Understanding how gene regulatory networks (GRNs) orchestrate key developmental events such as tissue patterning, cell division and fate specification, is a major outstanding question in biology. GRNs are traditionally represented as static models comprised of edges and nodes. However, these models fail to capture the dynamic flow of information through the network that ultimately determines its developmental output. Mathematical modeling offers the potential for describing network dynamics. However, models require parameterization for which experimental data is often missing. Recent developments in the field of imaging have provided the tools to enable the observation of network dynamics in living organisms and the experimental determination of important parameters necessary for modeling their behavior. In Arabidopsis roots, a small network of genes regulated by the transcription factors SHORT-ROOT (SHR) and SCARECROW (SCR) controls the formative division of the immediate progeny of the ground tissue stem cells. These divisions are asymmetric, in that the daughter cells go on to produce distinct cell lineages, the cortex and endodermis. Over 20 years of genetic research have elucidated the topology of this network, yet little is known about how network components act together dynamically to effect cell division and fate specification. Here, I propose to use leading edge imaging techniques to experimentally determine important kinetic parameters of the SHR-SCR network and use these to model its function. Specifically, I will use two-photon light sheet microscopy to measure in real-time the timing and levels of changes in protein expression of network components as cells divide in wild-type plants and in response to SHR induction (Aim 1). I will then determine the specific SHR-SCR complexes formed in their cellular context both before and after cell division using a new technique from the field of correlation spectroscopy called Number and Brightness (Aim 2). And finally, I will use these experimentally determined parameters and interactions to model the behavior of the SHR-SCR network (Aim 3). This work will shed light on how this network dynamically controls cell division and the specification of cell fate in the Arabidopsis root. It will also explore new methods for understanding gene network function that may be generally applicable to all organisms.

Public Health Relevance

The sequencing revolution has revealed that many human diseases cannot be linked to single genes, but instead are complex and multigenic. Thus, understanding how genes interact is critical for public health. Insights gained from understanding gene networks in Arabidopsis may be generally applicable to all organisms, including humans.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Postdoctoral Individual National Research Service Award (F32)
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Special Emphasis Panel (ZRG1-F05-D (21))
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Reddy, Michael K
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Duke University
Schools of Arts and Sciences
United States
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