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LSMEM2, localized at the neuromuscular junction, modulates mitochondrial integration in skeletal muscles

GSE285026 Mus musculus (mouse) RNA-seq (gene expression) 15 samples Submitted 2025/06/25 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 15 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
15 samples: 15 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
LSMEM2, Localized at the Neuromuscular Junction, Modulates Mitochondrial Integration in Skeletal MusclesFASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2025
Summary (written by the submitters)
In addition to the canonical metabolism-regulating function, AMP-activated protein kinase (AMPK) has non-canonical functions, in which AMPK spatiotemporally phosphorylates specific sets of substrates. Recently, we identified LSMEM2, a novel substrate of AMPK in the heart. LSMEM2 is a membrane protein localized at the intercalated disc (ICD), whose function is currently under investigation.
Read the full summary ↓
Interestingly, LSMEM2 is also expressed in the skeletal muscles. As skeletal muscles lack a homophilic intercellular junction corresponding to the ICD in the heart, predicting the role of LSMEM2 in skeletal muscles is difficult. In this study, we identified that LSMEM2 is expressed in skeletal muscles, specifically at the neuromuscular junction (NMJ). LSMEM2-knockout mice showed no histological abnormalities, suggesting that LSMEM2 is not essential for skeletal muscle development. The overexpression of full-length wild-type or C-del mutant of LSMEM2 led to the tubular aggregate formation with functional abnormality in male mice. RNA sequence analysis revealed that the genesets of mitochondrial oxidative phosphorylation and vesicle-mediated transport are enriched in LSMEM2 overexpression. Furthermore, histological analysis demonstrated the accumulation of swollen subsarcolemmal mitochondria in LSMEM2-overexpressing skeletal muscles. The study findings suggest that LSMEM2 may play a role in the pathogenesis of skeletal muscle diseases.
Published in
LSMEM2, Localized at the Neuromuscular Junction, Modulates Mitochondrial Integration in Skeletal Muscles
Elrefaei E, Yamazaki S, Yazawa I et al. · FASEB journal : official publication of the Federation of American Societies for Experimental Biology 2025 · PMID 40525396 · doi:10.1096/fj.202402152R
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 GSE285026_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: 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 PRJNA1201062 and SRA study SRP552924. Searching any of these in the dataset finder brings you back here.

Study design
15 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 15 sample titles: 15 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
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