Adaptive evolution on neutral networks

We study the evolution of large but finite asexual populations evolving in fitness landscapes in which all mutations are either neutral or strongly deleterious. We demonstrate that despite the absence of higher fitness genotypes, adaptation takes place as regions with more advantageous distributions of neutral genotypes are discovered. Since these discoveries are typically rare events, the population dynamics can be subdivided into separate epochs, with rapid transitions between them. Within one epoch, the average fitness in the population is approximately constant. The transitions between epochs, however, are generally accompanied by a significant increase in the average fitness. We verify our theoretical considerations with two analytically tractable bitstring models.Comment: 16 pages, 4 eps figures, Latex (academic press style file), submitted to the Bulletin of Mathematical Biolog

The Speed of Adaptation in Large Asexual Populations

In large asexual populations, beneficial mutations have to compete with each other for fixation. Here, I derive explicit analytic expressions for the rate of substitution and the mean beneficial effect of fixed mutations, under the assumptions that the population size N is large, that the mean effect of new beneficial mutations is smaller than the mean effect of new deleterious mutations, and that new beneficial mutations are exponentially distributed. As N increases, the rate of substitution approaches a constant, which is equal to the mean effect of new beneficial mutations. The mean effect of fixed mutations continues to grow logarithmically with N. The speed of adaptation, measured as the change of log fitness over time, also grows logarithmically with N for moderately large N, and it grows double-logarithmically for extremely large N. Moreover, I derive a simple formula that determines whether at given N beneficial mutations are expected to compete with each other or go to fixation independently. Finally, I verify all results with numerical simulations.Comment: 33 pages, 6 figures. Minor changes in discussion. To appear in Genetic

Avida: a software platform for research in computational evolutionary biology

Avida is a software platform for experiments with self-replicating and evolving computer programs. It provides detailed control over experimental settings and protocols, a large array of measurement tools, and sophisticated methods to analyze and post-process experimental data. We explain the general principles on which Avida is built, as well as its main components and their interactions. We also explain how experiments are set up, carried out, and analyzed

Digital evolution in time-dependent fitness landscapes

We study the response of populations of digital organisms that adapt to a time-varying (periodic) fitness landscape of two oscillating peaks. We corroborate in general predictions from quasi-species theory in dynamic landscapes, such as adaptation to the average fitness landscape at small periods (high frequency) and quasistatic adaptation at large periods (low frequency). We also observe adaptive phase shifts (time tags between a change in the fitness landscape and art adaptive change in the population) that indicate a low-pass filter effect, in agreement with existing theory,. Finally, we witness long-term adaptation to fluctuating environments not anticipated in previous theoretical work

Phenotypic mixing and hiding may contribute to memory in viral quasispecies

Background. In a number of recent experiments with food-and-mouth disease virus, a deleterious mutant, was found to avoid extinction and remain in the population for long periods of time. This observation was called quasispecies memory. The origin of quasispecies memory is not fully understood. Results. We propose and analyze a simple model of complementation between the wild type virus and a mutant that has an impaired ability of cell entry. The mutant will go extinct unless it is recreated from the wild type through mutations. However, under phenotypic mixing-and-hiding as a mechanism of complementation, the time to extinction in the absence of mutations increases with increasing multiplicity of infection (m.o.i.). The mutant's frequency at equilibrium under selection-mutation balance also increases with increasing m.o.i. At high m.o.i., a large fraction of mutant genomes are encapsidated with wild-type protein, which enables them to infect cells as efficiently as the wild type virions, and thus increases their fitness to the wild-type level. Moreover, even at low m.o.i. the equilibrium frequency of the mutant is higher than predicted by the standard quasispecies model, because a fraction of mutant virions generated from wild-type parents will also be encapsidated by wild-type protein. Conclusions. Our model predicts that phenotypic hiding will strongly influence the population dynamics of viruses, particularly at high m.o.i., and will also have important effects on the mutation--selection balance at low m.o.i. The delay in mutant extinction and increase in mutant frequencies at equilibrium may, at least in part, explain memory in quasispecies populations.Comment: 10 pages pdf, as published by BM

Evolution of Resource Competition between Mutually Dependent Digital Organisms

We study the emergence and dynamics of competing strains of digital organisms in a world with two depletable resources. Consumption of one resource produces the other resource as a by-product, and vice versa. As a consequence, two types of mutually dependent organisms emerge that each prey on the waste product of the other. In the absence of mutations, that is, in a purely ecological setting, the abundances of the two types of organisms display a wide range of different types of oscillations, from regular oscillations with large amplitude to irregular oscillations with amplitudes ranging from small to large. In this regime, time-averaged abundance levels seem to be controlled by the relative fitness of the organisms in the absence of resources. Under mutational pressure, on the other hand, populations evolve that seem to avoid the oscillations of intermediate to large amplitudes. In this case, the relative fitness of the organisms in the presence of resources plays an important role in the time-averaged abundance levels as well

Population genetics of translational robustness

Recent work has shown that expression level is the main predictor of a gene’s evolutionary rate, and that more highly expressed genes evolve slower. A possible explanation for this observation is selection for proteins which fold properly despite mistranslation, in short selection for translational robustness. Translational robustness leads to the somewhat paradoxical prediction that highly expressed genes are extremely tolerant to missense substitutions but nevertheless evolve very slowly. Here, we study a simple theoretical model of translational robustness that allows us to gain analytic insight into how this paradoxical behavior arises.Comment: 32 pages, 4 figures, Genetics in pres