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Effects of HDAC gene knockdowns in human stem cell derived cardiomyocytes

GSE309350 Homo sapiens (human) RNA-seq (gene expression) 61 samples Submitted 2026/03/12 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 61 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
61 samples: 18 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.
Paper
Comparative transcriptomics analysis of histone deacetylases, transcription factors, and ion channel genes in human iPSC-cardiomyocytes vs. the adult human heartbioRxiv : the preprint server for biology · 2026
Summary (written by the submitters)
Histone deacetylases (HDACs) play a major role in a wide range of cellular and developmental processes, often as master regulators of gene transcription. These epigenetic modifiers, which include eleven canonical HDACs and seven sirtuins (SIRTs), are commonly studied in cancer, especially by using nonselective HDAC inhibitor drugs. However, HDACs and SIRTs are also thought to be influential in cardiac function and pathology, yet the specific roles of individual HDACs have not been robustly probed in cardiomyocytes.
Read the full summary ↓
In this study, we report the transcriptomic effects of individual HDAC/SIRT knockdowns in human induced pluripotent stem cell derived cardiomyocytes.
Published in
Comparative transcriptomics analysis of histone deacetylases, transcription factors, and ion channel genes in human iPSC-cardiomyocytes vs. the adult human heart
Pozo MR, Pressler MP, Horvath A et al. · bioRxiv : the preprint server for biology 2026 · PMID 41648544 · doi:10.64898/2026.01.16.700033
This dataset
Open GSE309350 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 GSE309350_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1335217 and SRA study SRP628390. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41648544) ↗
Study design
18 conditions, mostly in triplicate
Untreated hiPSC-CM, biological replicate # ×7 Negative siRNA in hiPSC-CM, biological replic… ×6 HDAC1 knockdown in hiPSC-CM, biological repli… ×3 HDAC2 knockdown in hiPSC-CM, biological repli… ×3 HDAC3 knockdown in hiPSC-CM, biological repli… ×3 HDAC4 knockdown in hiPSC-CM, biological repli… ×3 HDAC5 knockdown in hiPSC-CM, biological repli… ×3 HDAC6 knockdown in hiPSC-CM, biological repli… ×3 +10 more

Supports a between-group comparison across 61 samples.

How we read this: 18 replicated groups read from 61 sample titles; they account for 61 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

+ 21 more — browse all 61 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq 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.