Citation

Jang S, Choubey S, Furchtgott L, Zou LN, Doyle A, Menon V, Loew EB, Krostag AR, Martinez RA, Madisen L, Levi BP, Ramanathan S. 2017. Dynamics of embryonic stem cell differentiation inferred from single-cell transcriptomics show a series of transitions through discrete cell states. eLife. DOI:10.7554/eLife.20487

Abstract

The complexity of gene regulatory networks that lead multipotent cells to acquire different cell fates makes a quantitative understanding of differentiation challenging. Using a statistical framework to analyze single-cell transcriptomics data, we infer the gene expression dynamics of early mouse embryonic stem (mES) cell differentiation, uncovering discrete transitions across nine cell states. We validate the predicted transitions across discrete states using flow cytometry. Moreover, using live-cell microscopy, we show that individual cells undergo abrupt transitions from a naïve to primed pluripotent state. Using the inferred discrete cell states to build a probabilistic model for the underlying gene regulatory network, we further predict and experimentally verify that these states have unique response to perturbations, thus defining them functionally. Our study provides a framework to infer the dynamics of differentiation from single cell transcriptomics data and to build predictive models of the gene regulatory networks that drive the sequence of cell fate decisions during development. Article and supporting data available via http://europepmc.org/abstract/MED/28296635

Related Faculty

Photo of Sharad Ramanathan

Sharad Ramanathan investigates how multi-potent stem cells make fate decisions to give rise to complex human tissues, and how the dynamics of key neurons in the nervous system drive behavioral decisions.

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