Narrow Results

Penna's bit-string model of biological ageing due to the accumulation of deleterious mutations is generalized to allow for more than one disease per year. The results remain qualitatively unchanged except for a more complicated non-monotonic approach to equilibrium. We also look at "mutational meltdown", the extinction of the whole population if all mutations are deleterious and heritable, and why the Penna model can escape this extinction. No dependence on population size is found for mutational meltdown, with up to 10⁸ individuals.

In this work the Eigen model of quasispecies is reconsidered. Our main aim is to find to what extent mutational meltdown changes previously presented results, when the finite population can decrease or increase during evolution.

In this paper we consider a microscopic model of a simple ecosystem. The basic ingredients of this model are individuals, and both the phenotypic and genotypic levels are taken in account. The model is based on a long range cellular automaton (CA); introducing simple interactions between the individuals, we get some of the complex collective behaviors observed in a real ecosystem. Since our fitness function is smooth, the model does not exhibit the error threshold transition; on the other hand the size of total population is not kept constant, and the mutational meltdown transition is present. We study the effects of competition between genetically similar individuals and how it can lead to species formation. This speciation transition does not depend on the mutation rate. We present also an analytical approximation of the model.

We introduce a toy model for interacting populations connected by mutations and limited by a shared resource. We study the presence of Eigen's error threshold and mutational meltdown. The phase diagram of the system shows that the extinction of the whole population due to mutational meltdown can occur well before an eventual error threshold transition.

The process of deleterious mutation accumulation is influenced by numerous biological factors, including the way in which the accumulating mutations interact with one another. The phenomenon of negative mutation-to-mutation interactions is known as synergistic epistasis (SE). It is widely believed that SE should enhance selective elimination of mutations and thereby diminish the problem of genetic degeneration. We apply numerical simulation to test this commonly expressed assertion.

We find that under biologically realistic conditions, synergistic epistasis exerts little to no discernible influence on mutation accumulation and genetic degeneration. When the synergistic effect is greatly exaggerated, mutation accumulation is not significantly affected, but genetic degeneration accelerates markedly. As the synergistic effect is exaggerated still more, degeneration becomes catastrophic and leads to rapid extinction. Even when conditions are optimized to enhance the SE effect, selection efficiency against deleterious mutation accumulation is not appreciably influenced.

We also evaluated SE using parameters that result in extreme and artificially high selection efficiency (truncation selection and perfect genotypic fitness heritability). Even under these conditions, synergistic epistasis causes accelerated degeneration and only minor reductions in the rate of mutation accumulation.

When we included the effect of linkage within chromosomal segments in our SE analyses, it made degeneration still worse and even interfered with mutation elimination. Our results therefore strongly suggest that commonly held perceptions concerning the role of synergistic epistasis in halting mutation accumulation are not correct.