GEO series

PPARγ-dependent Remodeling of Translational Machinery in Adipose Progenitors is Impaired in Obesity [scRNA-seq]

GSE267192 Mus musculus (mouse) Single-cell RNA-seq 12 samples Submitted 2024/10/02 Platform GPL24247

At a glance

Single-cell RNA-seq · mouse · 12 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: 12 samples: 12 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.
Paper: PPARγ-dependent remodeling of translational machinery in adipose progenitors is impaired in obesityCell reports · 2024

Summary (written by the submitters)

Adipose tissue plays a pivotal role in energy homeostasis and metabolic regulation. However, in obesity, the remarkable adaptability of adipose tissue becomes impaired. The underlying mechanisms behind this limited adaptability remain poorly understood. In this study, we investigate a novel layer of regulation involving translation in the adipose stromal vascular fraction, examining its response to obesity and acute PPARγ agonist treatment with rosiglitazone.

Read the full summary ↓

Using single-cell RNA sequencing, we establish a transcriptional profile atlas of cellular remodeling from obese to lean-like states in inguinal and epididymal adipose tissue following rosiglitazone treatment. Notably, both stromal fractions exhibit a downregulation of inflammation-related transcripts and an upregulation of lipid-related metabolism and ribosomal transcripts. Adipocyte progenitor and preadipocyte populations display enhanced ex-vivo differentiation potential and upregulation in ribosome and peptide chain elongation pathways. This ribosomal remodeling is directly driven by PPARγ binding to gene promoters of ribosomal factors. Furthermore, we have characterized the translatome in the epididymal stromal fraction, highlighting a buffering response and fat-exclusive preferential translation after rosiglitazone treatment. Enhanced translation efficiency in rosiglitazone-elicited polysomes promotes the translation of transcripts containing G-rich sequences in their 5’ untranslated regions. Our findings shed light and provide a resource on how rosiglitazone remodels the adipose stromal vascular fraction, both dependent and independent of PPARγ. Importantly, we uncover translatome remodeling as a major new mechanism for maintaining translation homeostasis and preserving adipose tissue health in obesity.

Published in

PPARγ-dependent remodeling of translational machinery in adipose progenitors is impaired in obesity

De Siqueira MK, Li G, Zhao Y et al. · Cell reports 2024 · PMID 39579770 · doi:10.1016/j.celrep.2024.114945

This dataset

Open GSE267192 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 GSE267192_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 PRJNA1110216 and SRA study SRP506987. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39579770) ↗

Study design

12 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 12 sample titles: 12 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

GSM8262105 obob, rosi, eWAT, biological replicate 1, scRNAseq
GSM8262106 obob, rosi, eWAT, biological replicate 2, scRNAseq
GSM8262107 obob, rosi, iWAT, biological replicate 1, scRNAseq
GSM8262108 obob, rosi, iWAT, biological replicate 2, scRNAseq
GSM8262109 obob, veh, eWAT, biological replicate 1, scRNAseq
GSM8262110 obob, veh, eWAT, biological replicate 2, scRNAseq
GSM8262111 obob, veh, iWAT, biological replicate 1, scRNAseq
GSM8262112 obob, veh, iWAT, biological replicate 2, scRNAseq
GSM8262113 WT, veh, eWAT, biological replicate 1, scRNAseq
GSM8262114 WT, veh, eWAT, biological replicate 2, scRNAseq
GSM8262115 WT, veh, iWAT, biological replicate 1, scRNAseq
GSM8262116 WT, veh, iWAT, biological replicate 2, scRNAseq

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