Fitness effects of altering gene expression noise in Saccharomyces cerevisiae

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 n...

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Bibliographic Details
Published in:	eLife 2018-08, Vol.7
Main Authors:	Duveau, Fabien, Hodgins-Davis, Andrea, Metzger, Brian Ph, Yang, Bing, Tryban, Stephen, Walker, Elizabeth A, Lybrook, Tricia, Wittkopp, Patricia J
Format:	Article
Language:	eng
Subjects:	Analysis Base sequence Biochemistry Cell division competitive growth DNA sequencing evolution Evolution (Biology) Evolutionary Biology Gene expression Gene Expression Regulation, Fungal - genetics Genes Genetic aspects Genetic Fitness - genetics Genetic research Genotype Genotype & phenotype Genotypes Glyceraldehyde-3-Phosphate Dehydrogenase (Phosphorylating) - genetics Natural selection Noise Population growth promoter Proteins Reproductive fitness RNA Saccharomyces cerevisiae Saccharomyces cerevisiae - genetics Saccharomyces cerevisiae Proteins - genetics selection Selection, Genetic Single-Cell Analysis Standard deviation TDH3 Transcription factors
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Summary:	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 gene in . 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.
ISSN:	2050-084X 2050-084X