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Sphingosine kinase 2 regulates adipocyte browning and whole-body metabolism

GSE328946 Mus musculus (mouse) RNA-seq (gene expression) 36 samples Submitted 2026/06/30 Platform GPL13112
At a glance

RNA-seq (gene expression) · mouse · 36 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
36 samples: 12 conditions, mostly in triplicateGroups 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)
Obesity increases circulating levels of the bioactive sphingolipid metabolite sphingosine-1-phosphate (S1P). Here, we identify adipocyte-expressed sphingosine kinase 2 (SPHK2), an enzyme that produces S1P, as a regulator of adipose tissue browning. Mice with adipocyte-specific deletion of Sphk2 were protected from Western diet-induced obesity concomitantly with elevated energy expenditure and browning of subcutaneous fat and enhanced expression of Ucp1 and key thermogenic genes, resulting in reduced adiposity and hepatic steatosis, improved glucose tolerance and insulin sensitivity.
Read the full summary ↓
Mechanistically, obesogenic diet promoted nuclear localization of SPHK2 in adipocytes, where it cooperated with transcription factors to suppress the thermogenic transcriptome. Adipocyte SPHK2 was responsible for maintaining homeostatic circulating S1P levels and driving the pathogenic rise of S1P in response to obesogenic diet. Our findings reveal a distinct role of adipocyte SPHK2 in regulation of the thermogenic program important for whole-body metabolic homeostasis and energy expenditure and highlights SPHK2 as a potential therapeutic target for treatment of metabolic disorders.
This dataset
Open GSE328946 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 GSE328946_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 PRJNA1457063 and SRA study SRP694289. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
12 conditions, mostly in triplicate
Chow diet, brown adipose, wild-type repicate ×3 Chow diet, brown adipose, Sphk2 deleted repic… ×3 Chow diet, gonadal white adipose, wild-type r… ×3 Chow diet, gonadal white adipose, Sphk2 delet… ×3 Chow diet, subcutaneous white adipose, wild-t… ×3 Chow diet, subcutaneous white adipose, Sphk2 … ×3 Western diet, brown adipose, wild-type repica… ×3 Western diet, brown adipose, Sphk2 deleted re… ×3 +4 more

Supports a between-group comparison across 36 samples.

How we read this: 12 replicated groups read from 36 sample titles; they account for 36 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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