The host phylogeny determines viral infectivity and replication across Staphylococcus host species.

Virus host shifts, where a virus transmits to and infects a novel host species, are a major source of emerging infectious disease. Genetic similarity between eukaryotic host species has been shown to be an important determinant of the outcome of virus host shifts, but it is unclear if this is the case for prokaryotes where anti-virus defences can be transmitted by horizontal gene transfer and evolve rapidly. Here, we measure the susceptibility of 64 strains of Staphylococcaceae bacteria (48 strains of Staphylococcus aureus and 16 non-S. aureus species spanning 2 genera) to the bacteriophage ISP, which is currently under investigation for use in phage therapy. Using three methods-plaque assays, optical density (OD) assays, and quantitative (q)PCR-we find that the host phylogeny explains a large proportion of the variation in susceptibility to ISP across the host panel. These patterns were consistent in models of only S. aureus strains and models with a single representative from each Staphylococcaceae species, suggesting that these phylogenetic effects are conserved both within and among host species. We find positive correlations between susceptibility assessed using OD and qPCR and variable correlations between plaque assays and either OD or qPCR, suggesting that plaque assays alone may be inadequate to assess host range. Furthermore, we demonstrate that the phylogenetic relationships between bacterial hosts can generally be used to predict the susceptibility of bacterial strains to phage infection when the susceptibility of closely related hosts is known, although this approach produced large prediction errors in multiple strains where phylogeny was uninformative. Together, our results demonstrate the ability of bacterial host evolutionary relatedness to explain differences in susceptibility to phage infection, with implications for the development of ISP both as a phage therapy treatment and as an experimental system for the study of virus host shifts.

Contemporary selection on MHC genes in a free-living ruminant population.

Genes within the major histocompatibility complex (MHC) are the most variable identified in vertebrates. Pathogen-mediated selection is believed to be the main force maintaining MHC diversity. However, relatively few studies have demonstrated contemporary selection on MHC genes. Here, we examine associations between MHC variation and several fitness measurements including total fitness and five fitness components, in 3400 wild Soay sheep (Ovis aries) monitored between 1989 and 2012. In terms of total fitness, measured as lifetime breeding success of all individuals born, we found haplotypes named C and D were associated with decreased and increased male total fitness respectively. In terms of fitness components, juvenile survival was associated with haplotype divergence while individual haplotypes (C, D and F) were associated with adult fitness components. Consistent with the increased male total fitness, the rarest haplotype D has increased in frequency throughout the study period more than expected under neutral expectations. Our results demonstrate that contemporary natural selection is acting on MHC class II genes in Soay sheep and that the mode of selection on specific fitness components can be different mode from selection on total fitness.

The relative importance of plasticity versus genetic differentiation in explaining between population differences; a meta-analysis.

Both plasticity and genetic differentiation can contribute to phenotypic differences between populations. Using data on non-fitness traits from reciprocal transplant studies, we show that approximately 60% of traits exhibit co-gradient variation whereby genetic differences and plasticity-induced differences between populations are the same sign. In these cases, plasticity is about twice as important as genetic differentiation in explaining phenotypic divergence. In contrast to fitness traits, the amount of genotype by environment interaction is small. Of the 40% of traits that exhibit counter-gradient variation the majority seem to be hyperplastic whereby non-native individuals express phenotypes that exceed those of native individuals. In about 20% of cases plasticity causes non-native phenotypes to diverge from the native phenotype to a greater extent than if plasticity was absent, consistent with maladaptive plasticity. The degree to which genetic differentiation versus plasticity can explain phenotypic divergence varies a lot between species, but our proxies for motility and migration explain little of this variation.

Changes in temperature alter the potential outcomes of virus host shifts.

Host shifts-where a pathogen jumps between different host species-are an important source of emerging infectious disease. With on-going climate change there is an increasing need to understand the effect changes in temperature may have on emerging infectious disease. We investigated whether species' susceptibilities change with temperature and ask if susceptibility is greatest at different temperatures in different species. We infected 45 species of Drosophilidae with an RNA virus and measured how viral load changes with temperature. We found the host phylogeny explained a large proportion of the variation in viral load at each temperature, with strong phylogenetic correlations between viral loads across temperature. The variance in viral load increased with temperature, while the mean viral load did not. This suggests that as temperature increases the most susceptible species become more susceptible, and the least susceptible less so. We found no significant relationship between a species' susceptibility across temperatures, and proxies for thermal optima (critical thermal maximum and minimum or basal metabolic rate). These results suggest that whilst the rank order of species susceptibilities may remain the same with changes in temperature, some species may become more susceptible to a novel pathogen, and others less so.

