Holly A. Wichman

An empirical test of the mutational landscape model of adaptation using a single-stranded DNA virus

The primary impediment to formulating a general theory for adaptive evolution has been the unknown distribution of fitness effects for new beneficial mutations. By applying extreme value theory, Gillespie circumvented this issue in his mutational landscape model for the adaptation of DNA sequences, and Orr recently extended Gillespies model, generating testable predictions regarding the course of adaptive evolution. Here we provide the first empirical examination of this model, using a single-stranded DNA bacteriophage related to φX174, and find that our data are consistent with Orrs predictions, provided that the model is adjusted to incorporate mutation bias. Orrs work suggests that there may be generalities in adaptive molecular evolution that transcend the biological details of a system, but we show that for the model to be useful as a predictive or inferential tool, some adjustments for the biology of the system will be necessary.

Horizontal Gene Transfer and the Evolution of Microvirid Coliphage Genomes

Bacteriophage genomic evolution has been largely characterized by rampant, promiscuous horizontal gene transfer involving both homologous and nonhomologous source DNA. This pattern has emerged through study of the tailed double-stranded DNA (dsDNA) phages and is based upon a sparse sampling of the enormous diversity of these phages. The single-stranded DNA phages of the family Microviridae, including phiX174, appear to evolve through qualitatively different mechanisms, possibly as result of their strictly lytic lifestyle and small genome size. However, this apparent difference could reflect merely a dearth of relevant data. We sought to characterize the forces that contributed to the molecular evolution of the Microviridae and to examine the genetic structure of this single family of bacteriophage by sequencing the genomes of microvirid phage isolated on a single bacterial host. Microvirids comprised 3.5% of the detectable phage in our environmental samples, and sequencing yielded 42 new microvirid genomes. Phylogenetic analysis of the genes contained in these and five previously described microvirid phages identified three distinct clades and revealed at least two horizontal transfer events between clades. All members of one clade have a block of five putative genes that are not present in any member of the other two clades. Our data indicate that horizontal transfer does contribute to the evolution of the microvirids but is both quantitatively and qualitatively different from what has been observed for the dsDNA phages.

Beneficial Fitness Effects Are Not Exponential for Two Viruses

The distribution of fitness effects for beneficial mutations is of paramount importance in determining the outcome of adaptation. It is generally assumed that fitness effects of beneficial mutations follow an exponential distribution, for example, in theoretical treatments of quantitative genetics, clonal interference, experimental evolution, and the adaptation of DNA sequences. This assumption has been justified by the statistical theory of extreme values, because the fitnesses conferred by beneficial mutations should represent samples from the extreme right tail of the fitness distribution. Yet in extreme value theory, there are three different limiting forms for right tails of distributions, and the exponential describes only those of distributions in the Gumbel domain of attraction. Using beneficial mutations from two viruses, we show for the first time that the Gumbel domain can be rejected in favor of a distribution with a right-truncated tail, thus providing evidence for an upper bound on fitness effects. Our data also violate the common assumption that small-effect beneficial mutations greatly outnumber those of large effect, as they are consistent with a uniform distribution of beneficial effects.

Epistasis between beneficial mutations and the phenotype-to-fitness Map for a ssDNA virus.

Epistatic interactions between genes and individual mutations are major determinants of the evolutionary properties of genetic systems and have therefore been well documented, but few quantitative data exist on epistatic interactions between beneficial mutations, presumably because such mutations are so much rarer than deleterious ones. We explored epistasis for beneficial mutations by constructing genotypes with pairs of mutations that had been previously identified as beneficial to the ssDNA bacteriophage ID11 and by measuring the effects of these mutations alone and in combination. We constructed 18 of the 36 possible double mutants for the nine available beneficial mutations. We found that epistatic interactions between beneficial mutations were all antagonistic—the effects of the double mutations were less than the sums of the effects of their component single mutations. We found a number of cases of decompensatory interactions, an extreme form of antagonistic epistasis in which the second mutation is actually deleterious in the presence of the first. In the vast majority of cases, recombination uniting two beneficial mutations into the same genome would not be favored by selection, as the recombinant could not outcompete its constituent single mutations. In an attempt to understand these results, we developed a simple model in which the phenotypic effects of mutations are completely additive and epistatic interactions arise as a result of the form of the phenotype-to-fitness mapping. We found that a model with an intermediate phenotypic optimum and additive phenotypic effects provided a good explanation for our data and the observed patterns of epistatic interactions.

Mutational Effects and Population Dynamics During Viral Adaptation Challenge Current Models

Adaptation in haploid organisms has been extensively modeled but little tested. Using a microvirid bacteriophage (ID11), we conducted serial passage adaptations at two bottleneck sizes (104 and 106), followed by fitness assays and whole-genome sequencing of 631 individual isolates. Extensive genetic variation was observed including 22 beneficial, several nearly neutral, and several deleterious mutations. In the three large bottleneck lines, up to eight different haplotypes were observed in samples of 23 genomes from the final time point. The small bottleneck lines were less diverse. The small bottleneck lines appeared to operate near the transition between isolated selective sweeps and conditions of complex dynamics (e.g., clonal interference). The large bottleneck lines exhibited extensive interference and less stochasticity, with multiple beneficial mutations establishing on a variety of backgrounds. Several leapfrog events occurred. The distribution of first-step adaptive mutations differed significantly from the distribution of second-steps, and a surprisingly large number of second-step beneficial mutations were observed on a highly fit first-step background. Furthermore, few first-step mutations appeared as second-steps and second-steps had substantially smaller selection coefficients. Collectively, the results indicate that the fitness landscape falls between the extremes of smooth and fully uncorrelated, violating the assumptions of many current mutational landscape models.

