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Vitamin B2 Sensing by the Nuclear Receptor AhR Reprograms Hepatic Metabolism [ChIP-Seq]

GSE341320 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 54 samples Submitted 2026/08/01 Platform GPL30173Platform GPL34284Platform GPL34290
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 54 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
54 samples: 20 conditions, mostly in duplicateGroups 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)
Nuclear receptors such as RAR/RXR and VDR directly sense vitamins A and D, but analogous sensing mechanisms for most other vitamins remain unknown. Here we identify a metabolite sensing pathway linking vitamin B2 (riboflavin) availability to an adaptive gene expression program. Riboflavin deficiency limits the FAD-dependent enzyme kynurenine 3-monooxygenase, leading to accumulation of kynurenine, an endogenous ligand of the aryl hydrocarbon receptor (AhR).
Read the full summary ↓
Kynurenine-induced AhR nuclear translocation selectively activates poised hepatic enhancers in cooperation with AP-1 and C/EBPα, inducing glucuronidation genes and the FAD synthase gene FLAD1. This response is required to maintain intracellular FAD levels and support cell fitness under riboflavin-limiting conditions. In vivo, dietary riboflavin deficiency enhances hepatic drug clearance and reduces irinotecan toxicity. Together, these findings reveal a vitamin-sensing mechanism in which a cofactor-dependent enzyme acts as the sensor and AhR functions as the transcriptional effector that enables both flavin homeostasis and hepatic clearance capacity.
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 GSE341320_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 PRJNA1501350 and SRA study SRP721051. Searching any of these in the dataset finder brings you back here.

Study design
20 conditions, mostly in duplicate
HepG2_Day12_Cont_H3K27ac_ChIP ×5 HepG2_Day12_B2_minus_H3K27ac_ChIP ×5 AhR_flox_Hepatocyte_Cont_Ad_Cont_H3K27ac_ChIP ×3 AhR_flox_Hepatocyte_B2_minus_Ad_Cont_H3K27ac_… ×3 AhR_flox_Hepatocyte_Cont_Ad_Cre_H3K27ac_ChIP ×3 AhR_flox_Hepatocyte_B2_minus_Ad_Cre_H3K27ac_C… ×3 Mouse_Liver_4W_Control_AhR_ChIP ×3 Mouse_Liver_4W_B2_minus_AhR_ChIP ×3 +12 more

Supports a between-group comparison across 54 samples.

How we read this: 20 replicated groups read from 54 sample titles; they account for 54 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

+ 14 more — browse all 54 samples with per-sample file links →

Datasets on a similar topic

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

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