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Isoform Usage as a Distinct Regulatory Layer Driving Nutrient-Responsive Metabolic Adaptation (RNA-seq)

GSE248964 Mus musculus (mouse) RNA-seq (gene expression) 117 samples Submitted 2025/02/03 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 117 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
117 samples
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
Isoform usage as a distinct regulatory layer driving nutrient-responsive metabolic adaptationCell metabolism · 2025
Summary (written by the submitters)
This study outlines the landscape of isoform usage modulations across major metabolic organs in both mice and monkeys, spanning diverse metabolic states. Our in-depth analysis identify numerous isoform-usage events, intricately influenced by nutrient challenges and largely independent of gene expression regulation. When analysing splicing factor-binding motifs in nutrient-regulated events, HuR emerges as the predominant orchestrator of the isoform network in adipocytes.
Published in
Isoform usage as a distinct regulatory layer driving nutrient-responsive metabolic adaptation
Li J, Cai C, Teo WW et al. · Cell metabolism 2025 · PMID 39938511 · doi:10.1016/j.cmet.2025.01.009
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 GSE248964_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 PRJNA1046513 and SRA study SRP474987. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 117 more — browse all 117 samples with per-sample file links →

Datasets on a similar topic

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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.