Towards evolutionary predictions: Current promises and challenges.

Evolution has traditionally been a historical and descriptive science, and predicting future evolutionary processes has long been considered impossible. However, evolutionary predictions are increasingly being developed and used in medicine, agriculture, biotechnology and conservation biology. Evolutionary predictions may be used for different purposes, such as to prepare for the future, to try and change the course of evolution or to determine how well we understand evolutionary processes. Similarly, the exact aspect of the evolved population that we want to predict may also differ. For example, we could try to predict which genotype will dominate, the fitness of the population or the extinction probability of a population. In addition, there are many uses of evolutionary predictions that may not always be recognized as such. The main goal of this review is to increase awareness of methods and data in different research fields by showing the breadth of situations in which evolutionary predictions are made. We describe how diverse evolutionary predictions share a common structure described by the predictive scope, time scale and precision. Then, by using examples ranging from SARS-CoV2 and influenza to CRISPR-based gene drives and sustainable product formation in biotechnology, we discuss the methods for predicting evolution, the factors that affect predictability and how predictions can be used to prevent evolution in undesirable directions or to promote beneficial evolution (i.e. evolutionary control). We hope that this review will stimulate collaboration between fields by establishing a common language for evolutionary predictions.

Effects of Synonymous Mutations beyond Codon Bias: The Evidence for Adaptive Synonymous Substitutions from Microbial Evolution Experiments.

Synonymous mutations are often assumed to be neutral with respect to fitness because they do not alter the encoded amino acid and so cannot be "seen" by natural selection. Yet a growing body of evidence suggests that synonymous mutations can have fitness effects that drive adaptive evolution through their impacts on gene expression and protein folding. Here, we review what microbial experiments have taught us about the contribution of synonymous mutations to adaptation. A survey of site-directed mutagenesis experiments reveals the distributions of fitness effects for nonsynonymous and synonymous mutations are more similar, especially for beneficial mutations, than expected if all synonymous mutations were neutral, suggesting they should drive adaptive evolution more often than is typically observed. A review of experimental evolution studies where synonymous mutations have contributed to adaptation shows they can impact fitness through a range of mechanisms including the creation of illicit RNA polymerase binding sites impacting transcription and changes to mRNA folding stability that modulate translation. We suggest that clonal interference in evolving microbial populations may be the reason synonymous mutations play a smaller role in adaptive evolution than expected based on their observed fitness effects. We finish by discussing the impacts of falsely assuming synonymous mutations are neutral and discuss directions for future work exploring the role of synonymous mutations in adaptive evolution.

The distribution of fitness effects among synonymous mutations in a gene under directional selection.

The fitness effects of synonymous mutations, nucleotide changes that do not alter the encoded amino acid, have often been assumed to be neutral, but a growing body of evidence suggests otherwise. We used site-directed mutagenesis coupled with direct measures of competitive fitness to estimate the distribution of fitness effects among synonymous mutations for a gene under directional selection and capable of adapting via synonymous nucleotide changes. Synonymous mutations had highly variable fitness effects, both deleterious and beneficial, resembling those of nonsynonymous mutations in the same gene. This variation in fitness was underlain by changes in transcription linked to the creation of internal promoter sites. A positive correlation between fitness and the presence of synonymous substitutions across a phylogeny of related Pseudomonads suggests these mutations may be common in nature. Taken together, our results provide the most compelling evidence to date that synonymous mutations with non-neutral fitness effects may in fact be commonplace.

Identifying Drivers of Parallel Evolution: A Regression Model Approach.

Parallel evolution, defined as identical changes arising in independent populations, is often attributed to similar selective pressures favoring the fixation of identical genetic changes. However, some level of parallel evolution is also expected if mutation rates are heterogeneous across regions of the genome. Theory suggests that mutation and selection can have equal impacts on patterns of parallel evolution; however, empirical studies have yet to jointly quantify the importance of these two processes. Here, we introduce several statistical models to examine the contributions of mutation and selection heterogeneity to shaping parallel evolutionary changes at the gene-level. Using this framework, we analyze published data from forty experimentally evolved Saccharomyces cerevisiae populations. We can partition the effects of a number of genomic variables into those affecting patterns of parallel evolution via effects on the rate of arising mutations, and those affecting the retention versus loss of the arising mutations (i.e., selection). Our results suggest that gene-to-gene heterogeneity in both mutation and selection, associated with gene length, recombination rate, and number of protein domains drive parallel evolution at both synonymous and nonsynonymous sites. While there are still a number of parallel changes that are not well described, we show that allowing for heterogeneous rates of mutation and selection can provide improved predictions of the prevalence and degree of parallel evolution.

What drives parallel evolution?: How population size and mutational variation contribute to repeated evolution.

