Genome heterogeneity drives the evolution of species
arXiv:1912.01444 · doi:10.1103/PhysRevResearch.2.043026
Abstract
Most of the DNA that composes a complex organism is non-coding and defined as junk. Even the coding part is composed of genes that affect the phenotype differently. Therefore, a random mutation has an effect on the specimen fitness that strongly depends on the DNA region where it occurs. Such heterogeneous composition should be linked to the evolutionary process. However, the way is still unknown. Here, we study a minimal model for the evolution of an ecosystem where two antagonist species struggle for survival on a lattice. Each specimen possesses a toy genome, encoding for its phenotype. The gene pool of populations changes in time due to the effect of random mutations on genes (entropic force) and of interactions with the environment and between individuals (natural selection). We prove that the relevance of each gene in the manifestation of the phenotype is a key feature for evolution. In the presence of a uniform gene relevance, a mutational meltdown is observed. Natural selection acts quenching the ecosystem in a non-equilibriumstate that slowly drifts, decreasing the fitness and leading to the extinction of the species. Conversely, if a specimen is provided with a heterogeneous gene relevance, natural selection wins against entropic forces, and the species evolves increasing its fitness. We finally show that heterogeneity together with spatial correlations is responsible for spontaneous sympatric speciation.
8 pages, 4 figures
References in corpus (6)
- Why highly expressed proteins evolve slowly
- Stochastic population dynamics in spatially extended predator-prey systems
- Fluctuations and Correlations in Lattice Models for Predator-Prey Interaction
- Exploration-exploitation tradeoffs dictate the optimal distributions of phenotypes for populations subject to fitness fluctuations
- Entropy evaluation sheds light on ecosystem complexity
- Complex population dynamics as a competition between multiple time-scale phenomena