Abstract
A central question of evolutionary dynamics on graphs is whether or not a mutation introduced in a population of residents survives and eventually even spreads to the whole population, or becomes extinct. The outcome naturally depends on the fitness of the mutant and the rules by which mutants and residents may propagate on the network, but arguably the most determining factor is the network structure. Some structured networks are transient amplifiers. They increase for a certain fitness range the fixation probability of beneficial mutations as compared to a well-mixed population. We study a perturbation method for identifying transient amplifiers for death–birth updating. The method involves calculating the coalescence times of random walks on graphs and finding the vertex with the largest remeeting time. If the graph is perturbed by removing an edge from this vertex, there is a certain likelihood that the resulting perturbed graph is a transient amplifier. We test all pairwise nonisomorphic regular graphs up to a certain order and thus cover the whole structural range expressible by these graphs. For cubic and quartic regular graphs we find a sufficiently large number of transient amplifiers. For these networks we carry out a spectral analysis and show that the graphs from which transient amplifiers can be constructed share certain structural properties. Identifying spectral and structural properties may promote finding and designing such networks.
Highlights
An important measure for the success of an initially rare mutant among a resident population on an evolutionary graph is the fixation probability of the mutation
As we are interested in how population structure relates to evolutionary dynamics, it would be most desirable to study differences in the graph structure among the realizations of random graphs
The results show that certain evolutionary graphs may have interesting and desirable properties which are rare with respect to the total number of structurally different graphs from a certain class of graphs
Summary
An important measure for the success of an initially rare mutant among a resident population on an evolutionary graph is the fixation probability of the mutation. The evolutionary dynamics associated with the mutant’s spread most likely depends on its fitness, with a beneficial mutant possessing a higher fitness than the resident individuals, while a deleterious mutant has a lower fitness. Compared to a well-mixed population, some graphs produce a higher fixation probability for a beneficial mutant, amplifying the effect of selection. For some other graphs we find the opposite with an increased fixation probability for a deleterious mutation, and suppressing selection. There are transient amplifiers characterized by an increased fixation probability for some range of the mutant’s fitness, and graphs that have multiple transitions between amplification and suppression (Alcalde Cuesta et al 2018)
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