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Integrated epigenetic and genetic programming of primary human T cells [RNA-seq]

GSE306915 Homo sapiens (human) RNA-seq (gene expression) 77 samples Submitted 2025/09/08 Platform GPL20301Platform GPL30173
At a glance

RNA-seq (gene expression) · human · 77 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
77 samples: 21 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.
Summary (written by the submitters)
Targeted epigenetic engineering of gene expression in cell therapies would allow programming of desirable phenotypes without many of the challenges and safety risks associated with double strand break-based genetic editing approaches. Here, we develop an all-RNA platform for efficient, durable, and multiplexed epigenetic programming in primary human T cells, stably turning endogenous genes off or on using CRISPRoff and CRISPRon epigenetic editors.
Read the full summary ↓
We achieve epigenetic programming of diverse targeted genomic elements without the need for sustained expression of CRISPR systems. CRISPRoff-mediated gene silencing is maintained through numerous cell divisions, T cell stimulations, and in vivo adoptive transfer, avoiding cytotoxicity or chromosomal abnormalities inherent to multiplexed Cas9-mediated genome editing. Finally, we successfully combined genetic and epigenetic-engineering using orthogonal CRISPR Cas12a/dCas9 systems for targeted CAR knockin and CRISPRoff silencing of therapeutically relevant genes to improve preclinical CAR T cell-mediated in vivo tumor control and survival.
This dataset
Open GSE306915 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 GSE306915_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 PRJNA1313922 and SRA study SRP616572. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
21 conditions, mostly with about 4 replicates each
CRISPRoff_FAS_Guide1_Day7_Dono ×4 CRISPRoff_PTPN2_Guide6_Day7_Dono ×4 CRISPRoff_RC3H1_Guide2_Day7_Dono ×4 CRISPRoff_SUV39H1_Guide2_Day7_Dono ×4 CRISPRoff_RASA2_pool_Day7_Dono ×4 CRISPRoff_MED12_pool_Day7_Dono ×4 CRISPRoff_AAVS1_Guide1_Day7_Dono ×4 CRISPRoff_AAVS1_Guide2_Day7_Dono ×4 +13 more

Supports a between-group comparison across 77 samples.

How we read this: 21 replicated groups read from 77 sample titles; they account for 77 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

+ 37 more — browse all 77 samples with per-sample file links →

Datasets on a similar topic

Search all human 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.