GEO series

Evolutionary guided transcription factor design programs novel T cell states [RNAseq_Paired]

GSE335040 Homo sapiens (human) RNA-seq (gene expression) 33 samples Submitted 2026/06/17 Platform GPL34284

At a glance

RNA-seq (gene expression) · human · 33 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: Homo sapiens (human)
Samples: 33 samples: 33 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)

Human protein-coding genes evolved via modular rearrangement of domains from ancestral genes. Here, we develop a scalable, evolutionarily guided method to assemble novel protein-coding genes from constituent domains within a protein family, termed DESynR (Domain Engineered via Synthesis and Recombination) genes. Using primary human chimeric antigen receptor T cells as a model, we find that the expression of DESynR Activator Protein-1 (AP-1) transcription factors (TFs) significantly outperforms the overexpression of natural AP-1 TFs in multiple functional assays in vitro and in vivo.

Read the full summary ↓

Top DESynR AP-1 TFs exhibit non-intuitive domain architectures, including from TFs not canonically expressed in T cells. DESynR AP-1 TFs induce broad transcriptional and epigenetic reprogramming and establish non-natural T cell states that optimize features of exhaustion, effector and cytotoxic function, and persistence— in some cases co-opting gene expression modules from disparate cell types. We show that this reprogramming is primarily driven by differential regulation of established AP-1-bound regulatory elements, rather than unique binding. Finally, we extend the DESynR methodology to Erythroblast Transformation Specific (ETS) and Forkhead box (FOX) TFs to support the generalizability across protein families. Overall, we demonstrate that novel configurations of existing protein domains may uncover non-evolved genes that program cell states with therapeutic relevance.

This dataset

Open GSE335040 in finder → Find more human 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 GSE335040_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 PRJNA1477134 and SRA study SRP708557. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

33 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 33 sample titles: 33 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

GSM9804792 Healthy human donor (1), CAR T cells, JUN-FOS-BATF, RNA
GSM9804793 Healthy human donor (1), CAR T cells, JUN, RNA
GSM9804794 Healthy human donor (1), CAR T cells, FOS, RNA
GSM9804795 Healthy human donor (1), CAR T cells, BATF, RNA
GSM9804796 Healthy human donor (1), CAR T cells, GFP, RNA
GSM9804797 Healthy human donor (1), CAR T cells, FOSL1-BATF-MAFA, RNA
GSM9804798 Healthy human donor (1), CAR T cells, MAFF-ATF3-BATF2, RNA
GSM9804799 Healthy human donor (1), CAR T cells, FOSL1, RNA
GSM9804800 Healthy human donor (1), CAR T cells, MAFF, RNA
GSM9804801 Healthy human donor (1), CAR T cells, ATF3, RNA
GSM9804802 Healthy human donor (1), CAR T cells, BATF2, RNA
GSM9804803 Healthy human donor (2), CAR T cells, JUN-FOS-BATF, RNA
GSM9804804 Healthy human donor (2), CAR T cells, JUN, RNA
GSM9804805 Healthy human donor (2), CAR T cells, FOS, RNA
GSM9804806 Healthy human donor (2), CAR T cells, BATF, RNA
GSM9804807 Healthy human donor (2), CAR T cells, GFP, RNA
GSM9804808 Healthy human donor (2), CAR T cells, FOSL1-BATF-MAFA, RNA
GSM9804809 Healthy human donor (2), CAR T cells, MAFF-ATF3-BATF2, RNA
GSM9804810 Healthy human donor (2), CAR T cells, FOSL1, RNA
GSM9804811 Healthy human donor (2), CAR T cells, MAFF, RNA
GSM9804812 Healthy human donor (2), CAR T cells, ATF3, RNA
GSM9804813 Healthy human donor (2), CAR T cells, BATF2, RNA
GSM9804814 Healthy human donor (3), CAR T cells, JUN-FOS-BATF, RNA
GSM9804815 Healthy human donor (3), CAR T cells, JUN, RNA
GSM9804816 Healthy human donor (3), CAR T cells, FOS, RNA
GSM9804817 Healthy human donor (3), CAR T cells, BATF, RNA
GSM9804818 Healthy human donor (3), CAR T cells, GFP, RNA
GSM9804819 Healthy human donor (3), CAR T cells, FOSL1-BATF-MAFA, RNA
GSM9804820 Healthy human donor (3), CAR T cells, MAFF-ATF3-BATF2, RNA
GSM9804821 Healthy human donor (3), CAR T cells, FOSL1, RNA
GSM9804822 Healthy human donor (3), CAR T cells, MAFF, RNA
GSM9804823 Healthy human donor (3), CAR T cells, ATF3, RNA
GSM9804824 Healthy human donor (3), CAR T cells, BATF2, RNA

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GSE301298 Functional redundancy between UTY and UTX in regulating the localization of transcription factors involved in pluripotency 88 samples shares transcription, factor
GSE275721 Lineage master regulator and cancer-selective partner transcription factors rewire 3D genome topology for tumor-specific gene control 72 samples shares transcription, factor

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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.