Gradients in richness and turnover of a forest passerine's diet prior to breeding: A mixed model approach applied to faecal metabarcoding data.

Rather little is known about the dietary richness and variation of generalist insectivorous species, including birds, due primarily to difficulties in prey identification. Using faecal metabarcoding, we provide the most comprehensive analysis of a passerine's diet to date, identifying the relative magnitudes of biogeographic, habitat and temporal trends in the richness and turnover in diet of Cyanistes caeruleus (blue tit) along a 39 site and 2° latitudinal transect in Scotland. Faecal samples were collected in 2014-2015 from adult birds roosting in nestboxes prior to nest building. DNA was extracted from 793 samples and we amplified COI and 16S minibarcodes. We identified 432 molecular operational taxonomic units that correspond to putative dietary items. Most dietary items were rare, with Lepidoptera being the most abundant and taxon-rich prey order. Here, we present a statistical approach for estimation of gradients and intersample variation in taxonomic richness and turnover using a generalised linear mixed model. We discuss the merits of this approach over existing tools and present methods for model-based estimation of repeatability, taxon richness and Jaccard indices. We found that dietary richness increases significantly as spring advances, but changes little with elevation, latitude or local tree composition. In comparison, dietary composition exhibits significant turnover along temporal and spatial gradients and among sites. Our study shows the promise of faecal metabarcoding for inferring the macroecology of food webs, but we also highlight the challenge posed by contamination and make recommendations of laboratory and statistical practices to minimise its impact on inference.

The causes and consequences of changes in virulence following pathogen host shifts.

Emerging infectious diseases are often the result of a host shift, where the pathogen originates from a different host species. Virulence--the harm a pathogen does to its host-can be extremely high following a host shift (for example Ebola, HIV, and SARs), while other host shifts may go undetected as they cause few symptoms in the new host. Here we examine how virulence varies across host species by carrying out a large cross infection experiment using 48 species of Drosophilidae and an RNA virus. Host shifts resulted in dramatic variation in virulence, with benign infections in some species and rapid death in others. The change in virulence was highly predictable from the host phylogeny, with hosts clustering together in distinct clades displaying high or low virulence. High levels of virulence are associated with high viral loads, and this may determine the transmission rate of the virus.

Estimating the ability of plants to plastically track temperature-mediated shifts in the spring phenological optimum.

One consequence of rising spring temperatures is that the optimum timing of key life-history events may advance. Where this is the case, a population's fate may depend on the degree to which it is able to track a change in the optimum timing either via plasticity or via adaptation. Estimating the effect that temperature change will have on optimum timing using standard approaches is logistically challenging, with the result that very few estimates of this important parameter exist. Here we adopt an alternative statistical method that substitutes space for time to estimate the temperature sensitivity of the optimum timing of 22 plant species based on >200 000 spatiotemporal phenological observations from across the United Kingdom. We find that first leafing and flowering dates are sensitive to forcing (spring) temperatures, with optimum timing advancing by an average of 3 days °C-1 and plastic responses to forcing between -3 and -8 days °C-1 . Chilling (autumn/winter) temperatures and photoperiod tend to be important cues for species with early and late phenology, respectively. For most species, we find that plasticity is adaptive, and for seven species, plasticity is sufficient to track geographic variation in the optimum phenology. For four species, we find that plasticity is significantly steeper than the optimum slope that we estimate between forcing temperature and phenology, and we examine possible explanations for this countergradient pattern, including local adaptation.

The spatial scale of local adaptation in a stochastic environment.

The distribution of phenotypes in space will be a compromise between adaptive plasticity and local adaptation increasing the fit of phenotypes to local conditions and gene flow reducing that fit. Theoretical models on the evolution of quantitative characters on spatially explicit landscapes have only considered scenarios where optimum trait values change as deterministic functions of space. Here, these models are extended to include stochastic spatially autocorrelated aspects to the environment, and consequently the optimal phenotype. Under these conditions, the regression of phenotype on the environmental variable becomes steeper as the spatial scale on which populations are sampled becomes larger. Under certain deterministic models - such as linear clines - the regression is constant. The way in which the regression changes with spatial scale is informative about the degree of phenotypic plasticity, the relative scale of effective gene flow and the environmental dependency of selection. Connections to temporal models are discussed.

The contribution of viral genotype to plasma viral set-point in HIV infection.

