1,964 research outputs found
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
Tradeoff between short-term and long-term adaptation in a changing environment
We investigate the competition dynamics of two microbial or viral strains
that live in an environment that switches periodically between two states. One
of the strains is adapted to the long-term environment, but pays a short-term
cost, while the other is adapted to the short-term environment and pays a cost
in the long term. We explore the tradeoff between these alternative strategies
in extensive numerical simulations, and present a simple analytic model that
can predict the outcome of these competitions as a function of the mutation
rate and the time scale of the environmental changes. Our model is relevant for
arboviruses, which alternate between different host species on a regular basis.Comment: 9 pages, 3 figures, PRE in pres
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
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
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