ArticleProceedings of the National Academy of Sciences of the United States of America2016
On the (un)predictability of a large intragenic fitness landscape.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers.
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65 citing papers in PubMed.
- Synthetic Approaches as Empirical Tools for Testing Evolutionary Theory.Genome biology and evolution · 2026Review
- The adaptive landscapes of three globaleLife · 2026Article
- Inference of fitness landscapes with heterogeneous patterns of epistasis across sites.bioRxiv : the preprint server for biology · 2026Article
- Origins and breadth of pairwise epistasis in an α-helix of β-lactamase TEM-1.Nature communications · 2026Article
- Inference and Visualization of Complex Genotype-Phenotype Maps.Molecular biology and evolution · 2026Article
- A gene-based model of fitness and its implications for genetic variation: linkage disequilibrium.Genetics · 2025Article
- Inference and visualization of complex genotype-phenotype maps withbioRxiv : the preprint server for biology · 2025Article
- Learning sequence-function relationships with scalable, interpretable Gaussian processes.bioRxiv : the preprint server for biology · 2025Article
- A gene-based model of fitness and its implications for genetic variation: Linkage disequilibrium.bioRxiv : the preprint server for biology · 2025Article
- Importance of higher-order epistasis in protein sequence-function relationships.bioRxiv : the preprint server for biology · 2025Article
- Robustness of Ancestral Sequence Reconstruction to Among-site and Among-lineage Evolutionary Heterogeneity.Molecular biology and evolution · 2025Article
- Epistatic hotspots organize antibody fitness landscape and boost evolvability.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Gauge fixing for sequence-function relationships.PLoS computational biology · 2025Article
- Saturated Transposon Analysis in Yeast as a one-step method to quantify the fitness effects of gene disruptions on a genome-wide scale.PloS one · 2025Article
- The highly rugged yet navigable regulatory landscape of the bacterial transcription factor TetR.Nature communications · 2024Article
- Environment-independent distribution of mutational effects emerges from microscopic epistasis.Science (New York, N.Y.) · 2024Article
- Environment-independent distribution of mutational effects emerges from microscopic epistasis.bioRxiv : the preprint server for biology · 2024Article
- Gauge fixing for sequence-function relationships.bioRxiv : the preprint server for biology · 2024Article
- Unpredictability of the Fitness Effects of Antimicrobial Resistance Mutations Across Environments in Escherichia coli.Molecular biology and evolution · 2024Article
- Evolutionary "Crowdsourcing": Alignment of Fitness Landscapes Allows for Cross-species Adaptation of a Horizontally Transferred Gene.Molecular biology and evolution · 2023Article
5 more citing papers are in PubMed but not listed here.
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4 authors.
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No grant is acknowledged in the PubMed record.
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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.