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Engineered heart tissues facilitate functional characterization of noncoding variants implicated in Hypertrophic and Dilated Cardiomyopathy [Bulk RNA-Seq]

GSE331527 Homo sapiens (human) Single-nucleus RNA-seq 15 samples Submitted 2026/06/16 Platform GPL24676
At a glance

Single-nucleus RNA-seq · human · 15 samples

What it is
Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue). Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
15 samples: 5 conditions, mostly in triplicateGroups 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)
Inherited cardiomyopathies frequently arise from rare, highly penetrant coding variants with variable clinical expressivity. Recent biobank-scale genome-wide association studies (GWAS) suggest significant polygenic contributions to cardiovascular diseases, including cardiomyopathy. Most GWAS loci map to noncoding regions, which are poorly conserved across species, requiring a human genome context for experimental validation.
Read the full summary ↓
We created engineered heart tissues (EHTs) from human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes and primary cardiac fibroblasts. We assayed single-cell gene expression and chromatin accessibility to generate comprehensive genome-wide regulatory maps. Open chromatin regions (OCRs) were integrated with chromatin contact information and used to functionally fine-map single nucleotide polymorphisms (SNPs) in cardiomyopathy GWAS. SNPs and their associated regulatory regions were assessed using reporter assays, genome editing, and expression profiling. Single-cell RNA-seq of EHTs confirmed populations recapitulating major cell types found in hearts, with advanced cardiomyocyte maturation compared to monolayer hiPSC-cardiomyocytes. More than 400,000 OCRs were resolved to cell type and assayed for canonical transcription factor footprints. Functional fine-mapping of GWAS loci prioritized 5817 variants, and reporter assays on select variants validated allele-specific enhancer activity. We identified a locus harboring significant GWAS signals from both dilated cardiomyopathy and left ventricle ejection fraction in an intergenic region at chr3p25.1. Several of these variants lie in OCRs participating in long range chromatin interactions with SLC6A6 and GRIP2. Haplotype-resolved and synthetic reporter assays confirmed enhancer activity and narrowed candidate SNPs. CRISPR-deletion of this region reduced expression of both SLC6A6 and GRIP2, indicating the enhancer regulates the expression of more than one gene. EHTs with the enhancer deletion displayed markedly reduced contractile function, confirming the necessity of this enhancer region for normal contractility. Taken together, EHTs derived from hiPSCs are an experimentally tractable platform for testing the function of noncoding variants as modifiers of cardiomyopathy. Variants fine-mapped from cardiomyopathies using EHT regulatory maps have functional consequences and provide a set of prioritized sites to advance the study of polygenic heart failure liability.
This dataset
Open GSE331527 in finder → Find more human RNA-seq 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 GSE331527_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1468540 and SRA study SRP702303. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
5 conditions, mostly in triplicate
purified monolayer hiPSC-cardiomyocytes, day … ×3 purified monolayer hiPSC-cardiomyocytes, day1… ×3 purified monolayer hiPSC-cardiomyocytes, day1… ×3 purified monolayer hiPSC-cardiomyocytes, day1… ×3 purified monolayer hiPSC-cardiomyocytes, day1… ×3

Supports a between-group comparison across 15 samples.

How we read this: 5 replicated groups read from 15 sample titles; they account for 15 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
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