GEO series

Decoding the Epigenetics and Chromatin Loop Dynamics of Androgen Receptor-Mediated Transcription [HiChIP]

GSE251895 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 15 samples Submitted 2024/09/27 Platform GPL16791

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 15 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: 15 samples: 15 samples, each with a distinct title — no replicated groupsGroups 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: Decoding the epigenetics and chromatin loop dynamics of androgen receptor-mediated transcriptionNature communications · 2024

Summary (written by the submitters)

Androgen receptor (AR)-mediated transcription plays a critical role in normal prostate development and prostate cancer growth. AR drives gene expression by binding to thousands of cis-regulatory elements (CRE) that loop to hundreds of target promoters. With multiple CREs interacting with a single promoter, it remains unclear how individual AR bound CREs contribute to gene expression.

Read the full summary ↓

To characterize the involvement of these CREs, we investigated the AR-driven epigenetic and chromosomal chromatin looping changes. We collected a kinetic multi-omic dataset comprised of steady-state mRNA, chromatin accessibility, transcription factor binding, histone modifications, chromatin looping, and nascent RNA. Using an integrated regulatory network, we found that AR binding induces sequential changes in the epigenetic features at CREs, independent of gene expression. Further, we showed that binding of AR does not result in a substantial rewiring of chromatin loops, but instead increases the contact frequency of pre-existing loops to target promoters. Our results show that gene expression strongly correlates to the changes in contact frequency. We then proposed and experimentally validated an unbalanced multi-enhancer model where the impact on gene expression of AR-bound enhancers is heterogeneous, and is proportional to their contact frequency with target gene promoters. Overall, these findings provide new insight into AR-mediated gene expression upon acute androgen simulation and develop a mechanistic framework to investigate nuclear receptor mediated perturbations.

Published in

Decoding the epigenetics and chromatin loop dynamics of androgen receptor-mediated transcription

Altıntaş UB, Seo JH, Giambartolomei C et al. · Nature communications 2024 · PMID 39489778 · doi:10.1038/s41467-024-53758-5

This dataset

Open GSE251895 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 GSE251895_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 PRJNA1055896 and SRA study SRP479651. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39489778) ↗

Study design

15 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 15 sample titles: 15 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

GSM7989632 LNCaP_H3K27ac_0m_rep1_HIChIP
GSM7989633 LNCaP_H3K27ac_0m_rep2_HiChIP
GSM7989634 LNCaP_H3K27ac_30m_rep1_HiChIP
GSM7989635 LNCaP_H3K27ac_30m_rep2_HiChIP
GSM7989636 LNCaP_H3K27ac_4h_rep1_HiChIP
GSM7989637 LNCaP_H3K27ac_4h_rep2_HiChIP
GSM7989638 LNCaP_H3K27ac_16h_rep1_HiChIP
GSM7989639 LNCaP_H3K27ac_16h_rep2_HiChIP
GSM7989640 LNCaP_H3K27ac_72h_rep1_HiChIP
GSM7989641 LNCaP_H3K27ac_72h_rep2_HiChIP
GSM7989642 LNCaP_H3K4me3_0m_rep1_HiChIP
GSM7989643 LNCaP_H3K4me3_30m_rep1_HiChIP
GSM7989644 LNCaP_H3K4me3_4h_rep1_HiChIP
GSM7989645 LNCaP_H3K4me3_16h_rep1_HiChIP
GSM7989646 LNCaP_H3K4me3_72h_rep1_HiChIP

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.