The evolution of novel host use is unlikely to be constrained by trade-offs or a lack of genetic variation

Evolutionary ecology of virus emergence

The cross-species transmission of viruses into new host populations, termed virus emergence, is a significant issue in public health, agriculture, wildlife management, and related fields. Virus emergence requires overlap between host populations, alterations in virus genetics to permit infection of new hosts, and adaptation to novel hosts such that between-host transmission is sustainable, all of which are the purview of the fields of ecology and evolution. A firm understanding of the ecology of viruses and how they evolve is required for understanding how and why viruses emerge. In this paper, I address the evolutionary mechanisms of virus emergence and how they relate to virus ecology. I argue that, while virus acquisition of the ability to infect new hosts is not difficult, limited evolutionary trajectories to sustained virus between-host transmission and the combined effects of mutational meltdown, bottlenecking, demographic stochasticity, density dependence, and genetic erosion in ecological sinks limit most emergence events to dead-end spillover infections. Despite the relative rarity of pandemic emerging viruses, the potential of viruses to search evolutionary space and find means to spread epidemically and the consequences of pandemic viruses that do emerge necessitate sustained attention to virus research, surveillance, prophylaxis, and treatment.

Micro- and Macroevolutionary Trade-Offs in Plant-Feeding Insects

A long-standing hypothesis asserts that plant-feeding insects specialize on particular host plants because of negative interactions (trade-offs) between adaptations to alternative hosts, yet empirical evidence for such trade-offs is scarce. Most studies have looked for microevolutionary performance trade-offs within insect species, but host use could also be constrained by macroevolutionary trade-offs caused by epistasis and historical contingency. Here we used a phylogenetic approach to estimate the micro- and macroevolutionary correlations between use of alternative host-plant taxa within two major orders of plant-feeding insects: Lepidoptera (caterpillars) and Hemiptera (true bugs). Across 1,604 caterpillar species, we found both positive and negative pairwise correlations between use of 11 host-plant orders, with overall network patterns suggesting that different host-use constraints act over micro- and macroevolutionary timescales. In contrast, host-use patterns of 955 true bug species revealed uniformly positive correlations between use of the same 11 host plant orders over both timescales. The lack of consistent patterns across timescales and insect orders indicates that host-use trade-offs are historically contingent rather than universal constraints. Moreover, we observed few negative correlations overall despite the wide taxonomic and ecological diversity of the focal host-plant orders, suggesting that positive interactions between host-use adaptations, not trade-offs, dominate the long-term evolution of host use in plant-feeding insects.

A genomic perspective on the generation and maintenance of genetic diversity in herbivorous insects

Understanding the processes that generate and maintain genetic variation within populations is a central goal in evolutionary biology. Theory predicts that some of this variation is maintained as a consequence of adapting to variable habitats. Studies in herbivorous insects have played a key role in confirming this prediction. Here, we highlight theoretical and conceptual models for the maintenance of genetic diversity in herbivorous insects, empirical genomic studies testing these models, and pressing questions within the realm of evolutionary and functional genomic studies. To address key gaps, we propose an integrative approach combining population genomic scans for adaptation, genome-wide characterization of targets of selection through experimental manipulations, mapping the genetic architecture of traits influencing fitness, and functional studies. We also stress the importance of studying the maintenance of genetic variation across biological scales-from variation within populations to divergence among populations-to form a comprehensive view of adaptation in herbivorous insects.

A Continuous Correlated Beta Process Model for Genetic Ancestry in Admixed Populations

Admixture and recombination create populations and genomes with genetic ancestry from multiple source populations. Analyses of genetic ancestry in admixed populations are relevant for trait and disease mapping, studies of speciation, and conservation efforts. Consequently, many methods have been developed to infer genome-average ancestry and to deconvolute ancestry into continuous local ancestry blocks or tracts within individuals. Current methods for local ancestry inference perform well when admixture occurred recently or hybridization is ongoing, or when admixture occurred in the distant past such that local ancestry blocks have fixed in the admixed population. However, methods to infer local ancestry frequencies in isolated admixed populations still segregating for ancestry do not exist. In the current paper, I develop and test a continuous correlated beta process model to fill this analytical gap. The method explicitly models autocorrelations in ancestry frequencies at the population-level and uses discriminant analysis of SNP windows to take advantage of ancestry blocks within individuals. Analyses of simulated data sets show that the method is generally accurate such that ancestry frequency estimates exhibited low root-mean-square error and were highly correlated with the true values, particularly when large (±10 or ±20) SNP windows were used. Along these lines, the proposed method outperformed post hoc inference of ancestry frequencies from a traditional hidden Markov model (i.e., the linkage model in structure), particularly when admixture occurred more distantly in the past with little on-going gene flow or was followed by natural selection. The reliability and utility of the method was further assessed by analyzing genetic ancestry in an admixed human population (Uyghur) and three populations from a hybrid zone between Mus domesticus and M. musculus. Considerable variation in ancestry frequencies was detected within and among chromosomes in the Uyghur, with a large region of excess French ancestry harboring a gene with a known disease association. Similar variation was detected in the mouse hybrid zone, with notable constancy in regions of excess ancestry among admixed populations. By filling what has been an analytical gap, the proposed method should be a useful tool for many biologists. A computer program (popanc), written in C++, has been developed based on the proposed method and is available on-line at http://sourceforge.net/projects/popanc/.

