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Enhancer-instructed chromatin folding and compartmentalization dictate Vκ repertoire rearrangement to combat bacterial infection [ATAC-seq]

GSE193813 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 4 samples Submitted 2022/12/05 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 4 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
4 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.
Summary (written by the submitters)
Antigen receptor loci are organized into variable (V), diversity (D), and joining (J) elements that rearrange to generate diverse antigen receptor repertoires. Here, we identified an enhancer (E34) in the immunoglobulin kappa locus (Igκ) that instructed rearrangement of Vκ genes located in a sub-topologically associating domain (subTAD), including a Vκ gene encoding for antibodies targeting bacterial phosphorylcholine.
Read the full summary ↓
E34 promoted the deposition of active histone marks across the E34 subTAD to instruct its nuclear repositioning from a V(D)J recombination-repressive compartment to a permissive one. E34-induced nuclear repositioning of the E34 subTAD promoted Vκ-Jκ interactions assisted by enhancer-associated epigenetic marks and de novo CTCF binding. Finally, we found that E34-instructed Vκ-Jκ rearrangement was essential to combat Streptococcus pneumoniae but not methicillin-resistant Staphylococcus aureus or influenza infections. These data show how enhancer-instructed chromatin topology mechanically pulls specific Vκ and Jκ genes into close physical proximity to generate distinct antibody repertoires to combat bacterial infection.
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 GSE193813_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 PRJNA798026 and SRA study SRP355441. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 4 more — browse all 4 samples with per-sample file links →

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