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ABCA1-eRNA as a novel Epigenetic Regulator, promotes cholesterol efflux, Attenuates Macrophage Inflammation and Severity of Coronary Artery Disease [CUT&TAG]

GSE192937 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 14 samples Submitted 2024/12/01 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 14 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
14 samples: 14 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.
Summary (written by the submitters)
Enhancer RNAs (eRNAs) are emerging as powerful regulators of various biological processes, but the underlying epigenetic regulatory mechanisms of these molecules in cholesterol homeostasis remain elusive. Using an integrated genomic screen, we identified an intragenic super-enhancer derived long noncoding RNA embedded in the ATP-binding cassette transporter A1 (ABCA1) gene, named ABCA1-seRNA, which is required for activation of RXRα/LXR mediated gene expression.
Read the full summary ↓
Deficiency of ABCA1-seRNA abolished cholesterol efflux, promotes Macrophage Inflammation, and that haven been causally Susceptibility to Coronary heart disease. Mechanistically, ABCA1-seRNA affects cholesterol efflux by interaction with MED23 and recruitment RXR and LXR to mediate ABCA1 transcription in cis. Furthermore, ABCA1-seRNA repression inflammatory response and attenuated macrophage M1 polarization and migration through ubiquitination of a NF-B subunit P65. Our results suggest that super-enhancer derived long noncoding RNA, as a novel Epigenetic Regulator, are critical components to maintain cholesterol homeostasis and inflammation restriction, represent an attractive therapeutic target to reduce Atherosclerotic cardiovascular disease (ASCVD).
This dataset
Open GSE192937 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 GSE192937_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 PRJNA793853 and SRA study SRP353309. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
14 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 14 sample titles: 14 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
Datasets on a similar topic

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

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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.