Disease progression in HIV-infected individuals varies greatly, and while the environmental and host factors influencing this variation have been widely investigated, the viral contribution to variation in set-point viral load, a predictor of disease progression, is less clear. Previous studies, using transmission-pairs and analysis of phylogenetic signal in small numbers of individuals, have produced a wide range of viral genetic effect estimates. Here we present a novel application of a population-scale method based in quantitative genetics to estimate the viral genetic effect on set-point viral load in the UK subtype B HIV-1 epidemic, based on a very large data set. Analyzing the initial viral load and associated pol sequence, both taken before anti-retroviral therapy, of 8,483 patients, we estimate the proportion of variance in viral load explained by viral genetic effects to be 5.7% (CI 2.8-8.6%). We also estimated the change in viral load over time due to selection on the virus and environmental effects to be a decline of 0.05 log10 copies/mL/year, in contrast to recent studies which suggested a reported small increase in viral load over the last 20 years might be due to evolutionary changes in the virus. Our results suggest that in the UK epidemic, subtype B has a small but significant viral genetic effect on viral load. By allowing the analysis of large sample sizes, we expect our approach to be applicable to the estimation of the genetic contribution to traits in many organisms.

Passerines may be sufficiently plastic to track temperature-mediated shifts in optimum lay date.

Projecting the fates of populations under climate change is one of global change biology's foremost challenges. Here, we seek to identify the contributions that temperature-mediated local adaptation and plasticity make to spatial variation in nesting phenology, a phenotypic trait showing strong responses to warming. We apply a mixed modeling framework to a Britain-wide spatiotemporal dataset comprising >100 000 records of first egg dates from four single-brooded passerine bird species. The average temperature during a specific time period (sliding window) strongly predicts spatiotemporal variation in lay date. All four species exhibit phenological plasticity, advancing lay date by 2-5 days °C(-1) . The initiation of this sliding window is delayed further north, which may be a response to a photoperiod threshold. Using clinal trends in phenology and temperature, we are able to estimate the temperature sensitivity of selection on lay date (B), but our estimates are highly sensitive to the temporal position of the sliding window. If the sliding window is of fixed duration with a start date determined by photoperiod, we find B is tracked by phenotypic plasticity. If, instead, we allow the start and duration of the sliding window to change with latitude, we find plasticity does not track B, although in this case, at odds with theoretical expectations, our estimates of B differ across latitude vs. longitude. We argue that a model combining photoperiod and mean temperature is most consistent with current understanding of phenological cues in passerines, the results from which suggest that each species could respond to projected increases in spring temperatures through plasticity alone. However, our estimates of B require further validation.

Are molecular markers useful predictors of adaptive potential?

Estimates of molecular genetic variation are often used as a cheap and simple surrogate for a population's adaptive potential, yet empirical evidence suggests they are unlikely to be a valid proxy. However, this evidence is based on molecular genetic variation poorly predicting estimates of adaptive potential rather than how well it predicts true values. As a consequence, the relationship has been systematically underestimated and the precision with which it could be measured severely overstated. By collating a large database, and using suitable statistical methods, we obtain a 95% upper bound of 0.26 for the proportion of variance in quantitative genetic variation explained by molecular diversity. The relationship is probably too weak to be useful, but this conclusion must be taken as provisional: less noisy estimates of quantitative genetic variation are required. In contrast, and perhaps surprisingly, current sampling strategies appear sufficient for characterising a population's molecular genetic variation at comparable markers.

A tale of two phylogenies: comparative analyses of ecological interactions.

The evolution of traits involved in ecological interactions such as predator-prey, host-parasite, and plant-pollinator interactions, are likely to be shaped by the phylogenetic history of both parties. We develop generalized linear mixed-effects models (GLMM) that estimate the effect of both parties' phylogenetic history on trait evolution, both in isolation but also in terms of how the two histories interact. Using data on the incidence and abundance of 206 flea species on 121 mammal species, we illustrate our method and compare it to previously used methods for detecting host-parasite coevolution. At large spatial scales we find that the phylogenetic interaction effect was substantial, indicating that related parasite species were more likely to be found on related host species. At smaller spatial scales, and when sampling effort was not controlled for, phylogenetic effects on the number and types of parasite species harbored by hosts were found to dominate. We go on to show that in situations where these additional phylogenetic effects exist, then previous methods have very high Type I error rates when testing for the phylogenetic interaction. Our GLMM method represents a robust and reliable approach to quantify the phylogenetic effects of traits determined by, or defined by, ecological interactions and has the advantage that it can easily be extended and interpreted in a broader context than existing permutation tests.

Host phylogeny determines viral persistence and replication in novel hosts.

