Synergistic Pleiotropy Overrides the Costs of Complexity in Viral Adaptation

Abstract

Adaptive evolution progresses as a series of steps toward a multidimensional phenotypic optimum, and organismal or environmental complexity determines the number of phenotypic dimensions, or traits, under selection. Populations evolving in complex environments may experience costs of complexity such that improvement in one or more traits is impeded by selection on others. We compared the fitness effects of the first fixed mutations for populations of single-stranded DNA bacteriophage evolving under simple selection for growth rate to those of populations evolving under more complex selection for growth rate as well as capsid stability. We detected a cost of complexity manifested as a smaller growth rate improvement for mutations fixed under complex conditions. We found that, despite imposing a cost for growth rate improvement, strong complex selection resulted in the greatest overall fitness improvement, even for single mutations. Under weaker secondary selective pressures, tradeoffs between growth rate and stability were pervasive, but strong selection on the secondary trait resulted largely in mutations beneficial to both traits. Strength of selection therefore determined the nature of pleiotropy governing observed trait evolution, and strong positive selection forced populations to find mutations that improved multiple traits, thereby overriding costs incurred as a result of a more complex selective environment. The costs of complexity, however, remained substantial when considering the effects on a single trait in the context of selection on multiple traits.

Factors influencing the effect size distribution of adaptive substitutions

“…Pleiotropy has also been implicated in floral divergence across multiple plant species [32]. An experimental evolution study using bacteriophage found that selection on multiple traits commonly led to the fixation of mutations with synergistically beneficial effects, rather than constraints on fitness [33].…”

The genetic architecture of local adaptation and reproductive isolation in sympatry within the Mimulus guttatus species complex

“…), floral (Smith ) and viral adaptation (McGee et al . ). Beneficial pleiotropy should be particularly effective at circumventing fitness valleys when organisms are moving through a multimodal fitness landscape.…”

“…There is now empirical evidence demonstrating that larger effect mutations are more pleiotropic (Albert et al 2008;Wagner et al 2008;Wang et al 2010), and recent theory predicts that many mutations of small effect will predominate when adaptation involves selection on many phenotypes (Tenaillon 2014). However, synergistic pleiotropy, where all effects of a mutation are in an advantageous direction, should facilitate adaptation (Wang et al 2010) and there are empirical examples of beneficially pleiotropic loci contributing to stickleback (Mills et al 2014), floral (Smith 2016) and viral adaptation (McGee et al 2016). Beneficial pleiotropy should be particularly effective at circumventing fitness valleys when organisms are moving through a multimodal fitness landscape.…”

Modeling the interplay between plastic tradeoffs and evolution in changing environments

“…One of the effects we studied by example shows how the best adaptation for one environment may be expected to first emerge in another. Examples of this phenomenon are known experimentally: for instance, the fastest way to evolve resistance to a high dose of antibiotic is through a series of exposures to increasing doses, rather than direct pressure from the environment of interest (see also [19,23]). Our results suggest that for evolution considered across multiple environments, this scenario may well be generic.…”

“…Furthermore, tradeoffs will depend on evolutionary history and themselves evolve [13][14][15][16][17][18]. In laboratory experiments, adapting bacteria to one task can both hinder and improve their performance at another, depending on the experimental protocol, the studied strain, and the exact nature of the tasks, as well as history of prior exposure [19][20][21]. Some phenomena appear non-intuitive and surprising, for instance, even very weak levels of an antibiotic can induce resistance to much higher levels [22,23].…”