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The Dlk1-Dio3 noncoding RNA cluster coordinately regulates mitochondrial respiration and chromatin structure to establish proper cell state for muscle differentiation

GSE272974 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 30 samples Submitted 2024/10/31 Platform GPL30172
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 30 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
30 samples: 30 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
The Dlk1-Dio3 noncoding RNA cluster coordinately regulates mitochondrial respiration and chromatin structure to establish proper cell state for muscle differentiationDevelopment (Cambridge, England) · 2024
Summary (written by the submitters)
To investigate the collective role of the Dlk1-Dio3 ncRNA cluster in myogenesis, we developed two stable CRISPR-Cas9 gene-edited C2C12 skeletal muscle cell lines, Meg3-proximal cis-acting sequence (Meg3-CAS or 2-4) to over-express and Meg3-transcription start site (Meg3-TSS or 2-7) to under-express the entire mega-cluster of Dlk1-Dio3 ncRNAs.
Read the full summary ↓
Mutations affecting the dosage of all ncRNAs expressed from the Dlk1-Dio3 locus cause profound changes in myoblast fusion and differentiation. To evaluate genome-wide perturbations in chromatin accessibility we evaluated specific histone lysine modifications, inducing the repressive histone mark, H3K27me3, and the activating mark, H3K4me3
Published in
The Dlk1-Dio3 noncoding RNA cluster coordinately regulates mitochondrial respiration and chromatin structure to establish proper cell state for muscle differentiation
Pinheiro A, Petty CA, Stephens CE et al. · Development (Cambridge, England) 2024 · PMID 39612212 · doi:10.1242/dev.203127
This dataset
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.

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 GSE272974_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1139736 and SRA study SRP521957. Searching any of these in the dataset finder brings you back here.

Study design
30 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 30 sample titles: 30 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
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.