The Evolution of Phenotypic Switching in Subdivided Populations

Abstract

Stochastic switching is an example of phenotypic bet hedging, where offspring can express a phenotype different from that of their parents. Phenotypic switching is well documented in viruses, yeast, and bacteria and has been extensively studied when the selection pressures vary through time. However, there has been little work on the evolution of phenotypic switching under both spatially and temporally fluctuating selection pressures. Here we use a population genetic model to explore the interaction of temporal and spatial variation in determining the evolutionary dynamics of phenotypic switching. We find that the stable switching rate is mainly determined by the rate of environmental change and the migration rate. This stable rate is also a decreasing function of the recombination rate, although this is a weaker effect than those of either the period of environmental change or the migration rate. This study highlights the interplay of spatial and temporal environmental variability, offering new insights into how migration can influence the evolution of phenotypic switching rates, mutation rates, or other sources of phenotypic variation. GENETICALLY identical cells can show significant cell-tocell variability in gene expression and other phenotypic characteristics. This variation in gene expression can be due to fluctuations in levels of methylation of CpG sites, in mRNA transcription, or in protein translation and may cause shifts among different regulatory states that result in bi-or multistability (Smits et al. 2006), which have also been viewed as an epigenetic switch (Lim and van Oudenaarden 2007). Moreover, these states are often heritable between generations, perhaps due to epigenetic inheritance. Examples include the lactose utilization network in Escherichia coli, where single cells can stochastically switch between two different states (Mettetal et al. 2006), or the galactose utilization network in yeast that displays bimodal patterns in the expression of GAL genes (Acar et al. 2005;Kaufmann et al. 2007).In stochastic switching, individual cells can randomly switch between different phenotypes, which may be inherited. The mode of inheritance in such cases can depart from straightforward Mendelism (Bonduriansky and Day 2009;Danchin and Wagner 2010). In particular, there can be interactions between inherited environmental conditions and epigenetic effects (see, e.g., Furrow et al. 2011) that contribute to the statistical heritability of phenotypes.Why do these genetically identical populations exhibit such switching behaviors? Stochastic switching is often interpreted as a bet-hedging strategy (Starrfelt and Kokko 2012) that could confer a fitness advantage in volatile environments (Thattai and van Oudenaarden 2004;Kussell and Leibler 2005). Switching increases the phenotypic diversity of the population within one generation, thereby increasing the chance of well-adapted offspring in a future environment. Studies have shown that stochastic changes can be advantageous even in comparison to envi...

Epigenetics in natural animal populations

“…This is intriguing because some recent findings studied under the context of bethedging may be directly translatable to epigenetic switching (e.g. Kussell & Leibler, 2005;Carja et al, 2014).…”

Evolution in changing environments: Modifiers of mutation, recombination, and migration

“…Moreover, the critical points of the mean fitness with respect to the mutation rate are those that cannot be invaded. Carja et al (62) also showed that these results hold with spatial heterogeneity in selection: For period 2 and symmetric selection, a modifier increasing mutation can always invade in the population regardless of the migration rate. Furthermore, for higher environmental periods, analytic computation in Mathematica (Wolfram Mathematica) was used to show that the parameter that controls the evolution is m b = ν + μ − 2νμ, where ν is the migration rate and μ the mutation rate.…”

The role of migration in the evolution of phenotypic switching

“…But if higher rates of switching are extremely beneficial to recent migrants, a greater rate of dispersal may select for more switching. A recent theoretical analysis, focusing on the mathematically tractable case of strictly symmetric selection and constant waiting times before environmental change, demonstrated that migration can supplant the need for switching [20]. However, such stringent symmetry conditions may characterize only a small subset of the ecological scenarios in which switching can be adaptive.…”