30-7 Friday, Jan. 4 15:00 - 15:15 Computational Modeling of Anthocyanin Pathway Evolution WHEELER, LC*; SMITH, SD; University of Colorado-Boulder; University of Colorado-Boulder firstname.lastname@example.org https://lcwheeler.github.io/
Alteration of metabolic pathways is a key component of the evolution of new phenotypes. Flower color is a striking example of the importance of metabolic evolution in a complex phenotype, wherein shifts in the activity of the underlying pathway lead to a wide range of pigments. Although experimental work has identified common classes of mutations responsible for transitions among colors, we lack a unifying model that relates pathway function and activity to the evolution of distinct pigment phenotypes. One challenge in creating such a model is the branching structure of pigment pathways, which may lead to evolutionary trade-offs due to competition for shared substrates. In order to predict the effects of shifts in enzyme function and activity on pigment production, we created a simplified kinetic model that mirrors the structure of anthocyanin pigment pathway. This model describes the production of the three major types of blue, purple and red pigments, and accordingly, includes multiple branches and substrate competition. We studied the behavior of this model by first identifying a state-space with realistic, functional parameter combinations. We then stochastically evolved the pathway between defined optima and mapped the evolutionary trajectories onto the state space. This approach allows us to quantify the probability density of trajectories through the state space and identify constraints. Finally, we test whether the observed trajectories and constraints match with experimental observations, i.e., the predominance of mutations which change color by altering enzyme expression as opposed to function. These analyses provide a theoretical framework which can be used to predict the consequences of new mutations in terms of both pigment phenotypes and pleiotropic effects.