Annuaire
Kane Toh, Genomics and Data Analytics Core (GeDaC), National University of Singapore - WEBINAR
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Le 03/06/2022, de 11:00 à 12:00 |
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| S'adresser à | WEBINAR, Equipe Gandrillon |
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Contact : O. Gandrillon
The transition state model of cell differentiation proposes that a transient window of gene expression stochasticity precedes entry into a differentiated state. As this has been assessed primarily in vitro, we sought to explore whether it can also be observed in vivo. Zebrafish neuromesodermal progenitors (NMps) differentiate into spinal cord and paraxial mesoderm at the late somitogenesis stages. We observed an increase in gene expression variability at the 24 somite stage (24ss) prior to their differentiation. From our analysis of a published 18ss scRNA-seq dataset, we showed that the NMp population possesses a signature consistent with a population undergoing a critical transition. By building in silico composite gene expression maps from our image data, we were able to assign an ‘NM index’ to each in silico NMp based on the cumulative expression of its neural and mesodermal markers. With the NM index distributions, we demonstrated that cell population heterogeneity of the NMps peaked at 24ss. We then incorporated stochasticity and non-autonomy into a genetic toggle switch model and uncovered the existence of rebellious cells, which we then confirmed by reexamining the composite maps. Taken together, our work supports the transition state model within an endogenous cell fate decision making event.
Preprint: https://www.biorxiv.org/content/10.1101/2022.02.25.481986v1