Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, United States; Laboratoire Matière et Systèmes Complexes, CNRS UMR 7057, Université Paris Diderot, Paris, France
Andrea Hodgins-Davis
Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, United States
Brian PH Metzger
Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, United States; Department of Ecology and Evolution, University of Chicago, Chicago, United States
Bing Yang
Department of Molecular, Cellular and Developmental Biology, University of Michigan, Ann Arbor, United States
Stephen Tryban
Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, United States
Elizabeth A Walker
Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, United States
Tricia Lybrook
Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, United States
Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, United States; Department of Molecular, Cellular and Developmental Biology, University of Michigan, Ann Arbor, United States
Gene expression noise is an evolvable property of biological systems that describes differences in expression among genetically identical cells in the same environment. Prior work has shown that expression noise is heritable and can be shaped by selection, but the impact of variation in expression noise on organismal fitness has proven difficult to measure. Here, we quantify the fitness effects of altering expression noise for the TDH3 gene in Saccharomyces cerevisiae. We show that increases in expression noise can be deleterious or beneficial depending on the difference between the average expression level of a genotype and the expression level maximizing fitness. We also show that a simple model relating single-cell expression levels to population growth produces patterns consistent with our empirical data. We use this model to explore a broad range of average expression levels and expression noise, providing additional insight into the fitness effects of variation in expression noise.
