GEO series

Multi-omics analysis of sarcospan overexpression in mdx skeletal muscle reveals compensatory remodeling of cytoskeleton-matrix interactions that promote mechanotransduction pathways

GSE262341 Mus musculus (mouse) RNA-seq (gene expression) 13 samples Submitted 2024/03/29 Platform GPL21103

At a glance

RNA-seq (gene expression) · mouse · 13 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: Mus musculus (mouse)
Samples: 13 samples: 5 × wild-type, vs 4 × mdx, vs 4 × mdxTG,Groups 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)

Background: The dystrophin-glycoprotein complex (DGC) is a critical adhesion complex of the muscle cell membrane, providing a mechanical link between the extracellular matrix (ECM) and the cortical cytoskeleton that stabilizes the sarcolemma during repeated muscle contractions. One integral component of the DGC is the transmembrane protein, sarcospan (SSPN).

Read the full summary ↓

Overexpression of SSPN in the skeletal muscle of mdx mice (murine model of DMD) restores muscle fiber attachment to the ECM in part through an associated increase in utrophin and integrin adhesion complexes at the cell membrane, protecting the muscle from contraction-induced injury. In this study, we utilized transcriptomic and ECM protein-optimized proteomics data sets from wild-type, mdx, and mdx transgenic (mdxTG) skeletal muscle tissues to identify pathways and proteins driving the compensatory action of SSPN overexpression. Methods: The tibialis anterior and quadriceps muscles were isolated from wild-type, mdx, and mdxTG mice and subjected to bulk RNA-Seq and global proteomics analysis using methods to enhance capture of ECM proteins. Data sets were further analyzed through the ingenuity pathway analysis (QIAGEN) and integrative gene set enrichment to identify candidate networks, signaling pathways, and upstream regulators. Results: Through our multi-omics approach, we identified 3 classes of differentially expressed genes and proteins in mdxTG muscle, including those that were (1) unrestored (significantly different from wild type, but not from mdx), (2) restored (significantly different from mdx, but not from wild type), and (3) compensatory (significantly different from both wild type and mdx). We identified signaling pathways that may contribute to the rescue phenotype, most notably cytoskeleton and ECM organization pathways. ECM-optimized proteomics revealed an increased abundance of collagens II, V, and XI, along with β-spectrin in mdxTG samples. Using ingenuity pathway analysis, we identified upstream regulators that are computationally predicted to drive compensatory changes, revealing a possible mechanism of SSPN rescue through a rewiring of cell-ECM bidirectional communication. We found that SSPN overexpression results in upregulation of key signaling molecules associated with regulation of cytoskeleton organization and mechanotransduction, including Yap1, Sox9, Rho, RAC, and Wnt. Conclusions: Our findings indicate that SSPN overexpression rescues dystrophin deficiency partially through mechanotransduction signaling cascades mediated through components of the ECM and the cortical cytoskeleton.

This dataset

Open GSE262341 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 GSE262341_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 PRJNA1091360 and SRA study SRP497485. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

5 × wild-type, vs 4 × mdx, vs 4 × mdxTG,

Supports a between-group comparison across 13 samples.

How we read this: 3 replicated groups read from 13 sample titles; they account for 13 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

GSM8163492 wild-type, replicate 1 wild-type,
GSM8163493 wild-type, replicate 2 wild-type,
GSM8163494 wild-type, replicate 3 wild-type,
GSM8163495 wild-type, replicate 4 wild-type,
GSM8163496 wild-type, replicate 5 wild-type,
GSM8163497 mdx, replicate 1 mdx,
GSM8163498 mdx, replicate 2 mdx,
GSM8163499 mdx, replicate 3 mdx,
GSM8163500 mdx, replicate 4 mdx,
GSM8163501 mdxTG, replicate 1 mdxTG,
GSM8163502 mdxTG, replicate 2 mdxTG,
GSM8163503 mdxTG, replicate 3 mdxTG,
GSM8163504 mdxTG, replicate 4 mdxTG,

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