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Selective Translation of ZNF281 as Part of the Integrated Stress Response System has Therapeutic Relevance for Cardio-Oncology

GSE325898 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 18 samples Submitted 2026/03/24 Platform GPL24676Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 18 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
Mus musculus (mouse)
Samples
18 samples: 6 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)
This study aims to investigate the role of ZNF281 in cardiomyocyte function and tumor biology by integrating RNA-seq and ChIP-seq datasets. Using a C57BL/6 mouse model, we isolated cardiomyocytes from ZNF281 overexpression (OE) and knockdown (Kd) mice, along with their respective controls, to analyze transcriptomic changes and ZNF281 genome-wide binding patterns.
Read the full summary ↓
Additionally, we included tumor samples from nude mice, specifically A549 ZNF281 knockout (KO) tumors and parental A549 tumors, to explore the differential regulation and binding patterns of ZNF281 between cardiac tissue and tumors. RNA-seq was performed to identify differentially expressed genes regulated by ZNF281 in both contexts, while ChIP-seq was conducted to map ZNF281 DNA-binding sites and its role in transcriptional regulation. This study will provide insights into the context-dependent functions of ZNF281 in the heart and tumors, enhancing our understanding of its role in cardiac biology and cancer progression.
This dataset
Open GSE325898 in finder → Find more 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 GSE325898_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 PRJNA1227919 and SRA study SRP566289. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly in triplicate
RNA_Control ×3 RNA_ZNF281_OE ×3 ZNF_ChIP_Control ×3 ZNF_ChIP_ZNF281_OE ×3 ZNF281_ChIP_Tumor_Parental ×3 RNA_A549_ZNF281 KO ×2 RNA_A549_Parental ×1

Supports a between-group comparison across 17 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 17 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
Datasets on a similar topic

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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.