← BioTransfer GEO Dataset Finder
GEO series

Transcriptomic Responses to Neuromuscular Electrical Stimulation (NMES) in Muscle, Brain and Plasma Exosomes in WT and Klotho Deficient Mice [mRNA]

GSE296705 Mus musculus (mouse) RNA-seq (gene expression) 72 samples Submitted 2025/09/03 Platform GPL34290
At a glance

RNA-seq (gene expression) · mouse · 72 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
72 samples: 72 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
Transcriptomic Response to Neuromuscular Electrical Stimulation in Muscle, Brain, and Plasma EVs in WT and Klotho-Deficient MiceInternational journal of molecular sciences · 2025
Summary (written by the submitters)
Previous studies indicate extracellular vesicles (EVs) play a role in cellular communication which may be impacted by neuromuscular electrical stimulation (NMES), a noninvasive approach to improve daily living and functional motor activities. Therefore, we utilized NMES to stimulate the tibialis anterior of WT and KlHET mice and evaluated transcriptomic profiles of muscle tissue, brain tissue, and plasma-derived EVs.
Read the full summary ↓
Muscle mRNA indicate that genes related to metabolic processes are upregulated in response to NMES in but have little overlap in WT and KlHET NMES versus control. Brain mRNA in WT shows upregulation of several genes related to blood flow and cell adhesion processes while KlHET shows downregulation in cell adhesion processes and immune function. In plasma-derived EVs, little overlap in ncRNA, with the exception of let-7d-5p which regulates insulin signaling targets and immune responses, was present. Findings indicate local and distal transcriptomic metabolic effects of NMES are mediated by KLOTHO deficiency.
Published in
Transcriptomic Response to Neuromuscular Electrical Stimulation in Muscle, Brain, and Plasma EVs in WT and Klotho-Deficient Mice
Cavanaugh CA, Moore AE, Fitz NF et al. · International journal of molecular sciences 2025 · PMID 40869172 · doi:10.3390/ijms26167849
This dataset
Open GSE296705 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 GSE296705_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 PRJNA1260776 and SRA study SRP584102. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40869172) ↗
Study design
72 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 72 sample titles: 72 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

+ 32 more — browse all 72 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.