GEO series

HMGA2 overexpression drives a leiomyoma-like phenotype by modulating the epigenomic environment in primary myometrial cells [ChIP-Seq]

GSE276287 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 15 samples Submitted 2025/10/01 Platform GPL18573

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: Engineered uterine primary myometrial cells with high-mobility group AT-hook 2 overexpression display a leiomyoma-like transcriptional and epigenomic phenotypeF&S science · 2024

Summary (written by the submitters)

With the utilization of advanced tools for genome-wide studies, the role of the epigenome in regulating gene expression is becoming more evident in both normal tissue development and disease states. Uterine fibroids, also known as leiomyomas, are a major reproductive disease that manifests as benign tumors and altered extracellular matrix composition leading to severe pathological symptoms.

Read the full summary ↓

Several genomic alterations have been associated with leiomyoma. HMGA2 overexpression has been noted in approximately 10% of all patients with leiomyoma. HMGA2 is a chromatin-targeted protein and is therefore an important contributor to altered transcriptomic outcomes. However, due to a lack of specific antibodies against HMGA2 and appropriate in vitro cellular models, there is a lack in understanding of HMGA2 interaction with and regulation of chromatin in the context of leiomyoma. To address this gap, we engineered primary myometrial cells that express V5-tagged HMGA2 at levels comparable to those observed in leiomyoma. We observed transcriptomic and H3K27 acetylation changes that appeared to drive a leiomyoma-like phenotype in the engineered HMGA2v5 cells. HMGA2 was found to be diffusedly bound to chromatin, with most of the binding occurring at promoter- distal regions. Moreover, altered chromatin accessibility was observed in HMGA2v5 cells, with enrichment of AP-1 family transcription factor binding motifs at various sites. Thus, our study suggests that overexpression of HMGA2 modulates the genomic architecture of myometrial cells to cause leiomyoma-like gene expression and epigenomic changes.

Published in

Engineered uterine primary myometrial cells with high-mobility group AT-hook 2 overexpression display a leiomyoma-like transcriptional and epigenomic phenotype

Saini P, Holmes AG, Wei JJ et al. · F&S science 2024 · PMID 39074663 · doi:10.1016/j.xfss.2024.07.008

This dataset

Open GSE276287 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 GSE276287_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 PRJNA1156549 and SRA study SRP530393. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39074663) ↗

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

GSM8495086 1313 myo primary control input
GSM8495087 1313 myo primary control H3K27ac
GSM8495088 1313 myo primary HMGA2-V5 input
GSM8495089 1313 myo primary HMGA2-V5 H3K27ac
GSM8495090 1313 myo primary HMGA2-V5 V5
GSM8495091 1289 myo primary control input
GSM8495092 1289 myo primary control H3K27ac
GSM8495093 1289 myo primary HMGA2-V5 input
GSM8495094 1289 myo primary HMGA2-V5 H3K27ac
GSM8495095 12898 myo primary HMGA2-V5 V5
GSM8495096 1257 myo primary control input
GSM8495097 1257 myo primary control H3K27ac
GSM8495098 1257 myo primary HMGA2-V5 input
GSM8495099 1257 myo primary HMGA2-V5 H3K27ac
GSM8495100 1257 myo primary HMGA2-V5 V5

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