Towards a mathematical theory of development

Lecture | January 16 | 10 a.m.-12 p.m. | 4500 Berkeley Way West

 Geoffrey Schiebinger PhD

 Public Health, School of

In this talk we introduce a mathematical model to describe temporal processes like embryonic
development and cellular reprogramming. We consider stochastic processes in gene expression
space to represent developing populations of cells, and we use optimal transport to recover
the temporal couplings of the process. We apply these ideas to study 315,000 single-cell RNA-sequencing profiles collected at 40 time points over 18 days of reprogramming fibroblasts into
induced pluripotent stem cells. To validate the optimal transport model, we demonstrate that
it can accurately predict developmental states at held-out time points. We construct a high-resolution map of reprogramming that rediscovers known features; uncovers new alternative
cell fates including neural- and placental-like cells; predicts the origin and fate of any cell class;
and implicates regulatory models in particular trajectories. Of these findings, we highlight the
transcription factor Obox6 and the paracrine signaling factor GDF9, which we experimentally
show enhance reprogramming efficiency. Our approach provides a general framework for
investigating cellular differentiation, and poses some interesting questions in theoretical

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