Plant-Microbe Interactions is a required course in the Plant Pathology core curriculum that is offered every Spring and is co-taught with Dr. Gary Payne. My section of the course covers the following topics: 1) introduction to population genetics concepts; 2) phylodynamics of pathogen evolution; 3) population biology and disease management; 4) inoculum source and evolutionary potential; 5) durable resistance; 6) host-pathogen coevolution; and 7) quorum-sensing systems in bacteria. Applied Evolutionary and Population Genetic Data Analysis is an advanced graduate course taught in the Fall of alternate years. This course introduces students to nonparametric and model-based methods for inferences on population processes (mutation, migration, drift, recombination, and selection). The goal is to provide a theoretical and conceptual overview of these methods as well as hands-on training on implementation and biological interpretation of results. Sample data sets in computer laboratories will integrate summary statistic, cladistic, coalescent, and Bayesian approaches to examine population processes in different pathosystems with specific emphasis on eukaryotic microbes, viruses and bacteria.

My research interests are in evolutionary biology, molecular population genetics and genomics. Research in my laboratory is interdisciplinary and combines sampling of genetic and phenotypic variation in natural fungal populations, in silico comparative analyses of fungal genomes, and the development of integrative evolutionary analysis tools. An important aspect of our work is developing new methodologies and tools to examine the influence of mutation, recombination, gene flow, selection and demography on the evolution of fungal genomes, populations and species. Our computational goal is to effectively manage and integrate the plethora of new approaches for making inferences on population processes from DNA sequence variation, bringing together simple summary-statistics, nonparametric methods and complex parameter-rich models. We have been developing new methodologies and tools for integrating genetic and phenotypic data within an evolutionary framework. Recently we released a flexible and scalable workbench tool that manages a series of population genetic programs. A major focus is examining the evolution of fungal secondary metabolism, specifically the sterigmatocystin (ST), O-methylsterigmatocystin (OMST) and aflatoxin (AF) biosynthetic pathway in Aspergillus. The genes for ST, OMST, and AF are clustered and these compounds are synthesized as end products by numerous ascomycetes. Although all three metabolites (ST, OMST, and AF) are potent carcinogens in animals, the biological and evolutionary significance of these bioreactive compounds in fungi is unknown. We are combining inferences from macro- and micro-evolutionary analyses to understand the conservation of these metabolites among Aspergillus species and how diversity is generated and maintained within species over long periods of time. Recent work examines genetic variation in experimental populations and in field studies using biological control strains.