Dynamics of unconditionally deleterious mutations: Gaussian approximation and soft selection

Area of Science:

• Population Genetics
• Evolutionary Biology
• Quantitative Genetics

Background:

• Deleterious mutations accumulate in populations.
• Selection acts to remove these mutations.
• Understanding mutation-selection balance is key to evolutionary stability.

Purpose of the Study:

• To investigate the interplay between deleterious mutations and directional selection.
• To model the population distribution of mutations under soft selection.
• To determine conditions for tolerable mutation load and stable equilibrium.

Main Methods:

• Developed a mathematical model for an amphimictic population.
• Assumed rare, equally deleterious mutations.
• Utilized soft selection, where fitness depends on deviation from the population mean.
• Derived equations for mean (M) and variance (V) of mutations across generations.

Main Results:

• Identified a unique and stable equilibrium for M and V.
• Equilibrium selection coefficient (s) against mutant alleles derived.
• Established a condition for tolerable mutation load: genome degradation rate (v) < 2.
• Mutation-selection balance is near-Gaussian under soft selection.

Conclusions:

• Soft selection leads to a stable mutation-selection equilibrium.
• Population health depends on the rate of genome degradation.
• The model provides insights into the evolutionary maintenance of genetic variation.