057

At a glance

RNA-seq (gene expression) · mouse · 15 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: 15 samples: 15 samples, each with a distinct title — no replicated groupsGroups 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 longitudinally profiled gene expression in naive and central and effector memory CD8+ T cells across multiple models of acute cognate infection to reveal subset-specific activation programs. However, how prior antigen experience alters T-cell activation programs remains poorly understood. We longitudinally profiled gene expression in naive, central memory, and effector memory CD8+ T cells in response to cognate antigen across multiple models of acute infection.

Read the full summary ↓

Naive T cells engaged TOX- and TCF7-centered programs and generated early stem-like central memory precursors. Their initially slow proliferation was followed by rapid expansion and the production of large numbers of effector cells. Central memory T cells rapidly triggered effector and proliferation programs while maintaining a smaller self-renewing population. Effector memory T cells expanded poorly and generated almost exclusively effector progeny. Effector progeny derived from both memory subsets survived contraction more efficiently than naive T-cell-derived progeny and established persistent effector memory populations. These data show that prior antigen experience does not simply accelerate CD8+ T-cell activation but redirects cell-intrinsic programs governing progeny fate and persistence. These distinct programs may reflect adaptation to different histories and anticipated patterns of antigen exposure.

This dataset

Open GSE339513 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 GSE339513_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 PRJNA1499113 and SRA study SRP720318. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

15 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 15 sample titles: 15 distinct titles with little repetition. 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

GSM9896953 Sample1_Naive_Clone2
GSM9896954 Sample2_AIMT_Clone2
GSM9896955 Sample3_Memory_Clone2
GSM9896956 Sample4_Naive_Clone2
GSM9896957 Sample5_AIMT_Clone2
GSM9896958 Sample6_Memory_Clone2
GSM9896959 Sample7_Naive_Clone12
GSM9896960 Sample8_AIMT_Clone12
GSM9896961 Sample9_Memory_Clone12
GSM9896962 Sample10_Naive_Clone12
GSM9896963 Sample11_AIMT_Clone12
GSM9896964 Sample13_AIMT_Clone12
GSM9896965 Sample14_Naive_Clone2
GSM9896966 Sample15_AIMT_Clone2
GSM9896967 Sample16_Memory_Clone2

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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.