GEO series

miR-200a-3p regulates gene expression of diabetic cardiomyopathy in murine cardiomyocytes

GSE233919 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2026/04/04 Platform GPL24247

At a glance

RNA-seq (gene expression) · mouse · 18 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: 18 samples: 6 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)

Hsa-miR200a-3p play a crucial role in regulating glycometabolism and diabetic progression. But how hsa-miR200a-3p impact diabetic cardiomyopathy development is sitill ill-defined. Here,we found that the expression of hsa-miR200a-3p was significantly reduced in mouse cardiomyocytes HL-1 cells after high glucose stimulation. And we systemically investigated the overall mRNA expression level under hsa-miR200a-3p mimics, or inhibitors treatment in HL-1 at high glucose conditions.

Read the full summary ↓

High-throughput sequencing results showed that 744 genes were significantly differentially expressed by high glucose stimulation in mouse cardiomyocytes. And when compared with the control group, 414 genes were differentially expressed after hsa-miR200a-3p overexpression; 33 genes were differentially expressed after added hsa-miR200a-3p inhibitor. WGCNA analysis found that all DEGs could be divided into five modules, and the gene expression pattern in the yellow module was positively correlated with hsa-miR200a-3p overexpression group and negatively correlated with hsa-miR200a-3p inhibitor group.We observed that these DEGs were mostly enriched in RrRNA processing, translation, and RNA transport. Then, we further identified three DEGs (Gm13205, Flnc, and Ntmt1) were found to be commonly expressed in down-regulated DEGs of the hsa-miR200a-3p mimics group and up-regulated DEGs of the hsa-miR200a-3p inhibitor/ high glucose groups. In addition, we predicted that Srm andTspan4 were two main targets for hsa-miR200a-3p in HL-1 cells. These findings demonstrate that high glucose suppressed hsa-miR200a-3p in vitro, and hsa-miR200a-3p may involve in diabetic cardiomyopathy development.

This dataset

Open GSE233919 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 GSE233919_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 PRJNA978577 and SRA study SRP440718. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

6 conditions, mostly in triplicate

Ctrl ×3 HG ×3 inhibitor ×3 inhibitor ctrl ×3 mimics ×3 mimics ctrl ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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

GSM7439065 Ctrl_rep1 Ctrl
GSM7439066 Ctrl_rep2 Ctrl
GSM7439067 Ctrl_rep3 Ctrl
GSM7439068 HG_rep1 HG
GSM7439069 HG_rep2 HG
GSM7439070 HG_rep3 HG
GSM7439071 inhibitor_rep1 inhibitor
GSM7439072 inhibitor_rep2 inhibitor
GSM7439073 inhibitor_rep3 inhibitor
GSM7439074 inhibitor ctrl_rep1 inhibitor ctrl
GSM7439075 inhibitor ctrl_rep2 inhibitor ctrl
GSM7439076 inhibitor ctrl_rep3 inhibitor ctrl
GSM7439077 mimics_rep1 mimics
GSM7439078 mimics_rep2 mimics
GSM7439079 mimics_rep3 mimics
GSM7439080 mimics ctrl_rep1 mimics ctrl
GSM7439081 mimics ctrl_rep2 mimics ctrl
GSM7439082 mimics ctrl_rep3 mimics ctrl

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Search all mouse RNA-seq datasets in GEO →

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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.