← BioTransfer GEO Dataset Finder
GEO series

ZNF143 is a transcriptional regulator of nuclear-encoded mitochondrial genes that acts independently of looping and CTCF

GSE260914 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 78 samples Submitted 2024/03/08 Platform GPL21626Platform GPL16417
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 78 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
78 samples: 25 conditions, mostly in duplicateGroups 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
ZNF143 is a transcriptional regulator of nuclear-encoded mitochondrial genes that acts independently of looping and CTCFMolecular cell · 2025
Summary (written by the submitters)
Gene expression is orchestrated by transcription factors (TFs), which bind to DNA in a sequence-specific manner, and by spatial genome structure, which constrains and shapes TF activity. Zinc finger protein 143 (ZNF143/ZFP143) is a TF that has been implicated in both gene activation and 3D genome organisation. We have generated an acute ZNF143/ZFP143 depletion system to study its direct consequences on chromatin looping and gene transcription.
Read the full summary ↓
The effects of ZNF143/ZFP143 depletion are inconsistent with it being a looping factor, which we further confirmed by systematic analysis of previous studies. However, degradation of ZNF143/ZFP143 led to the down-regulation of hundreds of its targets, which were found to be enriched in nuclear-encoded mitochondrial genes. By studying the consequences of ZNF143/ZFP143 loss in monoculture and in an in vitro embryonic development model, we establish ZNF143/ZFP143 as a conserved transcriptional regulator of cell proliferation and differentiation by modulating mitochondrial functions.
Published in
ZNF143 is a transcriptional regulator of nuclear-encoded mitochondrial genes that acts independently of looping and CTCF
Magnitov MD, Maresca M, Alonso Saiz N et al. · Molecular cell 2025 · PMID 39708805 · doi:10.1016/j.molcel.2024.11.031
This dataset
Open GSE260914 in finder → Find more mouse 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 GSE260914_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 PRJNA1083999 and SRA study SRP493460. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39708805) ↗
Study design
25 conditions, mostly in duplicate
TTseq_DMSO ×2 TTseq_dTAG_2H ×2 TTseq_dTAG_6H ×2 TTseq_dTAG_24H ×2 4C_DMSO_rep1.Zfp ×2 4C_DMSO_rep2.Zfp ×2 4C_dTAG_6H_rep1.Zfp ×2 4C_dTAG_6H_rep2.Zfp ×2 +45 more

Supports a between-group comparison across 50 samples.

How we read this: 25 replicated groups read from 78 sample titles; they account for 50 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

+ 38 more — browse all 78 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.