Evolutionary Feedback Mediated through Population Density, Illustrated with Viruses in Chemostats

A cornerstone of evolutionary ecology is that population density affects adaptation: r and K selection is the obvious example. The reverse is also appreciated: adaptation impacts population density. Yet, empirically demonstrating a direct connection between population density and adaptation is challenging. Here, we address both evolution and ecology of population density in models of viral (bacteriophage) chemostats. Chemostats supply nutrients for host cell growth, and the hosts are prey for viral reproduction. Two different chemostat designs have profoundly different consequences for viral evolution. If host and virus are confined to the same chamber, as in a predator‐prey system, viral regulation of hosts feeds back to maintain low viral density (measured as infections per cell). Viral adaptation impacts host density but has a small effect on equilibrium viral density. More interesting are chemostats that supply the viral population with hosts from a virus‐free refuge. Here, a type of evolutionary succession operates: adaptation at low viral density leads to higher density, but high density then favors competitive ability. Experiments support these models with both phenotypic and molecular data. Parallels to these designs exist in many natural systems, so these experimental systems may yield insights to the evolution and regulation of natural populations.

Loss of LINE-1 activity in the megabats.

LINE-1 (L1) retrotransposons are the most abundant type of mammalian retroelement. They have profound effects on genome plasticity and have been proposed to fulfill essential host functions, yet it remains unclear where they lie on the spectrum from parasitism to mutualism. Their ubiquity makes it difficult to determine the extent of their effects on genome evolution and gene expression because of the relative dearth of animal models lacking L1 activity. We have isolated L1 sequences from 11 megabat species by a method that enriches for recently inserted L1s and have done a bioinformatic examination of L1 sequences from a 12th species whose genome was recently shotgun sequenced. An L1 extinction event appears to have occurred at least 24 million years ago (MYA) in an ancestor of the megabats. The ancestor was unusual in having maintained two highly divergent long-term L1 lineages with different levels of activity, which appear, on an evolutionary scale, to have simultaneously lost that activity. These megabat species can serve as new animal models to ask what effect loss of L1 activity has on mammalian genome evolution and gene expression.

Extinction of LINE-1 activity coincident with a major mammalian radiation in rodents

LINE-1 transposable elements (L1s) are ubiquitous in mammals and are thought to have remained active since before the mammalian radiation. Only one L1 extinction event, in South American rodents in the genus Oryzomys, has been convincingly demonstrated. Here we examine the phylogenetic limits and evolutionary tempo of that extinction event by characterizing L1s in related rodents. Fourteen genera from five tribes within the Sigmodontinae subfamily were examined. Only the Sigmodontini, the most basal tribe in this group, demonstrate recent L1 activity. The Oryzomyini, Akodontini, Phyllotini, and Thomasomyini contain only L1s that appear to have inserted long ago; their L1s lack open reading frames, have mutations at conserved amino acid residues, and show numerous private mutations. They also lack restriction site-defined L1 subfamilies specific to any species, genus or tribe examined, and fail to form monophyletic species, genus or tribal L1 clusters. We determine here that this L1 extinction event occurred roughly 8.8 million years ago, near the divergence of Sigmodon from the remaining Sigmodontinae species. These species appear to be ideal model organisms for studying the impact of L1 inactivity on mammalian genomes.

Experimental evolution of viruses: Microviridae as a model system

φX174 was developed as a model system for experimental studies of evolution because of its small genome size and ease of cultivation. It has been used extensively to address statistical questions about the dynamics of adaptive evolution. Molecular changes seen during experimental evolution of φX174 under a variety of conditions were compiled from 10 experiments comprising 58 lineages, where whole genomes were sequenced. A total of 667 substitutions was seen. Parallel evolution was rampant, with over 50 per cent of substitutions occurring at sites with three or more events. Comparisons of experimentally evolved sites to variation seen among wild phage suggest that at least some of the adaptive mechanisms seen in the laboratory are relevant to adaptation in nature. Elucidation of these mechanisms is aided by the availability of capsid and pro-capsid structures for φX174 and builds on years of genetic studies of the phage life history.

Testing the Extreme Value Domain of Attraction for Distributions of Beneficial Fitness Effects

In modeling evolutionary genetics, it is often assumed that mutational effects are assigned according to a continuous probability distribution, and multiple distributions have been used with varying degrees of justification. For mutations with beneficial effects, the distribution currently favored is the exponential distribution, in part because it can be justified in terms of extreme value theory, since beneficial mutations should have fitnesses in the extreme right tail of the fitness distribution. While the appeal to extreme value theory seems justified, the exponential distribution is but one of three possible limiting forms for tail distributions, with the other two loosely corresponding to distributions with right-truncated tails and those with heavy tails. We describe a likelihood-ratio framework for analyzing the fitness effects of beneficial mutations, focusing on testing the null hypothesis that the distribution is exponential. We also describe how to account for missing the smallest-effect mutations, which are often difficult to identify experimentally. This technique makes it possible to apply the test to gain-of-function mutations, where the ancestral genotype is unable to grow under the selective conditions. We also describe how to pool data across experiments, since we expect few possible beneficial mutations in any particular experiment.