Yeast Evolutionary Genetics and Genomics

TOPICAL COLLECTIONS

Guest Editor

Jeffrey A. Lewis

University of Arkansas

Dr. Jeffrey A. Lewis joined the faculty at the Department of Biological Sciences at the University of Arkansas in 2013. He previously completed his PhD in Microbiology at the University of Wisconsin-Madison in 2007, where his research under the mentorship of Dr. Jorge Escalante-Semerena focused on the genetics and biochemistry of bacterial metabolism. He then worked on the functional and comparative genomics of stress responses as a postdoctoral fellow with Dr. Audrey Gasch. His current research program focuses on understanding how cells sense and respond to stressful environments; in particular, why some individuals are more or less susceptible to stress. His lab takes advantage of brewer’s yeast, which arguably has the most sophisticated genetic toolbox, to understand which genes and processes are required for resistance to stressors commonly encountered in nature. Because life has dealt with environmental stress since the very beginning, stress responses are ancient, and thus yeast is an ideal model for generating an integrated view of eukaryotic stress defense and physiology.

Collection Overview

The budding yeast Saccharomyces cerevisiae has long served as a model for eukaryotic genetics and cell biology, and with a relatively small genome size and the first sequenced eukaryotic genome, yeast research has played a critical role in the development of genomics and systems biology. More recently, yeast has emerged as a powerful model system for evolutionary genetics, where as a microbe, it has similar advantages as bacteria for laboratory evolution, yet as a diploid, it is amenable to high-throughput quantitative genetics. The recent sequencing of over 1,000 diverse S. cerevisiae strains leaves yeast well positioned as a model for population and ecological genetics. This collection provides the latest highlights for the “awesome power” of yeast evolutionary genetics, and while yeast have been at the forefront of tool development, we envision many of these methods being adaptable to current and emerging model organisms.