On non-random mating, adaptive evolution and information theory

Abstract

Population genetics describes evolutionary processes, focusing on the variation within and between species and the forces shaping this diversity. Evolution reflects information accumulated in genomes, enhancing organisms adaptation to their environment. In this paper, we propose a model that begins with the distribution of matings based on mutual fitness and progresses to viable adult genotype distribution. At each stage the changes result in different measures of information. The evolutionary dynamics of each stage of the model correspond to aspects such as the type of mating, the distributions of genotypes within matings, and the distribution of genotypes and haplotypes in the next generation. Changes in these distributions are caused by variation in fitness and result in Jeffreys divergence values other than zero. As an example, a model of hybrid sterility is developed at a biallelic locus, comparing the information indices associated with each stage of the evolutionary process. In conclusion, the informational perspective seems to facilitate the connection of causes and effects and allows the development of statistics to contrast null models of zero information (random mating, no selection, etc.). The informational perspective could contribute to clarify, deepen and expand the mathematical foundations of evolutionary theory. SIMPLE SUMMARYThe evolutionary process can be seen as a process of acquisition, storage, and updating of information by a population about the environment in which it lives. In this paper I propose a model that starts with the distribution of matings that occur according to mutual mating fitness and ends with the distribution of viable adult genotypes obtained after these matings. The result of the evolutionary dynamics associated with each stage of the model can be described in terms of information. This informational description facilitates the connection between causes and effects, as well as the development of statistics to test the null model of zero information, i.e. random mating and/or no effect of natural selection. Incorporating the informational perspective into the mathematical formalism of population genetics/genomics contributes to clarifying, expanding and deepening the mathematical description of evolutionary theory.