Fixation dynamics of beneficial alleles in prokaryotic polyploid chromosomes and plasmids

Theoretical population genetics has been mostly developed for sexually reproducing diploid and for monoploid (haploid) organisms, focusing on eukaryotes. The evolution of bacteria and archaea is often studied by models for the allele dynamics in monoploid populations. However, many prokaryotic organisms harbor multicopy replicons -- chromosomes and plasmids -- and theory for the allele dynamics in populations of polyploid prokaryotes remains lacking. Here we present a population genetics model for replicons with multiple copies in the cell. Using this model, we characterize the fixation process of a dominant beneficial mutation at two levels: the phenotype and the genotype. Our results show that, depending on the mode of replication and segregation, the fixation time of mutant phenotypes may precede the genotypic fixation time by many generations; we term this time interval the heterozygosity window. We furthermore derive concise analytical expressions for the occurrence and length of the heterozygosity window, showing that it emerges if the copy number is high and selection strong. Replicon ploidy thus allows for the maintenance of genetic variation following phenotypic adaptation and consequently for reversibility in adaptation to fluctuating environmental conditions.

The effect of weak clonal interference on average fitness trajectories in the presence of macroscopic epistasis

Adaptation dynamics on fitness landscapes is often studied theoretically in the strong-selection, weak-mutation (SSWM) regime. However, in a large population, multiple beneficial mutants can emerge before any of them fixes in the population. Competition between mutants is known as clonal interference, and how it affects the form of long-term fitness trajectories in the presence of epistasis is an open question. Here, by considering how changes in fixation probabilities arising from weak clonal interference affect the dynamics of adaptation on fitness-parameterized landscapes, we find that the change in the form of fitness trajectory arises only through changes in the supply of beneficial mutations (or equivalently, the beneficial mutation rate). Furthermore, a depletion of beneficial mutations as a population climbs up the fitness landscape can speed up the functional form of the fitness trajectory, while an enhancement of the beneficial mutation rate does the opposite of slowing down the form of the dynamics. Our findings suggest that by carrying out evolution experiments in both regimes (with and without clonal interference), one could potentially distinguish the different sources of macroscopic epistasis (fitness effect of mutations vs. change in fraction of beneficial mutations).

Experimental evidence that metapopulation structure can accelerate adaptive evolution

Whether the spatial arrangement of a population influences adaptive evolution has been a long-standing question in population genetics. In contrast to standard population genetic models, evolutionary graph theory (EGT) predicts certain topologies amplify (increase) the probability that a beneficial mutation will spread in the population relative to a well-mixed population. Here, we test these predictions empirically by tracking the fixation dynamics of an antibiotic resistant mutant under positive selection as it spreads through networks of different topologies both in vitro and in silico. We show that star-like topologies involving bi-directional dispersal between a central hub and peripheral leaves can be amplifiers of selection relative to a well-mixed network, consistent with the predictions of EGT. We further show that the mechanism responsible for amplification is the reduced probability that a rare beneficial mutant will be lost due to drift when it encounters a new patch. Our results provide the first empirical support for the prediction of EGT that spatial structure can amplify the spread of a beneficial mutation and broadens the conditions under which this phenomenon is thought to occur. We also show the importance of considering the migration rate, which is not independently adjustable in most previous models. More generally, our work underscores the potential importance of spatial structure in governing adaptive evolution by showing how the interplay between spatial structure and evolutionary forces determine the fate of a beneficial mutation. It also points the way towards using network topology to amplify the effects of weakly favoured mutations under directed evolution in industrial applications.

