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Multi-tissue single cell profiling of genetically diverse mouse models reveals mechanisms of resilience to obesity and diabetes [scRNA_seq_islet]

GSE272053 Mus musculus (mouse) Single-cell RNA-seq 19 samples Submitted 2024/12/31 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 19 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Samples
19 samples: 19 samples, each with a distinct title — no replicated groupsGroups 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)
Despite the importance of genetic factors to metabolic health, the cellular and molecular mechanisms mediating interindividual variation in progression along the continuum from health to type 2 diabetes mellitus (T2D) remain incompletely characterized. We studied three genetically diverse mouse strains with variable baseline metabolic physiology and distinct responses to a high fat high sugar diet.
Read the full summary ↓
To understand genetically encoded differences in cell type-specific responses to diet, we profiled two key metabolic tissues, white adipose and pancreatic islets, using single cell gene expression and chromatin accessibility. In both tissues, strain background most strongly influenced both cell composition and cell type-specific gene expression, with substantial but smaller contributions of biological sex and diet. Transcriptomics and chromatin profiling revealed considerable differences between strains in immune infiltration in both tissues. Mechanisms of adipose expansion and energy utilization differed between strains, highlighting the importance of metabolite transport (Acly, Slc25a1), catecholamine signaling (Adrb3, Gpr143), preadipocyte cell fate (Cd81), and adipocyte subsets with thermogenic capabilities (Ckb, Ucp1, PGC-1ɑ). Gene expression patterns in pancreatic beta cells were unique in the most resilient mouse strain, pointing to the importance of beta cell maturation pathways (Mafa, Ucn3), glucose metabolism (Glp1r), the unfolded protein/endoplasmic reticulum stress response (Atf6, Wfs1), and oxidative stress (Atox1) in the face of increased demand for insulin and glucolipotoxicity. Transcription of the adipokine Adipsin (Cfd) demonstrated a cross-tissue link consistent with the preservation of beta cell health in CAST mice. Finally, linking obesity and T2D GWAS effector genes to chromatin and transcriptional signals in the mouse revealed plausible cell types and states where variants mediating human disease traits likely exert their effects. Overall, this single cell atlas of key metabolic tissues provides insights into inherited variability in metabolic susceptibility and resilience and serves as a framework for utilizing diverse mice to study the progression of complex disease in a controlled, reproducible system.
This dataset
Open GSE272053 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 GSE272053_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1134770 and SRA study SRP519436. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
19 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 19 sample titles: 19 distinct titles with little repetition. 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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