Parallel evolution is the repeated evolution of the same phenotype or genotype in evolutionarily independent populations. Here, we use evolve-and-resequence experiments with bacteria and yeast to dissect the drivers of parallel evolution at the gene level. A meta-analysis shows that parallel evolution is often rare, but there is a positive relationship between population size and the probability of parallelism. We present a modeling approach to estimate the contributions of mutational and selective heterogeneity across a genome to parallel evolution. We show that, for two experiments, mutation contributes between ∼10 and 45%, respectively, of the variation associated with selection. Parallel evolution cannot, therefore, be interpreted as a phenomenon driven by selection alone; it must also incorporate information on heterogeneity in mutation rates along the genome. More broadly, the work discussed here helps lay the groundwork for a more sophisticated, empirically grounded theory of parallel evolution.

Can the experimental evolution programme help us elucidate the genetic basis of adaptation in nature?

There have been a variety of approaches taken to try to characterize and identify the genetic basis of adaptation in nature, spanning theoretical models, experimental evolution studies and direct tests of natural populations. Theoretical models can provide formalized and detailed hypotheses regarding evolutionary processes and patterns, from which experimental evolution studies can then provide important proofs of concepts and characterize what is biologically reasonable. Genetic and genomic data from natural populations then allow for the identification of the particular factors that have and continue to play an important role in shaping adaptive evolution in the natural world. Further to this, experimental evolution studies allow for tests of theories that may be difficult or impossible to test in natural populations for logistical and methodological reasons and can even generate new insights, suggesting further refinement of existing theories. However, as experimental evolution studies often take place in a very particular set of controlled conditions--that is simple environments, a small range of usually asexual species, relatively short timescales--the question remains as to how applicable these experimental results are to natural populations. In this review, we discuss important insights coming from experimental evolution, focusing on four key topics tied to the evolutionary genetics of adaptation, and within those topics, we discuss the extent to which the experimental work compliments and informs natural population studies. We finish by making suggestions for future work in particular a need for natural population genomic time series data, as well as the necessity for studies that combine both experimental evolution and natural population approaches.

Evolution of Fitness Trade-Offs in Locally Adapted Populations of Pseudomonas fluorescens.

Local adaptation seems to be common in natural systems, but the genetic causes of its evolution remain poorly understood. Here we characterize the genetic causes of trade-offs generating local adaptation in populations of Pseudomonas fluorescens that had previously been evolved for specialization on three different carbon resources. We measured the fitness effects of mutations that arose during selection in that environment and in alternative environments to quantify the degree of specialization. We find that all mutations are beneficial in the environment of selection and that those arising later during adaptation are associated with increasingly antagonistic effects in alternative environments compared with those arising earlier, consistent with a multioptima version of Fisher's geometric model of adaptation. We also find that fitness of pairs of beneficial mutations are consistently less than additive in selection environments, producing a pattern of diminishing returns, but are more variable in alternative environments, being either positive or negative. Finally, we find that mutations in genes associated with loss of motility are beneficial across all environments, whereas mutations involving other functions, such as gene regulation, had more variable effects, being more environment specific. Taken together, these results provide a detailed account of the genetics of specialization and suggest that the evolution of trade-offs associated with local adaptation may often result from the antagonistic effects of beneficial mutations substituted later in adaptation.

The effect of selection environment on the probability of parallel evolution.

Across the great diversity of life, there are many compelling examples of parallel and convergent evolution-similar evolutionary changes arising in independently evolving populations. Parallel evolution is often taken to be strong evidence of adaptation occurring in populations that are highly constrained in their genetic variation. Theoretical models suggest a few potential factors driving the probability of parallel evolution, but experimental tests are needed. In this study, we quantify the degree of parallel evolution in 15 replicate populations of Pseudomonas fluorescens evolved in five different environments that varied in resource type and arrangement. We identified repeat changes across multiple levels of biological organization from phenotype, to gene, to nucleotide, and tested the impact of 1) selection environment, 2) the degree of adaptation, and 3) the degree of heterogeneity in the environment on the degree of parallel evolution at the gene-level. We saw, as expected, that parallel evolution occurred more often between populations evolved in the same environment; however, the extent of parallel evolution varied widely. The degree of adaptation did not significantly explain variation in the extent of parallelism in our system but number of available beneficial mutations correlated negatively with parallel evolution. In addition, degree of parallel evolution was significantly higher in populations evolved in a spatially structured, multiresource environment, suggesting that environmental heterogeneity may be an important factor constraining adaptation. Overall, our results stress the importance of environment in driving parallel evolutionary changes and point to a number of avenues for future work for understanding when evolution is predictable.

Effects of new mutations on fitness: insights from models and data.

