An Individual-Based Diploid Model Predicts Limited Conditions Under Which Stochastic Gene Expression Becomes Advantageous

摘要: Recent studies suggest the existence of a stochasticity in gene expression (SGE) many organisms, and its non-negligible effect on their phenotype fitness. To date, however, how SGE affects key parameters population genetics are not well understood. can increase phenotypic variation act as load for individuals, if they at adaptive optimum stable environment. On other hand, part caused by might become advantageous individuals genetically less-adaptive, example due to an environmental change. Furthermore, unimportant genes have little or no fitness consequences. Thus, be advantageous, disadvantageous, selectively neutral depending context. In addition, there genetic basis that regulates magnitude SGE, which is often referred "modifier genes," but known about conditions under such SGE-modifier evolves. present study, we conducted individual-based computer simulations examine these diploid model. simulations, considered single locus determines organismal simplicity, creates stochastic manner. We also another modifies SGE. Our results suggested was always deleterious environments increased fixation probability mutations this Even frequently changing conditions, only very strong natural selection made adaptive. These evolution requires strict balance among strength selection, frequency changes. However, degree dominance affected condition becomes indicating better opportunity different models.