bioRxivBioinformaticsPreprint
A novel induced pluripotent stem cell model of schwann cell differentiation reveals NF2-related gene regulatory networks of the extracellular matrix
Olivia Lazaro, Sihong LiiD, William CarteriD, Oluwamayowa AwosikaiD, Sylvia RobertsoniD, Brooke E. HickeyiD, Steven P. AngusiD, Austin House, D. Wade ClappiD, Abdul S. QadiriD, Travis S. JohnsoniD, Steven D. RhodesiD
Abstract
Schwann cells are vital to development and maintenance of the peripheral nervous system and their dysfunction has been implicated in a range of neurological and neoplastic disorders, including NF2-related schwannomatosis. We developed a novel human induced pluripotent stem cell (hiPSC) model to study Schwann cell differentiation in health and disease. We performed transcriptomic, immunofluorescence, and morphological analysis of hiPSC derived Schwann cell precursors (SPCs) and terminally differentiated Schwann cells (SCs) representing distinct stages of development. To validate our findings, we performed integrated, cross-species analyses across multiple external datasets at bulk and single cell resolution. Our hiPSC model of Schwann cell development shared overlapping gene expression signatures with human amniotic mesenchymal stem cell (hAMSCs) derived SCs and in vivo mouse models, but also revealed unique features that may reflect species-specific aspects of Schwann cell biology. Moreover, we identified gene co-expression modules that are dynamically regulated during hiPSC to SC differentiation associated with ear and neural development, cell fate determination, the NF2 gene, and extracellular matrix (ECM) organization. By cross-referencing results between multiple datasets, we identified new genes potentially associated with NF2 expression. Our hiPSC model further provides a tractable platform for studying Schwann cell development in the context of human disease.
- organism: human
- assay: bulk RNA-seq
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- approach: benchmark study
- Citations
- 2
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