The rates and properties of new mutations affecting fitness have implications for a number of outstanding questions in evolutionary biology. Obtaining estimates of mutation rates and effects has historically been challenging, and little theory has been available for predicting the distribution of fitness effects (DFE); however, there have been recent advances on both fronts. Extreme-value theory predicts the DFE of beneficial mutations in well-adapted populations, while phenotypic fitness landscape models make predictions for the DFE of all mutations as a function of the initial level of adaptation and the strength of stabilizing selection on traits underlying fitness. Direct experimental evidence confirms predictions on the DFE of beneficial mutations and favors distributions that are roughly exponential but bounded on the right. A growing number of studies infer the DFE using genomic patterns of polymorphism and divergence, recovering a wide range of DFE. Future work should be aimed at identifying factors driving the observed variation in the DFE. We emphasize the need for further theory explicitly incorporating the effects of partial pleiotropy and heterogeneity in the environment on the expected DFE.

Adaptive synonymous mutations in an experimentally evolved Pseudomonas fluorescens population.

Conventional wisdom holds that synonymous mutations, nucleotide changes that do not alter the encoded amino acid, have no detectable effect on phenotype or fitness. However, a growing body of evidence from both comparative and experimental studies suggests otherwise. Synonymous mutations have been shown to impact gene expression, protein folding and fitness, however, direct evidence that they can be positively selected, and so contribute to adaptation, is lacking. Here we report the recovery of two beneficial synonymous single base pair changes that arose spontaneously and independently in an experimentally evolved population of Pseudomonas fluorescens. We show experimentally that these mutations increase fitness by an amount comparable to non-synonymous mutations and that the fitness increases stem from increased gene expression. These results provide unequivocal evidence that synonymous mutations can drive adaptive evolution and suggest that this class of mutation may be underappreciated as a cause of adaptation and evolutionary dynamics.

Competition both drives and impedes diversification in a model adaptive radiation.

Competitors are known to be important in governing the outcome of evolutionary diversification during an adaptive radiation, but the precise mechanisms by which they exert their effects remain elusive. Using the model adaptive radiation of Pseudomonas fluorescens, we show experimentally that the effect of competition on diversification of a focal lineage depends on both the strength of competition and the ability of the competitors to diversify. We provide evidence that the extent of diversification in the absence of interspecific competitors depends on the strength of resource competition. We also show that the presence of competitors can actually increase diversity by increasing interspecific resource competition. Competitors that themselves are able to diversify prevent diversification of the focal lineage by removing otherwise available ecological opportunities. These results suggest that the progress of an adaptive radiation depends ultimately on the strength of resource competition, an effect that can be exaggerated or impeded by the presence of competitors.

Spatial structure of ecological opportunity drives adaptation in a bacterium.

Abundant ecological opportunity is thought to drive adaptation and diversification. The presence of multiple opportunities leads to divergent selection, which can slow adaptation when niche-specific beneficial mutations have antagonistically pleiotropic effects. Alternately, competition for multiple opportunities can generate divergent selection, which leads to high rates of adaptive differentiation. Which outcome occurs may depend on the spatial structure of those ecological opportunities. In a mixture of resources, competition for multiple opportunities can drive divergent selection; however, if each resource is available in a spatially distinct patch, simultaneous competition for multiple opportunities cannot occur. We report the effects of the extent and spatial structure of ecological opportunity on the evolutionary dynamics of populations of Pseudomonas fluorescens over 1,000 generations. We varied the extent of ecological opportunity by varying the number of sugar resources (mannose, glucose, and xylose), and we varied spatial structure by providing resources in either mixtures or spatially distinct patches. We saw that a particularly novel resource (xylose) drove the rate of adaptation when provided in a mixture but had no effect on diversity. Instead, we saw the evolution of a single adaptive strategy that differed with respect to phenotype and degree of specialization, depending on both the extent and the spatial structure of ecological opportunity.

Evolutionary insight from whole-genome sequencing of experimentally evolved microbes.

Experimental evolution (EE) combined with whole-genome sequencing (WGS) has become a compelling approach to study the fundamental mechanisms and processes that drive evolution. Most EE-WGS studies published to date have used microbes, owing to their ease of propagation and manipulation in the laboratory and relatively small genome sizes. These experiments are particularly suited to answer long-standing questions such as: How many mutations underlie adaptive evolution, and how are they distributed across the genome and through time? Are there general rules or principles governing which genes contribute to adaptation, and are certain kinds of genes more likely to be targets than others? How common is epistasis among adaptive mutations, and what does this reveal about the variety of genetic routes to adaptation? How common is parallel evolution, where the same mutations evolve repeatedly and independently in response to similar selective pressures? Here, we summarize the significant findings of this body of work, identify important emerging trends and propose promising directions for future research. We also outline an example of a computational pipeline for use in EE-WGS studies, based on freely available bioinformatics tools.