A dynamical systems treatment of transcriptomic trajectories
Abstract: Inspired by Waddington’s illustration of an epigenetic landscape, cell-fate transitions have been envisioned as bifurcating dynamical systems. Single-cell RNA sequencing (scRNA-seq) is making it possible to interrogate cell fate-transitions at whole-genome scales with molecular-scale precision. However, it remains unclear how to bridge the disparate scales of the dynamics of whole transcriptomes to the molecules that define the collective fate-transitions. We bridge these scales by showing that bifurcations in transcriptional states can be analytically pinpointed and their genetic bases revealed, directly from data. We demonstrate the power of our conceptual framework and analytical scheme in the context of a recent scRNA-seq based investigation of hematopoietic stem cells to neutrophils. Our work provides a rigorous and “model-independent” mathematical framework for detecting and categorizing transitions in cell-fate directly from sequencing data.
Biosketch: Sidhartha Goyal got his PhD in Physics at Princeton in 2009 and then moved to KITP, UC Santa Barbara for a postdoc. He got his first degree in Electrical Engineering from IIT Bombay. Since 2014, he is a faculty in the Physics Department at University of Toronto.