Department of Biology, University of Pennsylvania, Philadelphia, 19104, USA.
Sci Rep. 2017 Jul 11;7(1):5090. doi: 10.1038/s41598-017-05214-2.
Phenotypic plasticity is an evolutionary driving force in diverse biological processes, including the adaptive immune system, the development of neoplasms, and the persistence of pathogens despite drug pressure. It is essential, therefore, to understand the evolutionary advantage of an allele that confers on cells the ability to express a range of phenotypes. Here, we study the fate of a new mutation that allows the expression of multiple phenotypic states, introduced into a finite population of individuals that can express only a single phenotype. We show that the advantage of such a mutation depends on the degree of phenotypic heritability between generations, called phenotypic memory. We analyze the fixation probability of the phenotypically plastic allele as a function of phenotypic memory, the variance of expressible phenotypes, the rate of environmental changes, and the population size. We find that the fate of a phenotypically plastic allele depends fundamentally on the environmental regime. In constant environments, plastic alleles are advantageous and their fixation probability increases with the degree of phenotypic memory. In periodically fluctuating environments, by contrast, there is an optimum phenotypic memory that maximizes the probability of the plastic allele's fixation. This same optimum memory also maximizes geometric mean fitness, in steady state. We interpret these results in the context of previous studies in an infinite-population framework. We also discuss the implications of our results for the design of therapies that can overcome persistence and, indirectly, drug resistance.
表型可塑性是多种生物学过程的进化驱动力,包括适应性免疫系统、肿瘤的发生发展以及病原体在药物压力下的持续存在。因此,理解赋予细胞表达一系列表型能力的等位基因的进化优势至关重要。在这里,我们研究了一种新突变的命运,该突变允许表达多种表型状态,这种突变被引入到只能表达单一表型的个体有限群体中。我们表明,这种突变的优势取决于代际之间表型遗传的程度,称为表型记忆。我们分析了表型可塑性等位基因的固定概率作为表型记忆、可表达表型的方差、环境变化率和种群大小的函数。我们发现,表型可塑性等位基因的命运从根本上取决于环境制度。在恒定的环境中,表型可塑性等位基因是有利的,其固定概率随着表型记忆的程度而增加。相比之下,在周期性波动的环境中,存在一个最佳的表型记忆,最大限度地提高了可塑性等位基因的固定概率。在稳态下,相同的最优记忆也最大限度地提高了几何平均适应性。我们根据无限群体框架中的先前研究来解释这些结果。我们还讨论了我们的结果对设计可以克服持久性并间接地克服耐药性的治疗方法的影响。