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Ramulus Mori (Sangzhi) Alkaloids Attenuate Diet-Induced Obesity by Promoting White Adipose Browning and Enhancing Brown Fat Thermogenesis

GSE312093 Mus musculus (mouse) RNA-seq (gene expression) 43 samples Submitted 2025/12/04 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 43 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
43 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.
Summary (written by the submitters)
Obesity is a chronic metabolic disorder characterized by excessive adipose accumulation and is closely associated with type 2 diabetes mellitus (T2DM), cardiovascular diseases, and metabolic dysfunction associated steatotic liver disease. Enhancing adipose thermogenic capacity has emerged as a promising strategy to counteract obesity. Ramulus Mori (Sangzhi) alkaloids (SZ-A), a natural alkaloid complex clinically approved for T2DM, exhibit multiple metabolic benefits, but their anti-obesity mechanisms remain unclear.
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 GSE312093_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 PRJNA1372171 and SRA study SRP650355. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 43 more — browse all 43 samples with per-sample file links →

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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.