GEO series

Fgf9 promotes adipogenesis and reduces osteogenesis by regulating mesenchymal stromal cells differentiation in adult bone marrow

GSE252394 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2024/07/17 Platform GPL21493

At a glance

RNA-seq (gene expression) · mouse · 18 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: 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: Fgf9 regulates bone marrow mesenchymal stem cell fate and bone-fat balance in osteoporosis by PI3K/AKT/Hippo and MEK/ERK signalingInternational journal of biological sciences · 2024

Summary (written by the submitters)

In this study, we found that Fgf9 regulates the bone-fat balance by modulating the cell fate determination of BMSCs. Histology and micro-CT analysis demonstrate that Fgf9 S99N mutation (loss-of-function) significantly inhibited the formation of bone marrow adipose tissue (BMAT) in adult mice and alleviated the ovariectomized (OVX) induced bone loss and BMAT accumulation.

Read the full summary ↓

In vitro cytodifferentiation assays unveiled that the Fgf9 S99N mutation hindered adipogenesis while promoting osteogenesis in BMSCs. Furthermore, recombinant FGF9 stimulation and Fgf9 overexpression in BMSCs demonstrated that Fgf9 significantly promoted adipocyte formation and inhibited osteogenesis in vitro and in vivo. Cytodifferentiation assays at various stages of BMSC differentiation indicated that FGF9 altered the osteogenic and adipogenic potential of BMSCs, particularly during the early stages of differentiation. Transcriptomic and gene expression analyses demonstrated that FGF9 significantly upregulated the expression of adipogenic genes while downregulating osteogenic gene expression at both mRNA and protein levels. KEEG analysis revealed and in vitro differentiation assays with specific inhibitors confirmed that FGF9 modulated bone-fat balance by inhibiting osteogenesis via the MAPK/ERK pathway and promoting adipogenesis by activating the PI3K/AKT and Hippo pathways.

Published in

Fgf9 regulates bone marrow mesenchymal stem cell fate and bone-fat balance in osteoporosis by PI3K/AKT/Hippo and MEK/ERK signaling

Chen M, Liang H, Wu M et al. · International journal of biological sciences 2024 · PMID 38993574 · doi:10.7150/ijbs.94863

This dataset

Open GSE252394 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 GSE252394_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 PRJNA1060328 and SRA study SRP480981. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38993574) ↗

Study design

6 conditions, mostly in triplicate

BMSCs, CM-Control, Day4, ×3 BMSCs, CM-FGF9, Day4, ×3 BMSCs, OI-Control, Day4, ×3 BMSCs, OI-FGF9, Day4, ×3 BMSCs, AI-Control, Day4, ×3 BMSCs, AI-FGF9, Day4, ×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

GSM8000724 BMSCs, CM-Control, Day4, Rep1 BMSCs, CM-Control, Day4,
GSM8000725 BMSCs, CM-Control, Day4, Rep2 BMSCs, CM-Control, Day4,
GSM8000726 BMSCs, CM-Control, Day4, Rep3 BMSCs, CM-Control, Day4,
GSM8000727 BMSCs, CM-FGF9, Day4, Rep1 BMSCs, CM-FGF9, Day4,
GSM8000728 BMSCs, CM-FGF9, Day4, Rep2 BMSCs, CM-FGF9, Day4,
GSM8000729 BMSCs, CM-FGF9, Day4, Rep3 BMSCs, CM-FGF9, Day4,
GSM8000730 BMSCs, OI-Control, Day4, Rep1 BMSCs, OI-Control, Day4,
GSM8000731 BMSCs, OI-Control, Day4, Rep2 BMSCs, OI-Control, Day4,
GSM8000732 BMSCs, OI-Control, Day4, Rep3 BMSCs, OI-Control, Day4,
GSM8000733 BMSCs, OI-FGF9, Day4, Rep1 BMSCs, OI-FGF9, Day4,
GSM8000734 BMSCs, OI-FGF9, Day4, Rep2 BMSCs, OI-FGF9, Day4,
GSM8000735 BMSCs, OI-FGF9, Day4, Rep3 BMSCs, OI-FGF9, Day4,
GSM8000736 BMSCs, AI-Control, Day4, Rep1 BMSCs, AI-Control, Day4,
GSM8000737 BMSCs, AI-Control, Day4, Rep2 BMSCs, AI-Control, Day4,
GSM8000738 BMSCs, AI-Control, Day4, Rep3 BMSCs, AI-Control, Day4,
GSM8000739 BMSCs, AI-FGF9, Day4, Rep1 BMSCs, AI-FGF9, Day4,
GSM8000740 BMSCs, AI-FGF9, Day4, Rep2 BMSCs, AI-FGF9, Day4,
GSM8000741 BMSCs, AI-FGF9, Day4, Rep3 BMSCs, AI-FGF9, Day4,

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