The Many Dimensions of Diet Breadth: Phytochemical, Genetic, Behavioral, and Physiological Perspectives on the Interaction between a Native Herbivore and an Exotic Host

From the perspective of an herbivorous insect, conspecific host plants are not identical, and intraspecific variation in host nutritional quality or defensive capacity might mediate spatially variable outcomes in plant-insect interactions. Here we explore this possibility in the context of an ongoing host breadth expansion of a native butterfly (the Melissa blue, Lycaeides melissa) onto an exotic host plant (alfalfa, Medicago sativa). We examine variation among seven alfalfa populations that differed in terms of colonization by L. melissa; specifically, we examined variation in phytochemistry, foliar protein, and plant population genetic structure, as well as responses of caterpillars and adult butterflies to foliage from the same populations. Regional patterns of alfalfa colonization by L. melissa were well predicted by phytochemical variation, and colonized patches of alfalfa showed a similar level of inter-individual phytochemical diversity. However, phytochemical variation was a poor predictor of larval performance, despite the fact that survival and weight gain differed dramatically among caterpillars reared on plants from different alfalfa populations. Moreover, we observed a mismatch between alfalfa supporting the best larval performance and alfalfa favored by ovipositing females. Thus, the axes of plant variation that mediate interactions with L. melissa depend upon herbivore life history stage, which raises important issues for our understanding of adaptation to novel resources by an organism with a complex life history.

Scale insect host ranges are broader in the tropics

The specificity of the interactions between plants and their consumers varies considerably. The evolutionary and ecological factors underlying this variation are unclear. Several potential explanatory factors vary with latitude, for example plant species richness and the intensity of herbivory. Here, we use comparative phylogenetic methods to test the effect of latitude on host range in scale insects. We find that, on average, scale insects that occur in lower latitudes are more polyphagous. This result is at odds with the general pattern of greater host-plant specificity of insects in the tropics. We propose that this disparity reflects a high cost for host specificity in scale insects, stemming from unusual aspects of scale insect life history, for example, passive wind-driven dispersal. More broadly, the strong evidence for pervasive effects of geography on host range across insect groups stands in stark contrast to the weak evidence for constraints on host range due to genetic trade-offs.

Phylogenetic analysis reveals positive correlations between adaptations to diverse hosts in a group of pathogen-like herbivores

A jack of all trades can be master of none-this intuitive idea underlies most theoretical models of host-use evolution in plant-feeding insects, yet empirical support for trade-offs in performance on distinct host plants is weak. Trade-offs may influence the long-term evolution of host use while being difficult to detect in extant populations, but host-use evolution may also be driven by adaptations for generalism. Here we used host-use data from insect collection records to parameterize a phylogenetic model of host-use evolution in armored scale insects, a large family of plant-feeding insects with a simple, pathogen-like life history. We found that a model incorporating positive correlations between evolutionary changes in host performance best fit the observed patterns of diaspidid presence and absence on nearly all focal host taxa, suggesting that adaptations to particular hosts also enhance performance on other hosts. In contrast to the widely invoked trade-off model, we advocate a "toolbox" model of host-use evolution in which armored scale insects accumulate a set of independent genetic tools, each of which is under selection for a single function but may be useful on multiple hosts.

Bayesian inference of selection in a heterogeneous environment from genetic time-series data

Evolutionary geneticists have sought to characterize the causes and molecular targets of selection in natural populations for many years. Although this research programme has been somewhat successful, most statistical methods employed were designed to detect consistent, weak to moderate selection. In contrast, phenotypic studies in nature show that selection varies in time and that individual bouts of selection can be strong. Measurements of the genomic consequences of such fluctuating selection could help test and refine hypotheses concerning the causes of ecological specialization and the maintenance of genetic variation in populations. Herein, I proposed a Bayesian nonhomogeneous hidden Markov model to estimate effective population sizes and quantify variable selection in heterogeneous environments from genetic time-series data. The model is described and then evaluated using a series of simulated data, including cases where selection occurs on a trait with a simple or polygenic molecular basis. The proposed method accurately distinguished neutral loci from non-neutral loci under strong selection, but not from those under weak selection. Selection coefficients were accurately estimated when selection was constant or when the fitness values of genotypes varied linearly with the environment, but these estimates were less accurate when fitness was polygenic or the relationship between the environment and the fitness of genotypes was nonlinear. Past studies of temporal evolutionary dynamics in laboratory populations have been remarkably successful. The proposed method makes similar analyses of genetic time-series data from natural populations more feasible and thereby could help answer fundamental questions about the causes and consequences of evolution in the wild.