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CD49a expression and induction of cytotoxicity on human tissue-resident CD8+ T cells is controlled by RUNX2 and RUNX3 transcription factor activity [ATAC-seq]

GSE232238 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 16 samples Submitted 2024/04/30 Platform GPL11154
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 16 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Homo sapiens (human)
Samples
16 samples: 3 × Dermis CD103-, donor 2018#C vs 3 × Dermis CD103+, donor 2018#C vs 3 × Epidermis CD103+, donor 2018#C vs 3 × Epidermis CD49a+, donor 2018#CGroups 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)
CD49a marks highly cytotoxic epidermal tissue-resident memory (TRM)-cells, but their molecular circuitry and relationships to circulating populations are poorly defined. We demonstrate enrichment of RUNX family transcription factor binding motifs in human epidermal CD8+CD103+CD49a+ TRM-cells, paralleled by high RUNX2 and RUNX3 protein expression.
Read the full summary ↓
Clonal overlap between epidermal CD8+CD103+CD49a+ TRM-cells and circulating memory CD8+CD45RA–CD62L+ T-cells identified a reservoir of circulating cells with potential to seed cytotoxic TRM-cells in new sites. Upon IL-15 and TGF-β stimulation, subsets of circulating CD8+CD45RA–CD62L+ T-cells acquired CD49a expression and cytotoxic transcriptional profiles in a RUNX2 and RUNX3 dependent manner. In contrast, knock-out of RUNX3, but not RUNX2, prevented CD103 expression. In melanoma, high RUNX2, but not RUNX3, transcription correlated with a cytotoxic CD8+CD103+CD49a+ TRM cell signature and overall patient survival. Together, our results indicate that combined RUNX2 and RUNX3 activity promotes the differentiation of cytotoxic CD8+CD103+CD49a+ TRM-cells, providing immunosurveillance of infected and malignant cells.
This dataset
Open GSE232238 in finder → Find more human ChIP / ATAC / CUT&Tag 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 GSE232238_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA971337. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × Dermis CD103-, donor 2018#C vs 3 × Dermis CD103+, donor 2018#C vs 3 × Epidermis CD103+, donor 2018#C vs 3 × Epidermis CD49a+, donor 2018#C

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 16 sample titles; they account for 12 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
Datasets on a similar topic

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