What population structures maximize evolutionary fitness?

Harmful mutations affect long-term evolutionary dynamics

Scientists at the Max Planck Institute in Plön have shown that population structures that increase the effect of selection do not necessarily lead to increased fitness. Instead, discouraging adverse mutations from taking hold is critical to maximizing fitness.

The update mechanism of continuously mutating Moran Bd is shown in a small graph.  An individual is first selected to reproduce with a probability proportional to its fitness.  The offspring mutate with probability μ, and their fitness f' is drawn from a distribution ρ(f',f), where f is the fitness of the parent.  Then a neighboring individual from the neighboring nodes is randomly chosen to die, and the offspring are placed on the empty node.

Evolutionary graph theory, a branch of theoretical biology, examines how population structure can affect the probability of a mutant taking over (“fixing”) a population and how long it typically takes. In the past, it was always considered the case of a single mutated individual. However, in continuously evolving systems, new mutations constantly appear. Usually, however, these occur nowhere, but increasingly where individuals breed. In the long run, such models assume an equilibrium state in which the average fitness no longer changes.

Intuitively, it has been assumed that selection enhancers increase the average fitness of the population in this equilibrium and suppressors of selection decrease the average fitness of the population in this equilibrium. However, Nikhil Sharma and Arne Traulsen from the Department of Evolutionary Theory at the Max Planck Institute for Evolutionary Biology in Plön were able to show that another group of graphs, the so-called fixation suppressors, can achieve the highest mean fitness of the population. The main reason for this is its ability to prevent harmful mutants from fixing themselves. “This highlights the importance of deleterious mutants in long-term evolutionary dynamics, which has been overlooked in the literature,” says Nikhil Sharma.

The influence of spatial structure

Spatial structure can significantly affect evolutionary dynamics. But traditionally regular population structures were considered, which have no influence on fixation probabilities. In recent years, however, it has been found that nonregular structures can have very complex influences on probabilities and fixation times. These dynamics are usually studied in terms of the fixation process of a single mutation at a randomly chosen site, allowing the classification of structures that enhance the effect of selection.

The new model shows that the fixation process of individual mutations in long-term evolutionary dynamics is characterized by a balance between mutation, selection and random processes. The goal of such abstract models is to understand the role of population structure in evolutionary processes. In theory, biotechnology could exploit such structures to make systems resistant to mutations or to selectively select for advantageous mutations.


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