Suppressors of selection

Abstract

Inspired by recent works on evolutionary graph theory, an area of growing interest in mathematical and computational biology, we present the first known examples of undirected structures acting as suppressors of selection for any fitness value $r>1$. This means that the average fixation probability of an advantageous mutant or invader individual placed at some node is strictly less than that of this individual placed in a well-mixed population. This leads the way to study more robust structures less prone to invasion, contrary to what happens with the amplifiers of selection where the fixation probability is increased on average for advantageous invader individuals. A few families of amplifiers are known, although some effort was required to prove it. Here, we use computer aided techniques to find an exact analytical expression of the fixation probability for some graphs of small order (equal to $6$, $8$ and $10$) proving that selection is effectively reduced for $r>1$. Some numerical experiments using Monte Carlo methods are also performed for larger graphs.

arXiv commentNew title, improved presentation, and further examples. Supporting Information is also included

References in corpus (4)

• Most undirected random graphs are amplifiers of selection for Birth-death dynamics, but suppressors of selection for death-Birth dynamics
• The duality of spatial death-birth and birth-death processes and limitations of the isothermal theorem
• Suppressors of selection
• Fast and asymptotic computation of the fixation probability for Moran processes on graphs

Cited by in corpus (8)

• Fixation probabilities in evolutionary dynamics under weak selection
• Transient amplifiers of selection and reducers of fixation for death-Birth updating on graphs
• Suppressors of selection
• Fixation dynamics on hypergraphs
• Fixation probability in evolutionary dynamics on switching temporal networks
• Fixation dynamics on multilayer networks
• Constant-selection evolutionary dynamics on weighted networks
• Exploring and mapping the universe of evolutionary graphs