Why Are Phenotypic Mutation Rates Much Higher Than Genotypic Mutation Rates?

Abstract

The evolution of genotypic mutation rates has been investigated in numerous theoretical and experimental studies. Mutations, however, occur not only when copying DNA, but also when building the phenotype, especially when translating and transcribing DNA to RNA and protein. Here we study the effect of such phenotypic mutations. We find a maximum phenotypic mutation rate, u max , that is compatible with maintaining a certain function of the organism. This may be called a phenotypic error threshold. In particular, we find a minimum phenotypic mutation rate, u min , with the property that there is (nearly) no selection pressure to reduce the rate of phenotypic mutations below this value. If there is a cost for lowering the phenotypic mutation rate, then u min is close to the optimum phenotypic mutation rate that maximizes the fitness of the organism. In our model, there is selective pressure to decrease the rate of genotypic mutations to zero, but to decrease the rate of phenotypic mutations only to a positive value. Despite its simplicity, our model can explain part of the huge difference between genotypic and phenotypic mutation rates that is observed in nature. The relevant data are summarized.

Nascent RNA folding mitigates transcription-associated mutagenesis

“…Cold Spring Harbor Laboratory Press on May 12, 2018 -Published by genome.cshlp.org Downloaded from low mutation rate); and RNA folding is the first known mechanism that simultaneously and concordantly regulates the genotypic mutation rate and phenotypic mutation rate (Bürger et al 2006). The full biological ramifications of the intriguing coupling between the processing and transmission accuracies of genetic information via RNA folding await further explorations.…”

Phenotype Switching and Mutations in Random Environments

“…Most work (Kimura 1967;Leigh 1970;Ishii et al 1989;Ben-Porath et al 1993;Lachmann and Jablonka 1996;Bürger et al 2006;Acar et al 2008) on evolution in changing environments considers infinite populations and deterministic cycles; Jablonka et al (1995) and Thattai and van Oudenaarden (2004) consider an infinite population and both deterministic and stochastic cycles. King and Masel (2007) consider finite populations governed by a Moran process when phenotype B has zero fitness in environment E and environment F is absorbing; they obtain exact results under the additional assumption that in E, any new-born B's are immediately replaced.…”

“…In our finite population model, reproduction, genetic mutations, phenotype switches, and environmental changes are all stochastic. This distinguishes our framework from most work on evolution in changing environments where infinite populations are considered with deterministic cycles (Kimura 1967;Leigh 1970;Ishii et al 1989;Ben-Porath et al 1993;Lachmann and Jablonka 1996;Bürger et al 2006;Acar et al 2008) or stochastic cycles (Jablonka et al 1995;Thattai and van Oudenaarden 2004). In particular, to determine optimal switching rates, standard arguments for infinite populations based on geometric mean fitness (Stumpf et al 2002) are not suitable for our model (King and Masel 2007).…”

Evolutionary paths of least resistance

“…Bratulic et al's paper (1) adds to a growing body of evidence demonstrating that phenotypic mutations (i.e., mutations occurring solely in the expressed phenotype) may indirectly influence the evolutionary dynamics of the underlying genotype (2,9,(11)(12)(13)(14). In particular, genetic adaptations can protect organisms from the deleterious consequences of phenotypic mutations (1, 9,12).…”

“…In particular, genetic adaptations can protect organisms from the deleterious consequences of phenotypic mutations (1, 9,12). This mechanism in turn opens the possibility that elevated phenotypic mutation rates may be beneficial for further adaptation (11,14).…”