title: On the (un)predictability of a large intragenic fitness landscape.
abstract: The study of fitness landscapes, which aims at mapping genotypes to fitness, is receiving ever-increasing attention. Novel experimental approaches combined with next-generation sequencing (NGS) methods enable accurate and extensive studies of the fitness effects of mutations, allowing us to test theoretical predictions and improve our understanding of the shape of the true underlying fitness landscape and its implications for the predictability and repeatability of evolution. Here, we present a uniquely large multiallelic fitness landscape comprising 640 engineered mutants that represent all possible combinations of 13 amino acid-changing mutations at 6 sites in the heat-shock protein Hsp90 in Saccharomyces cerevisiae under elevated salinity. Despite a prevalent pattern of negative epistasis in the landscape, we find that the global fitness peak is reached via four positively epistatic mutations. Combining traditional and extending recently proposed theoretical and statistical approaches, we quantify features of the global multiallelic fitness landscape. Using subsets of the data, we demonstrate that extrapolation beyond a known part of the landscape is difficult owing to both local ruggedness and amino acid-specific epistatic hotspots and that inference is additionally confounded by the nonrandom choice of mutations for experimental fitness landscapes.
authors.affiliation: Instituto Gulbenkian de Ciência, 2780-156 Oeiras, Portugal.|School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland.|Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland.
authors.forename: Claudia
authors.identifier: 0000-0003-4730-758X
authors.initials: C
authors.lastname: Bank
authors.affiliation: School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland.|Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland.
authors.forename: Sebastian
authors.identifier: 0000-0002-4393-9283
authors.initials: S
authors.lastname: Matuszewski
authors.affiliation: Eli Lilly and Company, Indianapolis, IN 46225.|Department of Biochemistry & Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA 01605.
authors.forename: Ryan T
authors.initials: RT
authors.lastname: Hietpas
authors.affiliation: School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland; jeffrey.d.jensen@asu.edu.|Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland.
authors.forename: Jeffrey D
authors.initials: JD
authors.lastname: Jensen
mesh_terms: D000220:Adaptation, Biological; D005075:Biological Evolution; D004843:Epistasis, Genetic; D056084:Genetic Fitness; D018841:HSP90 Heat-Shock Proteins / Q000235:genetics*; D020125:Mutation, Missense; D012441:Saccharomyces cerevisiae / Q000235:genetics*; D029701:Saccharomyces cerevisiae Proteins / Q000235:genetics*; D054712:Salinity
chemical_list: C074510:HSP82 protein, S cerevisiae; D018841:HSP90 Heat-Shock Proteins; D029701:Saccharomyces cerevisiae Proteins
keywords: adaptation; epistasis; evolution; fitness landscape; mutagenesis