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NEMO Knockout Drives Variations in Gene Expression Regenerative Trajectory and Induces Chromatin Remodeling in murine muscle satellite cells during healing from traumatic injury

GSE262348 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 20 samples Submitted 2024/04/01 Platform GPL17021Platform GPL19057
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 20 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
20 samples: 20 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.
Summary (written by the submitters)
This study investigates the impact of NEMO knockout on healing from traumatic tibial injury within a murine muscle satellite cell model. NEMO KO mice were profiled via RNA-seq at 0, 2, 4, 7 days post cold shock injury (DPI). The largest transcriptional response was observed at 2 DPI within the WT model, but NEMO knockouts exhibited delayed myogenesis and muscle regenerative defects.
Read the full summary ↓
Furthermore, it was observed that new fiber formation is defected upon transplantation of mutant derived MuSCs. mRNA profiling further suggested that loss of NF-kB signaling in MuSC’s in response to NEMO KO alters their ECM and cytokine secretome production. Additional profiling was performed at 2DPI via ATAC-seq within WT and NEMO mouse satellite cells, with observed changes in chromatin remodeling suggesting bidirectional MuSC-transcriptional regulator communication in skeletal muscle regeneration.
This dataset
Open GSE262348 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 GSE262348_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 PRJNA1091379 and SRA study SRP497505. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
20 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 20 sample titles: 20 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

Search all mouse 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.