Mitochondrial respiration is necessary for CD8 T cell proliferation and cell fate
RNA-seq (gene expression) · mouse · 99 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
- 99 samples: 22 conditions, mostly with about 5 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
- Mitochondrial respiration is necessary for CD8(+) T cell proliferation and cell fateNature immunology · 2025
Read the full summary ↓
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE296763_RAW.tar (it can run to tens of gigabytes).
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: 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 PRJNA1261015 and SRA study SRP584302. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 99 samples.
How we read this: 22 replicated groups read from 99 sample titles; they account for 99 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.
- GSM8976031 Direct_Infection_WT_Activated_1 Direct_Infection_WT_Act…
- GSM8976032 Direct_Infection_WT_Activated_2 Direct_Infection_WT_Act…
- GSM8976033 Direct_Infection_WT_Activated_3 Direct_Infection_WT_Act…
- GSM8976034 Direct_Infection_WT_Activated_4 Direct_Infection_WT_Act…
- GSM8976035 Direct_Infection_WT_Activated_5 Direct_Infection_WT_Act…
- GSM8976036 Direct_Infection_WT_Naïve_1 Direct_Infection_WT_Naï…
- GSM8976037 Direct_Infection_WT_Naïve_2 Direct_Infection_WT_Naï…
- GSM8976038 Direct_Infection_WT_Naïve_3 Direct_Infection_WT_Naï…
- GSM8976039 Direct_Infection_WT_Naïve_4 Direct_Infection_WT_Naï…
- GSM8976040 Direct_Infection_WT_Naïve_5 Direct_Infection_WT_Naï…
- GSM8976041 Direct_Infection_KO+AOX_Activated_1 Direct_Infection_KO+AOX…
- GSM8976042 Direct_Infection_KO+AOX_Activated_3 Direct_Infection_KO+AOX…
- GSM8976043 Direct_Infection_KO+AOX_Activated_4 Direct_Infection_KO+AOX…
- GSM8976044 Direct_Infection_KO+AOX_Naïve_1 Direct_Infection_KO+AOX…
- GSM8976045 Direct_Infection_KO+AOX_Naïve_3 Direct_Infection_KO+AOX…
- GSM8976046 Direct_Infection_KO+AOX_Naïve_4 Direct_Infection_KO+AOX…
- GSM8976047 Direct_Infection_KO_Activated_1 Direct_Infection_KO_Act…
- GSM8976048 Direct_Infection_KO_Activated_2 Direct_Infection_KO_Act…
- GSM8976049 Direct_Infection_KO_Activated_3 Direct_Infection_KO_Act…
- GSM8976050 Direct_Infection_KO_Activated_4 Direct_Infection_KO_Act…
- GSM8976051 Direct_Infection_KO_Activated_5 Direct_Infection_KO_Act…
- GSM8976052 Direct_Infection_KO_Naïve_1 Direct_Infection_KO_Naï…
- GSM8976053 Direct_Infection_KO_Naïve_2 Direct_Infection_KO_Naï…
- GSM8976054 Direct_Infection_KO_Naïve_3 Direct_Infection_KO_Naï…
- GSM8976055 Direct_Infection_KO_Naïve_4 Direct_Infection_KO_Naï…
- GSM8976056 Direct_Infection_KO_Naïve_5 Direct_Infection_KO_Naï…
- GSM8976057 Adoptive_Transfer_WT_Activated_1 Adoptive_Transfer_WT_Ac…
- GSM8976058 Adoptive_Transfer_WT_Activated_2 Adoptive_Transfer_WT_Ac…
- GSM8976059 Adoptive_Transfer_KO_Activated_1 Adoptive_Transfer_KO_Ac…
- GSM8976060 Adoptive_Transfer_KO_Activated_2 Adoptive_Transfer_KO_Ac…
- GSM8976061 Adoptive_Transfer_KO+AOX_Activated_1 Adoptive_Transfer_KO+AO…
- GSM8976062 Adoptive_Transfer_KO+AOX_Activated_2 Adoptive_Transfer_KO+AO…
- GSM8976063 Adoptive_Transfer_WT+AOX_Activated_1 Adoptive_Transfer_WT+AO…
- GSM8976064 Adoptive_Transfer_WT+AOX_Activated_2 Adoptive_Transfer_WT+AO…
- GSM8976065 Adoptive_Transfer_WT_Naïve_1 Adoptive_Transfer_WT_Na…
- GSM8976066 Adoptive_Transfer_WT_Naïve_2 Adoptive_Transfer_WT_Na…
- GSM8976067 Adoptive_Transfer_KO_Naïve_1 Adoptive_Transfer_KO_Na…
- GSM8976068 Adoptive_Transfer_KO_Naïve_2 Adoptive_Transfer_KO_Na…
- GSM8976069 Adoptive_Transfer_KO_Naïve_3 Adoptive_Transfer_KO_Na…
- GSM8976070 Adoptive_Transfer_KO+AOX_Naïve_1 Adoptive_Transfer_KO+AO…
+ 59 more — browse all 99 samples with per-sample file links →
- GSE306744 Pre-division TCF1 downregulation determines long-term effector and memory CD8 T cell fates [RNA-Seq] 31 samples shares cd8, fate
- GSE235005 Nutrient-driven histone code determines exhausted CD8+ T cell fates [ChIP-seq] 50 samples shares cd8, fate
- GSE286266 Age influences CMV-specific NK and CD8 T cell memory fates (NK cells) 12 samples shares cd8, fate
- GSE243640 GLUD1 determines murine muscle stem cell fate by controlling mitochondrial glutamate levels 19 samples shares mitochondrial, fate
- GSE302682 Sleeping Beauty mutagenesis identifies BACH2 and other regulators promoting CD8+ T cell persistence and effector function under tumor-associated chronic antigen stimulation - RNAseq 66 samples shares cd8
- GSE338265 Smad4 and Eomes converge on a shared transcriptional program associated with inflammatory CD8 T-cell differentiation 31 samples shares cd8
- GSE316541 α2,6-Sialoglycan-regulated anti-tumor immunity of tumor-infiltrating CD8+ T cells in the tumor microenvironment [CD8+T] 27 samples shares cd8
- GSE234974 Pan-cancer mapping of single CD8+ T cell profiles reveals a TCF1:CXCR6 axis regulating CD28 co-stimulation and anti-tumor immunity I 24 samples shares cd8
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.