← BioTransfer GEO Dataset Finder
GEO series

Circadian reprogramming of protein homeostasis and glycolipid metabolism in diabetic nephropathy

GSE283571 Mus musculus (mouse) RNA-seq (gene expression) 47 samples Submitted 2026/02/18 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 47 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
47 samples: 12 conditions, mostly with about 4 replicates eachGroups 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.
Paper
Circadian Reprogramming of Protein Homeostasis and Glycolipid Metabolism in Diabetic NephropathyFASEB bioAdvances · 2026
Summary (written by the submitters)
Background Dysfunction of the circadian clock has been implicated in the pathogenesis of a variety of diseases, including metabolic disorders, inflammatory conditions, and cancer. While the significance of circadian rhythm in diabetic nephropathy is gaining attention, the specific alterations in circadian profiles in diabetic nephropathy remain unexplored.
Read the full summary ↓
Methods In the present study, we performed RNA sequencing on renal cortex samples collected every 4-hour across the day from both control and diabetic mice. The rhythmicity of genes was identified using the JTK_CYCLE algorithm for each group. Genes that lost, acquired, or sustained rhythmicity in diabetic mice were denoted the circadian dysregulation gene-set. Subsequent bioinformatic analyses focused on this gene set to investigate the circadian reprogramming in diabetic nephropathy. Results We observed significant circadian disruption in the kidney of diabetic mice, marked by both the gain and loss of rhythmicity, along with alterations in the phase and amplitude of genes that retained rhythmic expressions. Circadian disturbances such like phase shifts and alterations in relative amplitude or mesor, were noted in core clock genes. Furthermore, genes that lost rhythmicity in diabetic nephropathy were predominantly associated with protein homeostasis and glycolipid metabolism, whereas those that gained rhythmicity were mainly linked to gene regulation, fatty acid metabolism, and protein transport. The genes in the circadian dysregulation gene-set that exhibit differential expression at least at one Zeitgeber time, were most prominently enriched in lipid metabolic process. WGCNA and correlation analysis revealed co-expression networks involving core clock genes and PPAR signaling pathway with renal triglyceride levels. Conclusions Our study reveals substantial circadian disruption in diabetic nephropathy, with significant impacts on protein homeostasis and glycolipid metabolism. Furthermore, our findings highlight the potential influence of circadian system dysregulation on the disorder of fatty acid metabolism in diabetic nephropathy.
Published in
Circadian Reprogramming of Protein Homeostasis and Glycolipid Metabolism in Diabetic Nephropathy
Li XQ, Cheng L, Chen TF et al. · FASEB bioAdvances 2026 · PMID 41684893 · doi:10.1096/fba.2025-00305
This dataset
Open GSE283571 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 GSE283571_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 PRJNA1194552 and SRA study SRP549585. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41684893) ↗
Study design
12 conditions, mostly with about 4 replicates each
Ctrl_ZT0 ×4 Ctrl_ZT4 ×4 Ctrl_ZT12 ×4 Ctrl_ZT16 ×4 Ctrl_ZT20 ×4 DM_ZT0 ×4 DM_ZT4 ×4 DM_ZT8 ×4 +4 more

Supports a between-group comparison across 47 samples.

How we read this: 12 replicated groups read from 47 sample titles; they account for 47 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

+ 7 more — browse all 47 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.