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Proc Natl Acad Sci U S A. 2016 Dec 6;113(49):14085-14090. Epub 2016 Nov 18.

On the (un)predictability of a large intragenic fitness landscape.

Author information

1
Instituto Gulbenkian de Ciência, 2780-156 Oeiras, Portugal.
2
School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland.
3
Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland.
4
Eli Lilly and Company, Indianapolis, IN 46225.
5
Department of Biochemistry & Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA 01605.
6
School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland; jeffrey.d.jensen@asu.edu.

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.

KEYWORDS:

adaptation; epistasis; evolution; fitness landscape; mutagenesis

PMID:
27864516
PMCID:
PMC5150413
DOI:
10.1073/pnas.1612676113
[Indexed for MEDLINE]
Free PMC Article

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