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RXR binding pattern in human PMA-differentiated THP-1 cells upon ligand stimulation [ChIP-seq]

GSE315571 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 28 samples Submitted 2026/05/14 Platform GPL30173
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 28 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
28 samples: 14 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.
Paper
Genome-wide chromatin profiling reveals a nonlimiting role for RXR in macrophage-like cells stimulated with multiple nuclear receptor agonistsThe Journal of biological chemistry · 2026
Summary (written by the submitters)
Retinoid X receptors (RXRs) act as obligate dimerisation partners for multiple nuclear receptors (NRs), each with distinct regulatory functions. In this study, human PMA-differentiated THP-1 (PMA-THP-1) cells were treated with single or combined ligands for RXR or six partners for 2 hours, and the genomic binding landscape of RXR was investigated using ChIP-seq.
Read the full summary ↓
RXR genomic binding regions were also mapped following 1 hour of treatment with vehicle or 1,25-vitD using ChIP-seq. In addition, histone H3 lysine 27 acetylation (H3K27ac) was mapped following 6 hours of treatment with vehicle or 1,25-vitD using ChIP-seq. In parallel, RNA-seq was performed on PMA-THP-1 cells following 6 hours of treatment with vehicle, 1,25-vitD or combined ligands to identify and compare the regulated gene sets.
Published in
Genome-wide chromatin profiling reveals a nonlimiting role for RXR in macrophage-like cells stimulated with multiple nuclear receptor agonists
Mianesaz H, Göczi L, Bojcsuk D et al. · The Journal of biological chemistry 2026 · PMID 42031173 · doi:10.1016/j.jbc.2026.111486
This dataset
Open GSE315571 in finder → Find more human 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 GSE315571_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 PRJNA1398274 and SRA study SRP659740. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42031173) ↗
Study design
14 conditions, mostly in duplicate
hs_THP1_2h_Vehicle_AntiRXRA_21218-1-AP_ChIPseq ×2 hs_THP1_2h_AM580_100nM_AntiRXRA_21218-1-AP_Ch… ×2 hs_THP1_2h_Calcitriol_100nM_AntiRXRA_21218-1-… ×2 hs_THP1_2h_GW501516_100nM_AntiRXRA_21218-1-AP… ×2 hs_THP1_2h_GW3965_1uM_AntiRXRA_21218-1-AP_ChI… ×2 hs_THP1_2h_RSG_1uM_AntiRXRA_21218-1-AP_ChIPseq ×2 hs_THP1_2h_T3_100nM_AntiRXRA_21218-1-AP_ChIPs… ×2 hs_THP1_2h_LG268_1uM_AntiRXRA_21218-1-AP_ChIP… ×2 +6 more

Supports a between-group comparison across 28 samples.

How we read this: 14 replicated groups read from 28 sample titles; they account for 28 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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