bioRxivBioinformaticsPreprint
Evaluation of a scalable approach to generate cell-type specific transcriptomic profiles of mesenchymal lineage cells
Luke J DillardiD, Will T. RosenowiD, Gina M. CalabreseiD, Larry D. Mesner, Basel Maher Al-BarghouthiiD, Abdullah AboodiD, Emily FarberiD, Suna Önengüt-GümüşcüiD, Steven M. TommasiniiD, Mark A Horowitz, Clifford james RoseniD, Lutian YaoiD, Ling QiniD, Charles R. FarberiD
Abstract
Genome-wide association studies (GWASs) have revolutionized our understanding of the genetics of complex diseases, such as osteoporosis; however, the challenge has been converting associations to causal genes. Studies have demonstrated the utility of transcriptomics data in linking disease-associated variants to genes; though for osteoporosis, few population transcriptomics datasets have been generated on bone or bone cells, and an even smaller number have profiled individual cell-types. To begin to evaluate approaches to address this challenge, we profiled the transcriptomes of bone marrow-derived stromal cells (BMSCs) cultured under osteogenic conditions, a popular model of osteoblast differentiation and activity, from five Diversity Outbred (DO) mice using single-cell RNA-seq (scRNA-seq). The goal of the study was to determine if BMSCs could serve as a model for the generation of cell-type specific transcriptomic profiles of mesenchymal lineage cells derived from large populations of mice to inform genetic studies. We demonstrate that dissociation of BMSCs from a heavily mineralized matrix had little effect on viability or their transcriptomic signatures. Furthermore, we show that BMSCs cultured under osteogenic conditions are diverse and consist of cells with characteristics of mesenchymal progenitors, marrow adipogenic lineage precursors (MALPs), osteoblasts, osteocyte-like cells, and immune cells. Importantly, all cells were nearly identical from a transcriptomic perspective to cells isolated directly from bone. We also demonstrated the ability to multiplex single cells and subsequently assign cells to their "mouse-of-origin" using demultiplexing approaches based on genotypes inferred from coding SNPs. We employed scRNA-seq analytical tools to confirm the biological identity of profiled cell-types. SCENIC was used to reconstruct gene regulatory networks (GRNs) and we showed that identified cell-types show GRNs expected of osteogenic and pre-adipogenic lineage cells. Further, CELLECT analysis showed that osteoblasts, osteocyte-like cells, and MALPs captured a significant component of BMD heritability. Together, these data suggest that BMSCs cultured under osteogenic conditions coupled with scRNA-seq can be used as a scalable and biologically informative model to generate cell-type specific transcriptomic profiles of mesenchymal lineage cells in large mouse, and potentially human, populations.
- organism: mouse
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: gene regulatory network inference
- research focus: differential expression
- approach: statistical model
- approach: experimental assay
- Citations
- 0
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Cell type-specific network analysis in Diversity Outbred mice identifies genes potentially responsible for human bone mineral density GWAS associations
Luke J Dillard, Gina M. Calabrese, … Charles R. Farber·eLifePeer-reviewed·Mar 11, 2026
- A framework for defining mesenchymal cell types associated with murine periosteal and endosteal bone
Intawat Nookaew, Jinhu Xiong, … Charles A. O’Brien·Journal of Biological ChemistryPeer-reviewed·Mar 11, 2024
- Single-cell RNA sequencing deconvolutes the in vivo heterogeneity of human bone marrow-derived mesenchymal stem cells
Z. Wang, X. Li, … H.-W. deng·bioRxiv·Apr 6, 2020
- Multiscale analysis and functional validation of the cellular and genetic determinants of skeletal disease
International Federation of Musculoskeletal Research Societies (IFMRS) Big Data Working Group, Ryan Chau Chia Chai, … Jennifer J. Westendorf·VU Research PortalPeer-reviewed·Jul 1, 2026
- Osteocyte Transcriptome Mapping Identifies a Molecular Landscape Controlling Skeletal Homeostasis and Susceptibility to Skeletal Disease
Scott E. Youlten, John P. Kemp, … Peter Ian Croucher·Nature CommunicationsPeer-reviewed·May 5, 2021
- Transcriptional plasticity of stromal cells amplifies their differentiation efficiency in vitro
Ali Jasim Mohammad Jamil, Mikkel Ørnfeldt Nørgård, … Alexander Rauch·Journal of Biological ChemistryPeer-reviewed·Jan 20, 2026