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Combinatorial targeting of the miR-379/miR-410 cluster normalizes glucose and lipid homeostasis in male models of diabetes and obesity

GSE304566 Mus musculus (mouse) RNA-seq (gene expression) 11 samples Submitted 2026/07/30 Platform GPL21103
At a glance

RNA-seq (gene expression) · mouse · 11 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
11 samples: 5 × Liver_NC vs 5 × Liver_TuDGroups 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)
The miR-379/miR-410 cluster, belonging to the Dlk1-Dio3 locus, is the largest cluster of miRNAs in mammals. Most of its components are predicted to regulate insulin signaling, and we found consistent upregulation of the cluster in the livers of obese subjects as well as of different experimental models of insulin resistance. We have engineered a tool, a TuD, able to target two microRNAs from the cluster in a liver-specific manner.
Read the full summary ↓
As a result, the cluster is repressed, which activates insulin signaling in the liver and leads to enhanced hepatic insulin sensitivity and reduced hepatic glucose output. This dataset includes transcriptomics data from liver tissue of young male mice carrying hepatic-specific expression of a TuD inhibitor able to repress the miR-379/miR-410 cluster (n=6) or a negative control sequence (n=5).
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 GSE304566_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 PRJNA1301793 and SRA study SRP607195. Searching any of these in the dataset finder brings you back here.

Study design
5 × Liver_NC vs 5 × Liver_TuD

Supports a between-group comparison across 10 samples.

How we read this: 2 replicated groups read from 11 sample titles; they account for 10 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
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