Fast and strong amplifiers of natural selection

Selection and random drift determine the probability that novel mutations fixate in a population. Population structure is known to affect the dynamics of the evolutionary process. Amplifiers of selection are population structures that increase the fixation probability of beneficial mutants compared to well-mixed populations. Over the past 15 years, extensive research has produced remarkable structures called strong amplifiers which guarantee that every beneficial mutation fixates with high probability. But strong amplification has come at the cost of considerably delaying the fixation event, which can slow down the overall rate of evolution. However, the precise relationship between fixation probability and time has remained elusive. Here we characterize the slowdown effect of strong amplification. First, we prove that all strong amplifiers must delay the fixation event at least to some extent. Second, we construct strong amplifiers that delay the fixation event only marginally as compared to the well-mixed populations. Our results thus establish a tight relationship between fixation probability and time: Strong amplification always comes at a cost of a slowdown, but more than a marginal slowdown is not needed.

Variable dosage compensation is associated with female consequences of an X-linked, male-beneficial mutation

Recent theory has suggested that dosage compensation mediates sexual antagonism over X-linked genes. This process relies on the assumption that dosage compensation scales phenotypic effects between the sexes, which is largely untested. We evaluated this by quantifying transcriptome variation associated with a recently arisen, male-beneficial, X-linked mutation across tissues of the field cricket Teleogryllus oceanicus , and testing the relationship between the completeness of dosage compensation and female phenotypic effects at the level of gene expression. Dosage compensation in T. oceanicus was variable across tissues but usually incomplete, such that relative expression of X-linked genes was typically greater in females. Supporting the assumption that dosage compensation scales phenotypic effects between the sexes, we found tissues with incomplete dosage compensation tended to show female-skewed effects of the X-linked allele. In gonads, where expression of X-linked genes was most strongly female-biased, ovaries-limited genes were much more likely to be X-linked than were testes-limited genes, supporting the view that incomplete dosage compensation favours feminization of the X. Our results support the expectation that sex chromosome dosage compensation scales phenotypic effects of X-linked genes between sexes, substantiating a key assumption underlying the theoretical role of dosage compensation in determining the dynamics of sexual antagonism on the X.

Identifying Potentially Beneficial Genetic Mutations Associated with Monophyletic Selective Sweep and a Proof-of-Concept Study with Viral Genetic Data

ABSTRACT Genetic mutations play a central role in evolution. For a significantly beneficial mutation, a one-time mutation event suffices for the species to prosper and predominate through the process called “monophyletic selective sweep.” However, existing methods that rely on counting the number of mutation events to detect selection are unable to find such a mutation in selective sweep. We here introduce a method to detect mutations at the single amino acid/nucleotide level that could be responsible for monophyletic selective sweep evolution. The method identifies a genetic signature associated with selective sweep using the population genetic test statistic Tajima’s D. We applied the algorithm to ebolavirus, influenza A virus, and severe acute respiratory syndrome coronavirus 2 to identify known biologically significant mutations and unrecognized mutations associated with potential selective sweep. The method can detect beneficial mutations, possibly leading to discovery of previously unknown biological functions and mechanisms related to those mutations. IMPORTANCE In biology, research on evolution is important to understand the significance of genetic mutation. When there is a significantly beneficial mutation, a population of species with the mutation prospers and predominates, in a process called “selective sweep.” However, there are few methods that can find such a mutation causing selective sweep from genetic data. We here introduce a novel method to detect such mutations. Applying the method to the genomes of ebolavirus, influenza viruses, and the novel coronavirus, we detected known biologically significant mutations and identified mutations the importance of which is previously unrecognized. The method can deepen our understanding of molecular and evolutionary biology.

The cost of evolved constitutive lac gene expression is usually, but not always, maintained during evolution of generalist populations

Beneficial mutations can become costly following an environmental change. Compensatory mutations can relieve these costs, while not affecting the selected function, so that the benefits are retained if the environment shifts back to be similar to the one in which the beneficial mutation was originally selected. Compensatory mutations have been extensively studied in the context of antibiotic resistance, responses to specific genetic perturbations and in the determination of interacting gene network components. Few studies have focused on the role of compensatory mutations during more general adaptation, especially as the result of selection in fluctuating environments where adaptations to different environment components may often involve tradeoffs. We examine if costs of a mutation in lacI, which deregulated expression of the lac operon in evolving populations of Escherichia coli bacteria, was compensated. This mutation occurred in multiple replicate populations selected in environments that fluctuated between growth on lactose, where the mutation was beneficial, and on glucose, where it was deleterious. We found that compensation for the cost of the lacI mutation was rare, but, when it did occur, it did not negatively affect the selected benefit. Compensation was not more likely to occur in a particular evolution environment. Compensation has the potential to remove pleiotropic costs of adaptation, but its rarity indicates that the circumstances to bring about the phenomenon may be peculiar to each individual or impeded by other selected mutations.

