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Skeletal Muscle NAD Depletion Does Not Accelerate Muscle Aging

GSE273462 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2025/04/23 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 16 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
16 samples: 8 × KO vs 8 × WTGroups 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)
NAD is a ubiquitous electron carrier essential for energy metabolism and the post-translational modification of numerous regulatory proteins. Perturbation of NAD metabolism is considered detrimental to health, with NAD depletion commonly thought to promote aging. However, to what extent normal NAD concentration can be decreased without deleterious repercussions is unclear.
Read the full summary ↓
Here, we describe a mouse model where NAMPT-mediated NAD+ biosynthesis is disrupted in adult skeletal muscle. The resulting 85% decrease in muscle NAD+ abundance did not cause tissue degeneration or dysfunction, as reflected in its unchanged morphology, contractility, and exercise tolerance. The lack of defects was corroborated by intact mitochondrial respiratory capacity and unaffected muscle transcriptomic and proteomic profiles. Furthermore, lifelong NAD depletion did not accelerate muscle aging or impair whole-body metabolism. Collectively, these findings demonstrate that NAD depletion does not drive the age-related decline in skeletal muscle function.
This dataset
Open GSE273462 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 GSE273462_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 PRJNA1141964 and SRA study SRP523110. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 × KO vs 8 × WT

Supports a between-group comparison across 16 samples.

How we read this: 2 replicated groups read from 16 sample titles; they account for 16 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
Datasets on a similar topic

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