Our laboratory researches the adaptive value of genomic variation in microbial populations and the ecological mechanisms that maintain and spread adaptive variants in nature. Microbial genomes diversify rapidly due to a combination of fast mutation rates, infrequent homologous recombination and acquisition of accessory genes through horizontal gene transfer. Natural selection is thought to prune away unfit lineages with near equal speed, but successful genomic variants may expand the niche dimension of the species. With advances in geographic information systems (GIS) as a framework for describing the world, scientists are more capable of linking data on genomes to patterns and processes in the environment than ever before. However, scientists haven’t yet deciphered the extent to which large scale patterns and processes, including patterns of land-management or climate, play a role in the distribution of genomic variation within the tiniest of species.

We seek to understand adaptive variation in microbial populations using genome-wide association studies that integrate two approaches. First, a new analytical framework has been proposed to link adaptive genomic variation with quantitative landscape characteristics. Landscape genomics combines GIS modeling, population genomics, and spatial analysis to yield quantitative insights into large-scale processes that generate and maintain adaptive variation in species. Second, a reverse ecology approach seeks to use genomic information as a model-generating tool to discover the phenotypic and genomic basis for adaptive divergence of microbial populations.

Environmental Science, Natural Resources Conservation, Agriculture, Veterinary Medicine, Veterinary Microbiology, Bioinformatics, Microbiology
PhD, Michigan State University, Microbiology and Molecular Genetics, 2007
environmental modeling landscape genomics food safety infectious diseases foodborne diseases microbial ecology