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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

GSE215179 Mus musculus (mouse) RNA-seq (gene expression) 30 samples Submitted 2024/05/01 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 30 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Mus musculus (mouse)
Samples
30 samples: 6 conditions, mostly in triplicateGroups 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 GSE215179 in finder → Find more mouse RNA-seq 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 GSE215179_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA889044 and SRA study SRP401838. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly in triplicate
bulkRNA_Th1_D3_Ifng(70)CTCFdel_F_WT ×3 bulkRNA_Th1_D3_Ifng(70)CTCFdel_F_KO ×3 bulkRNA_Th1_D7_Ifng(70)CTCFdel_F_WT ×3 bulkRNA_Th1_D7_Ifng(70)CTCFdel_F_KO ×3 bulkRNA_Th1_D3_WT ×3 bulkRNA_Th1_D3_KO ×3 bulkRNA_Th1_D3_WT1_anti_gamma ×1 bulkRNA_Th1_D3_WT1_IFNg ×1 +10 more

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 30 sample titles; they account for 18 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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