This project is an international collaboration involving researchers in the U.S. and Brazil and is funded by the National Science Foundation and FAPESP. In addition to the Rokyta Lab, the collaborators include Dr. Lisle Gibbs at Ohio State University, Dr. Christopher Parkinson at the University of Central Florida, Drs. Inácio de Loiola Meirelles Junqueira de Azevedo, Ana Maria Moura da Silva, and Erika Hingst-Zaher at the Instituto Butantan, and Dr. Hassam Zaher at the University of São Paulo. Understanding rapid diversification within evolutionary lineages requires determination of the factors and traits that promoted that diversification. Key innovations can lead to adaptive radiations by rendering new areas of ecological niche space accessible to a lineage and its descendents. The advanced snakes (superfamily Colubroidea) are comprised of more than 2,500 species, account for the majority of extant snake species, and represent one of the most diverse groups of terrestrial vertebrates. This superfamily originated approximately 100 million years ago and includes the front-fanged venomous families Viperidae and Elapidae and a diverse array of rear-fanged venomous species in the family Colubridae. Venom is hypothesized to have been the innovation initiating this radiation by expanding trophic opportunities, and subsequent toxin recruitment and toxin-gene neofunctionalization may have secondarily promoted further diversification. Venom and its coevolutionary interactions with prey provide strong selective pressures necessary to drive rapid evolution as well as natural mechanisms to generate extrinsic pre- and postzygotic isolation through reduced immigrant and hybrid fitnesses. Our goals for this project include determining how secondary key innovations within the venom system contributed to diversification patterns in the advanced snakes and testing for biases in the genetic pathways underlying rapid phenotypic evolution in venoms between closely related species as a means for understanding the process of diversification. An overview of our sampling strategy can be found here.

Viral Experimental Evolution

This project is currently funded by the National Institute of General Medical Sciences (NIGMS) at the National Institutes of Health (NIH) and is a collaboration with Dr. Wei Yang in the Department of Chemistry at Florida State University. The goals of this research include testing theoretical predictions about pleiotropy, epistasis, and adaptation in bacteriophages (i.e., viruses that infect bacteria) and identifying the mechanistic bases for these phenomena. The bacteriophages we use are all in the family Microviridae, have small genomes encoding only 11 proteins, and have generation times of approximately 12 minutes under standard laboratory conditions. These short generation times allow us to observe adaptive evolutionary changes in hours or days by applying defined selective pressures to laboratory populations. We use a unique protocol involving rapidly fluctuating selective pressures to induce a two-component fitness based on growth rate and capsid stability. The selection protocol, inspired by the population dynamics experienced by many pathogens, consists of periods of growth within hosts punctuated by strong selection for survival in the absence of hosts. Growth is allowed under normal culturing conditions, but survival selection involves extreme heat or pH, which selects for capsid stability, a simple yet fundamental biophysical property. We are using this protocol to study the pleiotropic effects of beneficial mutations in terms of a reaction rate and protein stability and to determine how this conflict, and pleiotropy in general, affects the genetic variation available for adaptation. By engineering identified beneficial mutations into new genetic contexts, we are measuring the extent to which biophysical properties of mutations are additive across backgrounds. By allowing long-term adaptation, we are determining whether deleterious pleiotropic effects can be overcome through compensatory evolution so that the two traits can be simultaneously maximized. We are also using molecular-dynamics simulation to determine the biophysical bases for the beneficial and epistatic effects of identified mutations.