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Interferon subverts an AHR-JUN axis to promote CXCL13+ T cells in lupus

GSE233050 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 76 samples Submitted 2024/07/08 Platform GPL16791
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 76 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
Homo sapiens (human)
Samples
76 samples: 16 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.
Paper
Interferon subverts an AHR-JUN axis to promote CXCL13(+) T cells in lupusNature · 2024
Summary (written by the submitters)
SLE is prototypical autoimmune disease driven by pathologic T cell-B cell interactions. Expansion of B cell-helper T cells including T follicular helper (Tfh) and T peripheral helper (Tph) cells is a prominent feature of systemic lupus erythematosus (SLE). Human Tfh and Tph cells characteristically produce high levels of the B cell chemoattractant CXCL13, yet regulation of T cell CXCL13 production and the relationship between CXCL13+ T cells and other T cell states remains unclear.
Read the full summary ↓
Here, we identify an imbalance in CD4 T cell phenotypes in SLE patients, with expansion of PD-1+/ICOS+ CXCL13+ T cells and reduction of CD96hi IL-22+ T cells. Using CRISPR screens, we identify the aryl hydrocarbon receptor (AHR) as a potent negative regulator of CXCL13 production by human CD4 T cells. Transcriptomic, epigenetic, and functional studies demonstrate that AHR coordinates with AP-1 family member JUN to prevent CXCL13+ Tph/Tfh cell differentiation and promote an IL-22+ phenotype. Type I interferon (IFN), a pathogenic driver of SLE, opposes AHR and JUN to promote T cell production of CXCL13. These results place CXCL13+ Tph/Tfh cells on a polarization axis opposite from Th22 cells and reveal AHR, JUN, and IFN as key regulators of these divergent T cell states.
Published in
Interferon subverts an AHR-JUN axis to promote CXCL13(+) T cells in lupus
Law C, Wacleche VS, Cao Y et al. · Nature 2024 · PMID 38987586 · doi:10.1038/s41586-024-07627-2
This dataset
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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 GSE233050_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 PRJNA974830 and SRA study SRP533994. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38987586) ↗
Study design
16 conditions, mostly in triplicate
CD4_mem_AHRinh_JUN_CnR ×4 CD4_mem_TCDD_JUN_CnR ×4 CD4_mem_AHRinh_IgG_CnR ×4 CD4_mem_TCDD_IgG_CnR ×4 CD4_mem_sgNT_AHR_CnR ×3 CD4_mem_sgAHR_AHR_CnR ×3 CD4_mem_sgNT_IgG_CnR ×3 CD4_mem_sgAHR_IgG_CnR ×3 +32 more

Supports a between-group comparison across 52 samples.

How we read this: 16 replicated groups read from 76 sample titles; they account for 52 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

+ 36 more — browse all 76 samples with per-sample file links →

Datasets on a similar topic

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