GEO series

Robust single nucleus RNA sequencing reveals depot-specific cell population dynamics in adipose tissue remodeling during obesity

GSE261417 Mus musculus (mouse) Single-nucleus RNA-seq 11 samples Submitted 2024/04/01 Platform GPL19057

At a glance

Single-nucleus RNA-seq · mouse · 11 samples

What it is: Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue). Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism: Mus musculus (mouse)
Samples: 11 samples: 4 × HFD, small nuclei, vs 4 × HFD, large nuclei, vs 3 × NCD,Groups 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: Robust single nucleus RNA sequencing reveals depot-specific cell population dynamics in adipose tissue remodeling during obesitybioRxiv : the preprint server for biology · 2024

Summary (written by the submitters)

Single nucleus RNA sequencing (snRNA-seq), an alternative to single cell RNA sequencing (scRNA-seq), encounters technical challenges in obtaining high-quality nuclei and RNA, persistently hindering its applications. Here, we present a robust technique for isolating nuclei across various tissue types, remarkably enhancing snRNA-seq data quality.

Read the full summary ↓

Employing this approach, we comprehensively characterize the depot-dependent cellular dynamics of various cell types underlying adipose tissue remodeling during obesity. By integrating nuclear RNA-seq data from adipocyte nuclei of varying sizes, we identify distinct adipocyte subpopulations categorized by size and functionality. Specifically, we characterize dysfunctional hypertrophic adipocytes prevalent in visceral adipose tissues during obesity, exhibiting cellular stress, inflammation and impaired metabolic gene expression. Obesity-induced changes in gene expression profiles of adipocyte subpopulations reveal their distinct contributions to adipose tissue pathophysiology. Our study establishes a robust snRNA-seq method, providing novel insights into the mechanisms orchestrating adipose tissue remodeling during obesity, with broader applicability across diverse biological systems.

Published in

Robust single nucleus RNA sequencing reveals depot-specific cell population dynamics in adipose tissue remodeling during obesity

So J, Strobel O, Wann J et al. · bioRxiv : the preprint server for biology 2024 · PMID 38645263 · doi:10.1101/2024.04.08.588525

This dataset

Open GSE261417 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 GSE261417_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 PRJNA1086907 and SRA study SRP494766. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38645263) ↗

Study design

4 × HFD, small nuclei, vs 4 × HFD, large nuclei, vs 3 × NCD,

Supports a between-group comparison across 11 samples.

How we read this: 3 replicated groups read from 11 sample titles; they account for 11 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

GSM8143725 NCD, replicate1 NCD,
GSM8143726 NCD, replicate2 NCD,
GSM8143727 NCD, replicate3 NCD,
GSM8143728 HFD, small nuclei, replicate1 HFD, small nuclei,
GSM8143729 HFD, small nuclei, replicate2 HFD, small nuclei,
GSM8143730 HFD, small nuclei, replicate3 HFD, small nuclei,
GSM8143731 HFD, small nuclei, replicate4 HFD, small nuclei,
GSM8143732 HFD, large nuclei, replicate1 HFD, large nuclei,
GSM8143733 HFD, large nuclei, replicate2 HFD, large nuclei,
GSM8143734 HFD, large nuclei, replicate3 HFD, large nuclei,
GSM8143735 HFD, large nuclei, replicate4 HFD, large nuclei,

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