Evolution in the weak-mutation limit: Stasis periods punctuated by fast transitions between saddle points on the fitness landscape

A mathematical analysis of the evolution of a large population under the weak-mutation limit shows that such a population would spend most of the time in stasis in the vicinity of saddle points on the fitness landscape. The periods of stasis are punctuated by fast transitions, in lnNe/s time (Ne, effective population size; s, selection coefficient of a mutation), when a new beneficial mutation is fixed in the evolving population, which accordingly moves to a different saddle, or on much rarer occasions from a saddle to a local peak. Phenomenologically, this mode of evolution of a large population resembles punctuated equilibrium (PE) whereby phenotypic changes occur in rapid bursts that are separated by much longer intervals of stasis during which mutations accumulate but the phenotype does not change substantially. Theoretically, PE has been linked to self-organized criticality (SOC), a model in which the size of “avalanches” in an evolving system is power-law-distributed, resulting in increasing rarity of major events. Here we show, however, that a PE-like evolutionary regime is the default for a very simple model of an evolving population that does not rely on SOC or any other special conditions.

Shifts in mutation spectra enhance access to beneficial mutations

Biased mutation spectra are pervasive, with widely varying direction and magnitude of mutational bias. Why are unbiased spectra rare, and how do such diverse biases evolve? We find that experimentally changing the mutation spectrum increases the beneficial mutation supply, because populations sample mutational classes that were poorly explored by the ancestor. Simulations show that selection does not oppose the evolution of a mutational bias in an unbiased ancestor; but it favours changing the direction of a long-term bias. Indeed, spectrum changes in the bacterial phylogeny are frequent, typically involving reversals of ancestral bias. Thus, shifts in mutation spectra evolve under selection, and may directly alter outcomes of adaptive evolution by facilitating access to beneficial mutations.

Punctuated equilibrium as the default mode of evolution of large populations on fitness landscapes dominated by saddle points in the weak-mutation limit

Punctuated equilibrium is a mode of evolution in which phenetic change occurs in rapid bursts that are separated by much longer intervals of stasis during which mutations accumulate but no major phenotypic change occurs. Punctuated equilibrium has been originally proposed within the framework of paleobiology, to explain the lack of transitional forms that is typical of the fossil record. Theoretically, punctuated equilibrium has been linked to self-organized criticality (SOC), a model in which the size of ‘avalanches’ in an evolving system is power-law distributed, resulting in increasing rarity of major events. We show here that, under the weak-mutation limit, a large population would spend most of the time in stasis in the vicinity of saddle points in the fitness landscape. The periods of stasis are punctuated by fast transitions, in lnNe time (Ne, effective population size), when a new beneficial mutation is fixed in the evolving population, which moves to a different saddle, or on much rarer occasions, from a saddle to a local peak. Thus, punctuated equilibrium is the default mode of evolution under a simple model that does not involve SOC or other special conditions.SignificanceThe gradual character of evolution is a key feature of the Darwinian worldview. However, macroevolutionary events are often thought to occur in a non-gradualist manner, in a regime known as punctuated equilibrium, whereby extended periods of evolutionary stasis are punctuated by rapid transitions between states. Here we analyze a mathematical model of population evolution on fitness landscapes and show that, for a large population in the weak-mutation limit, the process of adaptive evolution consists of extended periods of stasis, which the population spends around saddle points on the landscape, interrupted by rapid transitions to new saddle points when a beneficial mutation is fixed. Thus, punctuated equilibrium appears to be the default regime of biological evolution.