Pathogens switching to new hosts can result in the emergence of new infectious diseases, and determining which species are likely to be sources of such host shifts is essential to understanding disease threats to both humans and wildlife. However, the factors that determine whether a pathogen can infect a novel host are poorly understood. We have examined the ability of three host-specific RNA-viruses (Drosophila sigma viruses from the family Rhabdoviridae) to persist and replicate in 51 different species of Drosophilidae. Using a novel analytical approach we found that the host phylogeny could explain most of the variation in viral replication and persistence between different host species. This effect is partly driven by viruses reaching a higher titre in those novel hosts most closely related to the original host. However, there is also a strong effect of host phylogeny that is independent of the distance from the original host, with viral titres being similar in groups of related hosts. Most of this effect could be explained by variation in general susceptibility to all three sigma viruses, as there is a strong phylogenetic correlation in the titres of the three viruses. These results suggest that the source of new emerging diseases may often be predictable from the host phylogeny, but that the effect may be more complex than simply causing most host shifts to occur between closely related hosts.

Differences in spawning date between populations of common frog reveal local adaptation.

Phenotypic differences between populations often correlate with climate variables, resulting from a combination of environment-induced plasticity and local adaptation. Species comprising populations that are genetically adapted to local climatic conditions should be more vulnerable to climate change than those comprising phenotypically plastic populations. Assessment of local adaptation generally requires logistically challenging experiments. Here, using a unique approach and a large dataset (>50,000 observations from across Britain), we compare the covariation in temperature and first spawning dates of the common frog (Rana temporaria) across space with that across time. We show that although all populations exhibit a plastic response to temperature, spawning earlier in warmer years, between-population differences in first spawning dates are dominated by local adaptation. Given climate change projections for Britain in 2050-2070, we project that for populations to remain as locally adapted as contemporary populations will require first spawning date to advance by approximately 21-39 days but that plasticity alone will only enable an advance of approximately 5-9 days. Populations may thus face a microevolutionary and gene flow challenge to advance first spawning date by a further approximately 16-30 days over the next 50 years.

Directional selection and the evolution of breeding date in birds, revisited: Hard selection and the evolution of plasticity.

The mismatch between when individuals breed and when we think they should breed has been a long-standing problem in evolutionary ecology. Price et al. is a classic theory paper in this field and is mainly cited for its most obvious result: if individuals with high nutritional condition breed early, then the advantage of breeding early may be overestimated when information on nutritional condition is absent. Price at al.'s less obvious result is that individuals, on average, are expected to breed later than the optimum. Here, we provide an explanation of their non-intuitive result in terms of hard selection, and go on to show that neither of their results are expected to hold if the relationship between breeding date and nutrition is allowed to evolve. By introducing the assumption that the advantage of breeding early is greater for individuals in high nutritional condition, we show that their most cited result can be salvaged. However, individuals, on average, are expected to breed earlier than the optimum, not later. More generally, we also show that the hard selection mechanisms that underpin these results have major implications for the evolution of plasticity: when environmental heterogeneity becomes too great, plasticity is selected against, prohibiting the evolution of generalists.

Decomposing phenotypic skew and its effects on the predicted response to strong selection.

The major frameworks for predicting evolutionary change assume that a phenotype's underlying genetic and environmental components are normally distributed. However, the predictions of these frameworks may no longer hold if distributions are skewed. Despite this, phenotypic skew has never been decomposed, meaning the fundamental assumptions of quantitative genetics remain untested. Here we demonstrate that the substantial phenotypic skew in the body size of juvenile blue tits (Cyanistes caeruleus) is driven by environmental factors. Although skew had little impact on our predictions of selection response in this case, our results highlight the impact of skew on the estimation of inheritance and selection. Specifically, the nonlinear parent-offspring regressions induced by skew, alongside selective disappearance, can strongly bias estimates of heritability. The ubiquity of skew and strong directional selection on juvenile body size imply that heritability is commonly overestimated, which may in part explain the discrepancy between predicted and observed trait evolution.

The misuse of BLUP in ecology and evolution.

