GEO series

BBSome-dependent ciliary Hedgehog signaling governs cell fate in the white adipose tissue (RNA-Seq)

GSE254255 Mus musculus (mouse) Single-cell RNA-seq 18 samples Submitted 2025/06/24 Platform GPL24247

At a glance

Single-cell RNA-seq · mouse · 18 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. 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: 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.
Paper: BBS8-dependent ciliary Hedgehog signaling governs cell fate in the white adipose tissueThe EMBO journal · 2025

Summary (written by the submitters)

The primary cilium has emerged as critical in regulating whole-body energy metabolism, as reflected in the Bardet-Biedl syndrome (BBS) where primary cilia dysfunction leads to obesity due to hyperphagia and white adipose tissue (WAT) remodeling. The regulation of cell fate and differentiation of adipocyte precursor cells (APCs) is key to maintaining WAT homeostasis during obesity.

Read the full summary ↓

Using mice that recapitulated the BBS patient phenotype (Bbs8-/-), we demonstrate that primary cilia dysfunction reduces the stem-cell-like P1 APC subpopulation by inducing a phenotypic switch into a fibrogenic progenitor state, characterized by extracellular matrix (ECM) remodeling and upregulation of CD9. Single-cell RNA sequencing revealed a direct transition of stem-cell-like P1 cells into fibrogenic progenitors, bypassing the committed P2 cells. Ectopic ciliary Hedgehog signaling upon loss of BBS8 emerged as a central driver of the molecular changes in Bbs8-/- APCs, altering differentiation into adipocytes and lipid uptake. These findings unravel a novel role for primary cilia in governing APC fate, determining the delicate balance between adipogenesis and fibrogenesis. The identified molecular mechanisms provide insights into potential therapeutic targets for obesity.

Published in

BBS8-dependent ciliary Hedgehog signaling governs cell fate in the white adipose tissue

Sieckmann K, Winnerling N, Silva Ribeiro DJ et al. · The EMBO journal 2025 · PMID 40836034 · doi:10.1038/s44318-025-00524-y

This dataset

Open GSE254255 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 GSE254255_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 PRJNA1069088 and SRA study SRP485980. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40836034) ↗

Study design

6 conditions, mostly in triplicate

Bbs8 KO iWAT, APC P1, n ×3 Bbs8 KO iWAT, APC P2, n ×3 Bbs8 KO iWAT, APC P3, n ×3 Bbs8 WT iWAT, APC P1, n ×3 Bbs8 WT iWAT, APC P2, n ×3 Bbs8 WT iWAT, APC P3, n ×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

GSM8036811 Bbs8 KO iWAT, APC P1, n1 Bbs8 KO iWAT, APC P1, n
GSM8036812 Bbs8 KO iWAT, APC P2, n1 Bbs8 KO iWAT, APC P2, n
GSM8036813 Bbs8 KO iWAT, APC P3, n1 Bbs8 KO iWAT, APC P3, n
GSM8036814 Bbs8 WT iWAT, APC P1, n1 Bbs8 WT iWAT, APC P1, n
GSM8036815 Bbs8 WT iWAT, APC P2, n1 Bbs8 WT iWAT, APC P2, n
GSM8036816 Bbs8 WT iWAT, APC P3, n1 Bbs8 WT iWAT, APC P3, n
GSM8036817 Bbs8 WT iWAT, APC P1, n2 Bbs8 WT iWAT, APC P1, n
GSM8036818 Bbs8 WT iWAT, APC P2, n2 Bbs8 WT iWAT, APC P2, n
GSM8036819 Bbs8 WT iWAT, APC P3, n2 Bbs8 WT iWAT, APC P3, n
GSM8036820 Bbs8 KO iWAT, APC P1, n2 Bbs8 KO iWAT, APC P1, n
GSM8036821 Bbs8 KO iWAT, APC P2, n2 Bbs8 KO iWAT, APC P2, n
GSM8036822 Bbs8 KO iWAT, APC P3, n2 Bbs8 KO iWAT, APC P3, n
GSM8036823 Bbs8 KO iWAT, APC P1, n3 Bbs8 KO iWAT, APC P1, n
GSM8036824 Bbs8 KO iWAT, APC P2, n3 Bbs8 KO iWAT, APC P2, n
GSM8036825 Bbs8 KO iWAT, APC P3, n3 Bbs8 KO iWAT, APC P3, n
GSM8036826 Bbs8 WT iWAT, APC P1, n3 Bbs8 WT iWAT, APC P1, n
GSM8036827 Bbs8 WT iWAT, APC P2, n3 Bbs8 WT iWAT, APC P2, n
GSM8036828 Bbs8 WT iWAT, APC P3, n3 Bbs8 WT iWAT, APC P3, n

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