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Journal ArticleDOI

Empirical fitness landscapes and the predictability of evolution

TLDR
This work reviews recent empirical and theoretical developments of the genotype–fitness map, identifies methodological issues and organizing principles, and discusses possibilities to develop more realistic fitness landscape models.
Abstract
A central topic in biology concerns how genotypes determine phenotypes and functions of organisms that affect their evolutionary fitness. This Review discusses recent advances in the development of empirical fitness landscapes and their contribution to theoretical analyses of the predictability of evolution. The genotype–fitness map (that is, the fitness landscape) is a key determinant of evolution, yet it has mostly been used as a superficial metaphor because we know little about its structure. This is now changing, as real fitness landscapes are being analysed by constructing genotypes with all possible combinations of small sets of mutations observed in phylogenies or in evolution experiments. In turn, these first glimpses of empirical fitness landscapes inspire theoretical analyses of the predictability of evolution. Here, we review these recent empirical and theoretical developments, identify methodological issues and organizing principles, and discuss possibilities to develop more realistic fitness landscape models.

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The Role of Epidemic Resistance Plasmids and International High-Risk Clones in the Spread of Multidrug-Resistant Enterobacteriaceae

TL;DR: Escherichia coli sequence type 131 (ST131) and Klebsiella pneumoniae ST258 emerged in the 2000s as important human pathogens, have spread extensively throughout the world, and are responsible for the rapid increase in antimicrobial resistance among E. coli and K. pneumoniae strains.
Journal ArticleDOI

Contingency and determinism in evolution: Replaying life's tape.

TL;DR: The authors' review of many such experiments indicates that responses across replicate populations are often repeatable to some degree, although divergence increases as analyses move from overall fitness to underlying phenotypes and genetic changes.
Journal ArticleDOI

Synthetic biology for the directed evolution of protein biocatalysts: navigating sequence space intelligently

TL;DR: Improving enzymes by directed evolution requires the navigation of very large search spaces; this work surveys how to do this intelligently.
References
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Journal ArticleDOI

Analysis of a complete DNA-protein affinity landscape.

TL;DR: The entire protein-binding profile of all variants of a nucleic acid oligomer 10 bases in length is presented, which has been obtained experimentally by a series of highly parallel on-chip assays and analysed statistically using a number of metrics commonly applied to synthetic landscapes.
Posted Content

Random Field Models for Fitness Landscapes

TL;DR: This paper characterize isotropic random fields on finite graphs in terms of their Fourier series expansions and investigates the relation between the covariance matrix of the random field model and the correlation structure of the individual landscapes constructed from this random field.
Journal ArticleDOI

A Mathematical Theory of Natural Selection. Part VIII. Metastable Populations

TL;DR: Gonsalez as mentioned in this paper found that, in purple-eyed Drosophila melanogaster, arc wing or axillary speck (each due to a recessive gene) shortened life but the two together lengthened it.
Journal ArticleDOI

Genotype to phenotype mapping and the fitness landscape of the E. coli lac promoter.

TL;DR: This work constructs aotype-to-phenotype map using the recently collected corpora of high-throughput sequence data from the 75 base pairs long mutagenized E. coli lac promoter region, and identifies transcription factor and RNA polymerase binding sites in the promotor region and their interactions without difficult optimization steps.
Journal ArticleDOI

Random field models for fitness landscapes

Abstract: In many cases fitness landscapes are obtained as particular instances of random fields by randomly assigning a large number of parameters. Models of this type are often characterized reasonably well by their covariance matrices. We characterize isotropic random fields on finite graphs in terms of their Fourier series expansions and investigate the relation between the covariance matrix of the random field model and the correlation structure of the individual landscapes constructed from this random field. Correlation measures are a good characteristic of “rugged landscapes” models as they are closely related to quantities like the number of local optima or the length of adaptive walks. Our formalism suggests to approximate landscape with known autocorrelation function by a random field model that has the same correlation structure.
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