Best linear unbiased prediction (BLUP) is a method for obtaining point estimates of a random effect in a mixed effect model. Over the past decade it has been used extensively in ecology and evolutionary biology to predict individual breeding values and reaction norms. These predictions have been used to infer natural selection, evolutionary change, spatial-genetic patterns, individual reaction norms, and frailties. In this article we show analytically and through simulation and example why BLUP often gives anticonservative and biased estimates of evolutionary and ecological parameters. Although some concerns with BLUP methodology have been voiced before, the scale and breadth of the problems have probably not been widely appreciated. Bias arises because BLUPs are often used to estimate effects that are not explicitly accounted for in the model used to make the predictions. In these cases, predicted breeding values will often say more about phenotypic patterns than the genetic patterns of interest. An additional problem is that BLUPs are point estimates of quantities that are usually known with little certainty. Failure to account for this uncertainty in subsequent tests can lead to both bias and extreme anticonservatism. We demonstrate that restricted maximum likelihood and Bayesian solutions exist for these problems and show how unbiased and powerful tests can be derived that adequately quantify uncertainty. Of particular utility is a new test for detecting evolutionary change that not only accounts for prediction error in breeding values but also accounts for drift. To illustrate the problem, we apply these tests to long-term data on the Soay sheep (Ovis aries) and the great tit (Parus major) and show that previously reported temporal trends in breeding values are not supported.

Comparing parentage inference software: reanalysis of a red deer pedigree.

Knowledge of the parentage of individuals is required to address a variety of questions concerning the evolutionary dynamics of wild populations. A major advance in parentage inference in natural populations has been the use of molecular markers and the development of statistical methods to analyse these data. Cervus, one of the most widely used parentage inference programs, uses molecular data to determine parent-offspring relationships. However, Cervus does not make use of all available information: additional phenotypic information may exist predicting parent-offspring relationships, and additional genetic information may be exploited by simultaneously considering multiple types of relationships rather than just pairwise or just parent-offspring relationships. Here we reanalyse data from a wild red deer population using two programs capable of using this additional information, MasterBayes and COLONY2, and quantify the impact of these alternative approaches by comparison with a 'known pedigree' estimated using a larger suite of microsatellite makers for a subset of the population. The use of phenotypic information and multiple relationships increased the number of correct assignments. We highlight the differences between programs, particularly the use of population- rather than individual-level statistical confidence in Cervus. We conclude that the use of additional information allows MasterBayes and COLONY2 to assign more correct paternities, whereas their use of individual- rather than population-level confidence generates fewer erroneous assignments. We suggest that maximal information may be gained by combining outputs from different programs. Higher accuracy and completeness of pedigree information will improve parameters estimated from pedigree information in studies of natural populations.

No evidence for sibling or parent-offspring coadaptation in a wild population of blue tits, despite high power.

Parent and offspring behaviors are expected to act as both the agents and targets of selection. This may generate parent-offspring coadaptation in which parent and offspring behaviors become genetically correlated in a way that increases inclusive fitness. Cross-fostering has been used to study parent-offspring coadaptation, with the prediction that offspring raised by non-relatives, or parents raising non-relatives, should suffer fitness costs. Using long-term data from more than 400 partially crossed broods of blue tits (Cyanistes caeruleus), we show that there is no difference in mass or survival between crossed and non-crossed chicks. However, previous studies for which the evidence for parent-offspring coadaptation is strongest compare chicks from fully crossed broods with those from non-crossed broods. When parent-offspring coadaptation acts at the level of the brood then partial cross-fostering experiments are not expected to show evidence of coadaptation. To test this, we performed an additional experiment (163 broods) in which clutches were either fully crossed, non-crossed, or partially crossed. In agreement with the long-term data, there was no evidence for parent-offspring coadaptation on offspring fitness despite high power. In addition there was no evidence of effects on parental fitness, nor evidence of sibling coadaptation, although the power of these tests was more modest.

The evolution of phenotypic plasticity when environments fluctuate in time and space.

Most theoretical studies have explored the evolution of plasticity when the environment, and therefore the optimal trait value, varies in time or space. When the environment varies in time and space, we show that genetic adaptation to Markovian temporal fluctuations depends on the between-generation autocorrelation in the environment in exactly the same way that genetic adaptation to spatial fluctuations depends on the probability of philopatry. This is because both measure the correlation in parent-offspring environments and therefore the effectiveness of a genetic response to selection. If the capacity to genetically respond to selection is stronger in one dimension (e.g., space), then plasticity mainly evolves in response to fluctuations in the other dimension (e.g., time). If the relationships between the environments of development and selection are the same in time and space, the evolved plastic response to temporal fluctuations is useful in a spatial context and genetic differentiation in space is reduced. However, if the relationships between the environments of development and selection are different, the optimal level of plasticity is different in the two dimensions. In this case, the plastic response that evolves to cope with temporal fluctuations may actually be maladaptive in space, resulting in the evolution of hyperplasticity or negative plasticity. These effects can be mitigated by spatial genetic differentiation that acts in opposition to plasticity resulting in counter-gradient variation. These results highlight the difficulty of making space-for-time substitutions in empirical work but identify the key parameters that need to be measured in order to test whether space-for-time substitutions are likely to be valid.