Organismal adaptation to a new environment may start with plastic phenotypic changes followed by genetic changes, but whether the plastic changes are stepping stones to genetic adaptation is debated. Here we address this question by investigating gene expression and metabolic flux changes in the two-phase adaptation process using transcriptomic data from multiple experimental evolution studies and computational metabolic network analysis, respectively. We discover that genetic changes more frequently reverse than reinforce plastic phenotypic changes in virtually every adaptation. Metabolic network analysis reveals that, even in the presence of plasticity, organismal fitness drops after environmental shifts, but largely recovers through subsequent evolution. Such fitness trajectories explain why plastic phenotypic changes are genetically compensated rather than strengthened. In conclusion, although phenotypic plasticity may serve as an emergency response to a new environment that is necessary for survival, it does not generally facilitate genetic adaptation by bringing the organismal phenotype closer to the new optimum.

Phenotypic plasticity refers to environment-induced phenotypic changes without mutation and is present in all organisms. The role of phenotypic plasticity in organismal adaptations to novel environments has attracted much attention, but its role in readaptations to ancestral environments is understudied. To address this question, we use the reciprocal transplant approach to investigate the multitissue transcriptomes of chickens adapted to the Tibetan Plateau and adjacent lowland. While many genetic transcriptomic changes had occurred in the forward adaptation to the highland, plastic changes largely transform the transcriptomes to the preferred state when Tibetan chickens are brought back to the lowland. The same trend holds for egg hatchability, a key component of the chicken fitness. These findings, along with highly similar patterns in comparable experiments of guppies and Escherichia coli, demonstrate that organisms generally “remember” their ancestral environments via phenotypic plasticity and reveal a mechanism by which past experience affects future evolution.

Organismal adaptations to new environments often begin with plastic phenotypic changes followed by genetic phenotypic changes, but the relationship between the two types of changes is controversial. Contrary to the view that plastic changes serve as steppingstones to genetic adaptations, recent transcriptome studies reported that genetic gene expression changes more often reverse than reinforce plastic expression changes in experimental evolution. However, it was pointed out that this trend could be an artifact of the statistical nonindependence between the estimates of plastic and genetic phenotypic changes, because both estimates rely on the phenotypic measure at the plastic stage. Using computer simulation, we show that indeed the nonindependence can cause an apparent excess of expression reversion relative to reinforcement. We propose a parametric bootstrap method and show by simulation that it removes the bias almost entirely. Analyzing transcriptome data from a total of 34 parallel lines in 5 experimental evolution studies of Escherichia coli, yeast, and guppies that are amenable to our method confirms that genetic expression changes tend to reverse plastic changes. Thus, at least for gene expression traits, phenotypic plasticity does not generally facilitate genetic adaptation. Several other comparisons of statistically nonindependent estimates are commonly performed in evolutionary genomics such as that between cis- and trans-effects of mutations on gene expression and that between transcriptional and translational effects on gene expression. It is important to validate previous results from such comparisons, and our proposed statistical analyses can be useful for this purpose.

Although evolution by natural selection is widely regarded as the most important principle of biology, it is unknown whether phenotypic variations within and between species are mostly adaptive or neutral due to the lack of relevant studies of large, unbiased samples of phenotypic traits. Here, we examine 210 yeast morphological traits chosen because of experimental feasibility irrespective of their potential adaptive values. Our analysis is based on the premise that, under neutrality, the rate of phenotypic evolution measured in the unit of mutational size declines as the trait becomes more important to fitness, analogous to the neutral paradigm that functional genes evolve more slowly than functionless pseudogenes. However, we find faster evolution of more important morphological traits within and between species, rejecting the neutral hypothesis. By contrast, an analysis of 3,466 gene expression traits fails to refute neutrality. Thus, at least in yeast, morphological evolution appears largely adaptive, but the same may not apply to other classes of phenotypes. Our neutrality test is applicable to other species, especially genetic model organisms, for which estimations of mutational size and trait importance are relatively straightforward.

Ecological and demographic factors can significantly shape the evolution of microbial populations both directly and indirectly, as when changes in the effective population size affect the efficiency of natural selection on the mutation rate. However, it remains unclear how rapidly the mutation-rate responds evolutionarily to the entanglement of ecological and population-genetic factors over time. Here, we directly assess the mutation rate and spectrum of Escherichia coli clones isolated from populations evolving in response to 1000 days of different transfer volumes and resource-replenishment intervals. The evolution of mutation rates proceeded rapidly in response to demographic and/or environmental changes, with substantial bidirectional shifts observed as early as 59 generations. These results highlight the remarkable rapidity by which mutation rates are shaped in asexual lineages in response to environmental and population-genetic forces, and are broadly consistent with the drift-barrier hypothesis for the evolution of mutation rates, while also highlighting situations in which mutator genotypes may be promoted by positive selection.