bioRxivDevelopmental BiologyPreprint
Development in context: interferon response networks regulate human fetal thymic epithelial cell differentiation
Abdulvasey MohammediD, Benjamin D. SolomoniD, Priscila Ferreira SlepickaiD, Kelsea M. HubkaiD, Hanh Dan NguyeniD, Wenqing WangiD, Martin ArreolaiD, Michael ChaveziD, Christine Y. YehiD, Doo Kyung KimiD, Virginia D. WinniD, Casey A. GiffordiD, Veronika R. KedlianiD, Jong-Eun ParkiD, Georg A. HolländeriD, Vittorio SebastianoiD, Purvesh KhatriiD, Sarah Amalia TeichmanniD, Andrew J. GentlesiD, Katja Gabriele WeinachtiD
- Citations
- 1
Abstract
The thymus instructs T cell immunity and central tolerance, yet its therapeutic potential remains untapped. The quest to regenerate thymic function for clinical application is lagging while the signals that drive thymic epithelial cell differentiation remain incompletely understood. Here, we elucidate pathways instructing commitment and specialization of the human thymic epithelial stroma through complementary single cell transcriptomic approaches. First, we identify gene regulatory networks that define fetal thymic epithelium in the thus far unexplored context of other anterior foregut-derived organs; then, we characterize lineage trajectories within the thymic epithelial compartment across embryonic, fetal, and early postnatal stages. Activation of interferon response gene regulatory networks distinguished epithelial cells of the thymus from those of all other anterior foregut-derived organs. Interferon signals were processed differentially within thymic cortical and medullary lineages, reflected in distinct NF{kappa}B and IRF signatures, respectively. Our study reveals novel, translatable insights into the developmental programs underlying thymic epithelial cell differentiation that may advance the field of regenerative cell therapies. SUMMARYSingle cell transcriptomics of anterior foregut-derived organs identifies pathways governing thymic epithelial commitment and specialization.
- organism: human
- assay: scRNA-seq
- research focus: clustering
- research focus: trajectory inference
- research focus: gene regulatory network inference
- approach: statistical model
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