Genome dynamics during experimental evolution

Abstract

Evolutionary changes in organismal traits may occur either gradually or suddenly. However, until recently, there has been little direct information about how phenotypic changes are related to the rate and the nature of the underlying genotypic changes. Technological advances that facilitate whole-genome and whole-population sequencing, coupled with experiments that 'watch' evolution in action, have brought new precision to and insights into studies of mutation rates and genome evolution. In this Review, we discuss the evolutionary forces and ecological processes that govern genome dynamics in various laboratory systems in the context of relevant population genetic theory, and we relate these findings to evolution in natural populations.

Figure 1. Types of evolution experiments

There are three main ways that populations are propagated in evolution experiments, and they lead to different types of genetic dynamics. The mechanics of how populations are maintained in each setup are illustrated for microbes (top panels), with representative changes in population sizes over time also shown for each procedure (bottom panels). Analogous procedures exist for multicellular organisms, although population sizes are generally much smaller. a | Mutation accumulation. Frequent and deliberate population bottlenecks through one or a few randomly chosen breeding individuals, as accomplished by picking colonies of microorganisms that grow from single cells on agar plates, purge genetic diversity and lead to the fixation of arbitrary mutations without respect to their effects on fitness. b | Continuous culture. Maintaining organisms in populations where there is a constant inflow of nutrients and an outflow of random individuals and waste, as occurs in a chemostat, leads to adaptive evolution and genetic diversity within populations that typically maintain a nearly constant size. c | Serial transfer. Batch growth, where a fraction of the population is periodically transferred to fresh media and allowed to regrow until the limiting nutrient is exhausted, also leads to adaptive evolution because ample genetic diversity is maintained through each transfer. Alternatively, transfers can be made prior to nutrient depletion, thereby allowing perpetual population growth. A second, cryptic type of population bottleneck occurs during adaptive evolution experiments (b and c) as a consequence of selective sweeps, especially in asexual populations, that drive out competing lineages and thereby reduce genetic diversity.

Figure 2. | Genetic dynamics in evolution experiments

Five scenarios are illustrated using Muller plots (panels at left), which show the frequencies of different genotypes over time as shaded wedges. As new mutations appear, they are linked with mutations that previously arose in their predecessors. When there is sexual reproduction, existing mutational variants may also be recombined to produce new genotypes (as indicated by arrows pointing to multiply shaded regions with dashed boundaries). The frequencies of different alleles (mutational variants) within the population, as would be measured by metagenomic sequencing, are also shown for each scenario (panels at right). a | Periodic selection. If the rate at which new beneficial mutations appear is low and the fitness benefit of each mutation large, then only one mutation will usually sweep through the population at a time. These dynamics cause near step-like trajectories for fitness, phenotypic traits, and the number of beneficial mutations that accumulate over time. Successive sweeps typically take longer as the expected marginal benefit of a later mutation decreases if evolution is in the optimization regime, as pictured. b | Clonal interference. If the supply rate of beneficial mutations is higher, because either the population size or overall mutation rate is increased, then multiple beneficial mutations may arise before one of them achieves fixation. In asexual populations, competition between the contending mutations slows their progress toward fixation, allowing time for additional beneficial mutations to occur and giving rise to more complex trajectories for fitness and mutation number. c | Strong selection. If strong selection is imposed periodically, in ways that may even be lethal to most of the population (dashed vertical lines), then only one or a few genotypes may persist, and they can then quickly achieve fixation after this selection-induced bottleneck. This scenario can lead to large and sudden changes in a phenotype such as resistance to an antibiotic or stress. d | Sexual reproduction in an initially clonal population. As new beneficial mutations arise, they can be recombined into the same genetic background, rather than only competing with one another as in asexual populations. Thus, sex may lead to more rapid genetic evolution and adaptation. e | Sexual reproduction with standing genetic diversity. Shuffling of the genetic diversity initially present in a population may generate fitter genotypes faster than waiting for new beneficial mutations. Even so, if many different combinations of existing alleles give similar benefits, then no one allele will necessarily sweep to fixation on the timescale of the experiment.

Figure 3. | Second-order selection for evolvability

The success of a new mutation or a new combination of alleles may depend on its effect on the rate or fitness benefits of subsequent mutations, in addition to its immediate effect on fitness. Several scenarios are illustrated as alternative mutational paths in fitness landscapes. Genotypes are represented by circles; thick arrows represent initial mutations that generate a new genotype, and thin arrows represent subsequent mutational paths that are available to the genotypes; the mutation rate of a genotype is reflected by the number of thin arrows projecting from it. a | A fitness landscape favouring a hypermutator is shown. From a progenitor with a low ancestral mutation rate (blue), a variant that causes an elevated mutation rate (green) can sometimes take over an asexual population because it has a higher per-capita probability of generating beneficial mutations. Access to these opportunities may outweigh the immediate fitness cost of an increased genetic load. b | A fitness landscape favouring an antimutator is shown. In the longer term, as evolution approaches a local optimum and there are fewer beneficial mutations available, genotypes with lower mutation rates may evolve and be favoured because they have a reduced genetic load. c | A fitness landscape promoting an accessible innovation is shown. Starting from the same progenitor genotype (black), two mutants may have different probabilities of eventual success owing to differences in their evolvability. Here, one mutation (green) makes it possible for a subsequent mutation to invade an open niche, while the other mutation (blue) does not. d | A fitness landscape with antagonistic epistasis is shown. Even in the same niche, one beneficial mutation (blue) may constrain opportunities for further fitness gain more than another (green) because of antagonistic epistatic interactions. In essence, some beneficial mutations may lead to cul-de-sacs in the fitness landscape, allowing other beneficial mutations that do not limit further adaptation to prevail, provided they coexist for enough time. If evolution can be replayed many times starting with the two different genotypes, then an over- or under-representation of mutations in specific genes would provide a signature of such epistatic effects.

Figure 4. | Ecological and coevolutionary dynamics

Examples of genetic diversification and dynamics that are driven by ecological interactions within and between species. a | Multiple niches stabilize genetic diversity that evolves within one species. A new lineage colonizes an open niche, increasing the total population size, as shown here when the red ecotype using the primary niche gives rise to the blue ecotype that expands into an open niche. Negative frequency dependence in the fitness of these ecotypes allows their coexistence. In some cases, one lineage may be a source population that can evolve to recolonize the other niche and displace the lineage that previously occupied that niche, as shown here when the later, yellow ecotype from the primary niche gives rise to the violet ecotype that invades the second niche, displacing the previous occupant. b | In host-parasite co-evolution experiments, either hosts and parasites can be allowed to evolve over time or one partner — in this case, the host — can be kept unchanged by continually replenishing its population from a non-evolving stock. Genetic and phenotypic evolution typically occurs at higher rates when the partners co-evolve in response to one other — a phenomenon that is often referred to as “Red Queen” dynamics.