Department of Applied Mathematics, University of Ryerson, Toronto, Ontario, Canada M5B 2K3.
Department of Physics, University of Zanjan, Zanjan, Iran.
J R Soc Interface. 2019 Aug 30;16(157):20180781. doi: 10.1098/rsif.2018.0781. Epub 2019 Aug 14.
Understanding how environmental variability (or randomness) affects evolution is of fundamental importance for biology. The presence of temporal or spatial variability significantly affects the competition dynamics in populations, and gives rise to some counterintuitive observations. In this paper, we consider both birth-death (BD) or death-birth (DB) Moran processes, which are set up on a circular or a complete graph. We investigate spatial and temporal variability affecting division and/or death parameters. Assuming that mutant and wild-type fitness parameters are drawn from an identical distribution, we study mutant fixation probability and timing. We demonstrate that temporal and spatial types of variability possess fundamentally different properties. Under temporal randomness, in a completely mixed system, minority mutants experience (i) higher than neutral fixation probability and a higher mean conditional fixation time, if the division rates are affected by randomness and (ii) lower fixation probability and lower mean conditional fixation time if the death rates are affected. Once spatial restrictions are imposed, however, these effects completely disappear, and mutants in a circular graph experience neutral dynamics, but only for the DB update rule in case (i) and for the BD rule in case (ii) above. In contrast to this, in the case of spatially variable environment, both for BD/DB processes, both for complete/circular graph and both for division/death rates affected, minority mutants experience a higher than neutral probability of fixation. Fixation time, however, is increased by randomness on a circle, while it decreases for complete graphs under random division rates. A basic difference between temporal and spatial kinds of variability is the types of correlations that occur in the system. Under temporal randomness, mutants are spatially correlated with each other (they simply have equal fitness values at a given moment of time; the same holds for wild-types). Under spatial randomness, there are subtler, temporal correlations among mutant and wild-type cells, which manifest themselves by cells of each type 'claiming' better spots for themselves. Applications of this theory include cancer generation and biofilm dynamics.
了解环境变异性(或随机性)如何影响进化对于生物学具有根本重要性。时间或空间变异性的存在会显著影响种群的竞争动态,并产生一些违反直觉的观察结果。在本文中,我们考虑了出生-死亡(BD)或死亡-出生(DB) Moran 过程,这些过程建立在圆形或完全图上。我们研究了影响分裂和/或死亡参数的时空变异性。假设突变体和野生型的适合度参数来自相同的分布,我们研究了突变体的固定概率和时间。我们证明了时空类型的变异性具有根本不同的性质。在时间随机性下,在完全混合的系统中,如果分裂率受到随机性的影响,少数突变体经历(i)高于中性固定概率和更高的条件固定时间均值,如果死亡率受到随机性的影响;(ii)较低的固定概率和较低的条件固定时间均值。然而,一旦施加空间限制,这些效应就完全消失,并且在圆形图中的突变体经历中性动力学,但仅适用于情况(i)中的 DB 更新规则和情况(ii)中的 BD 规则。相比之下,在空间变化的环境中,无论是对于 BD/DB 过程、完整/圆形图还是受到影响的分裂/死亡率,少数突变体的固定概率都高于中性。然而,固定时间由于随机分裂率的随机性而增加,而对于随机分裂率的完整图则减少。时间和空间类型的变异性之间的一个基本区别是系统中发生的相关性类型。在时间随机性下,突变体彼此具有空间相关性(它们在给定时刻具有相同的适合度值;野生型也是如此)。在空间随机性下,突变体和野生型细胞之间存在更微妙的时间相关性,这些相关性表现为每种类型的细胞为自己“声称”更好的位置。该理论的应用包括癌症发生和生物膜动力学。