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Z-DNA underlies the target choice of Aire by facilitating promoter poising [scRNA-Seq]

GSE253215 Mus musculus (mouse) Single-cell RNA-seq 2 samples Submitted 2024/03/11 Platform GPL21273
At a glance

Single-cell RNA-seq · mouse · 2 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Samples
2 samples
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
AIRE relies on Z-DNA to flag gene targets for thymic T cell tolerizationNature · 2024
Summary (written by the submitters)
Aire is an unconventional transcription factor (TF) that enhances the expression of thousands of genes in medullary thymic epithelial cells (mTECs), which promotes clonal deletion or phenotypic diversion of self-reactive T cells. The biological logic of Aire’s target specificity remains largely unknown as, unlike many TFs, it does not bind to a particular DNA-sequence motif.
Read the full summary ↓
We implemented two orthogonal approaches to investigate Aire’s cis-regulatory mechanisms: construction of a convolutional neural network and leveraging of natural genetic variation via analysis of F1-hybrid mice. Both approaches nominated Z-DNA and Nfe2•Maf as putative positive influences on Aire’s target choices. Genome-wide mapping studies revealed that Z-DNA-forming and Nfe2l2-binding motifs were positively associated with the inherent ability of a gene’s promoter to generate DNA double-strand breaks (DSBs), and promoters showing strong DSB generation were more likely to enter a poised state with accessible chromatin and already-assembled transcriptional machinery. Consequently, Aire preferentially targeted genes with poised promoters. We propose a model whereby Z-DNA anchors the Aire-mediated transcriptional program by enhancing DSB generation and promoter poising. Beyond resolving a long-standing mechanistic conundrum, these findings suggest previously unexplored routes of manipulating T-cell tolerance.
Published in
AIRE relies on Z-DNA to flag gene targets for thymic T cell tolerization
Fang Y, Bansal K, Mostafavi S et al. · Nature 2024 · PMID 38480882 · doi:10.1038/s41586-024-07169-7
This dataset
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.

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 GSE253215_RAW.tar (it can run to tens of gigabytes).

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.

What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1064577 and SRA study SRP483634. Searching any of these in the dataset finder brings you back here.

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