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

GSE224554 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 10 samples Submitted 2024/03/11 Platform GPL19057
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 10 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
Mus musculus (mouse)
Samples
10 samples: 2 × WT_NELF_Chipmentation vs 2 × Aire_KO_NELF_Chipmentation vs 2 × WT_DMSO_Aire_Chipmentation vs 2 × WT_Topotecan_Aire_ChipmentationGroups 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
AIRE relies on Z-DNA to flag gene targets for thymic T cell tolerizationNature · 2024
Summary (written by the submitters)
We profiled NELF and Aire binding in medullary thymic epithelial cells using ChIPmentation to investigate the logic of Aire's target choices
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 GSE224554_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA934447 and SRA study SRP424169. Searching any of these in the dataset finder brings you back here.

Study design
2 × WT_NELF_Chipmentation vs 2 × Aire_KO_NELF_Chipmentation vs 2 × WT_DMSO_Aire_Chipmentation vs 2 × WT_Topotecan_Aire_Chipmentation

Supports a between-group comparison across 8 samples.

How we read this: 4 replicated groups read from 10 sample titles; they account for 8 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
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