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Selective requirement of 3D genomic organization for the Mdm1-Il22-Ifng locus regulation in initial Th1 cell lineage specification and differentiation

GSE215177 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 69 samples Submitted 2024/05/01 Platform GPL21626
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 69 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
69 samples: 56 distinct titles, 13 of them repeatedGroups 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)
Eukaryotic DNA fibers are organized into structured subunits in the nucleus, but the extent to which these 3D chromatin architectures influence cytokine expression remains unclear. Here, we investigate the role of dynamic loop formation within the topologically associating domain (TAD) in regulating the expression of two critical cytokines, interferon-gamma (IFN-) and interleukin-22 (IL-22).
Read the full summary ↓
These cytokine loci are closely located in the genome and are associated with complex enhancer landscapes, which are selectively active in type 1 and type 3 lymphocytes. Using in situ Hi-C, we demonstrate inducible TADs that insulate Ifng and Il22 enhancers during Th1 differentiation. Deleting the boundary of these TADs resulted in imbalanced Th1- and Th17-associated immunity, both in vitro and in vivo. In contrast, this boundary element was dispensable for cytokine regulation in NK cells. Our finding suggest that precise cytokine regulation relies on lineage- and developmental stage-specific interactions of 3D chromatin architectures and enhancer landscapes.
This dataset
Open GSE215177 in finder → Find more mouse 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 GSE215177_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 PRJNA889041 and SRA study SRP401839. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
56 distinct titles, 13 of them repeated
Th1_D5_K27Ac_141007_0175_s ×2 Th2_D3_K27Ac_141007_0175_s ×2 Th2_D5_K27Ac_141007_0175_s ×2 ChIP_Th1_D3_H3K27ac_F_WT ×2 ChIP_Th1_D3_H3K27ac_F_KO ×2 ChIP_Th1_D3_H3K4me1_F_WT ×2 ChIP_Th1_D3_H3K4me1_F_KO ×2 ChIP_Th1_D3_H3K27me3_F_WT ×2 +5 more

How we read this: Read from 69 sample titles: 56 distinct titles with little repetition. 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

+ 29 more — browse all 69 samples with per-sample file links →

Datasets on a similar topic

Search all mouse ChIP / ATAC / CUT&Tag datasets in GEO →

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