The Number and Pattern of Viral Genomic Reassortments are not Necessarily Identifiable from Segment Trees.

Reassortment is an evolutionary process common in viruses with segmented genomes. These viruses can swap whole genomic segments during cellular co-infection, giving rise to novel progeny formed from the mixture of parental segments. Since large-scale genome rearrangements have the potential to generate new phenotypes, reassortment is important to both evolutionary biology and public health research. However, statistical inference of the pattern of reassortment events from phylogenetic data is exceptionally difficult, potentially involving inference of general graphs in which individual segment trees are embedded. In this paper, we argue that, in general, the number and pattern of reassortment events are not identifiable from segment trees alone, even with theoretically ideal data. We call this fact the fundamental problem of reassortment, which we illustrate using the concept of the "first-infection tree," a potentially counterfactual genealogy that would have been observed in the segment trees had no reassortment occurred. Further, we illustrate four additional problems that can arise logically in the inference of reassortment events and show, using simulated data, that these problems are not rare and can potentially distort our observation of reassortment even in small data sets. Finally, we discuss how existing methods can be augmented or adapted to account for not only the fundamental problem of reassortment, but also the four additional situations that can complicate the inference of reassortment.

Inferring Viral Transmission Time from Phylogenies for Known Transmission Pairs.

When the time of an HIV transmission event is unknown, methods to identify it from virus genetic data can reveal the circumstances that enable transmission. We developed a single-parameter Markov model to infer transmission time from an HIV phylogeny constructed of multiple virus sequences from people in a transmission pair. Our method finds the statistical support for transmission occurring in different possible time slices. We compared our time-slice model results to previously described methods: a tree-based logical transmission interval, a simple parsimony-like rules-based method, and a more complex coalescent model. Across simulations with multiple transmitted lineages, different transmission times relative to the source's infection, and different sampling times relative to transmission, we found that overall our time-slice model provided accurate and narrower estimates of the time of transmission. We also identified situations when transmission time or direction was difficult to estimate by any method, particularly when transmission occurred long after the source was infected and when sampling occurred long after transmission. Applying our model to real HIV transmission pairs showed some agreement with facts known from the case investigations. We also found, however, that uncertainty on the inferred transmission time was driven more by uncertainty from time calibration of the phylogeny than from the model inference itself. Encouragingly, comparable performance of the Markov time-slice model and the coalescent model-which make use of different information within a tree-suggests that a new method remains to be described that will make full use of the topology and node times for improved transmission time inference.

Modeling the evolution of segment trees reveals deficiencies in current inferential methods for genomic reassortment.

Reassortment is an evolutionary process common in viruses with segmented genomes. These viruses can swap whole genomic segments during cellular co-infection, giving rise to new viral variants. Large-scale genome rearrangements, such as reassortment, have the potential to quickly generate new phenotypes, making the understanding of viral reassortment important to both evolutionary biology and public health research. In this paper, we argue that reassortment cannot be reliably inferred from incongruities between segment phylogenies using the established remove-and-rejoin or coalescent approaches. We instead show that reassortment must be considered in the context of a broader population process that includes the dynamics of the infected hosts. Using illustrative examples and simulation we identify four types of evolutionary events that are difficult or impossible to reconstruct with incongruence-based methods. Further, we show that these specific situations are very common and will likely occur even in small samples. Finally, we argue that existing methods can be augmented or modified to account for all the problematic situations that we identify in this paper. Robust assessment of the role of reassortment in viral evolution is difficult, and we hope to provide conceptual clarity on some important methodological issues that can arise in the development of the next generation of tools for studying reassortment.

Inferring viral transmission time from phylogenies for known transmission pairs.

When the time of an HIV transmission event is unknown, methods to identify it from virus genetic data can reveal the circumstances that enable transmission. We developed a single-parameter Markov model to infer transmission time from an HIV phylogeny constructed of multiple virus sequences from people in a transmission pair. Our method finds the statistical support for transmission occurring in different possible time slices. We compared our time-slice model results to previously-described methods: a tree-based logical transmission interval, a simple parsimony-like rules-based method, and a more complex coalescent model. Across simulations with multiple transmitted lineages, different transmission times relative to the source's infection, and different sampling times relative to transmission, we found that overall our time-slice model provided accurate and narrower estimates of the time of transmission. We also identified situations when transmission time or direction was difficult to estimate by any method, particularly when transmission occurred long after the source was infected and when sampling occurred long after transmission. Applying our model to real HIV transmission pairs showed some agreement with facts known from the case investigations. We also found, however, that uncertainty on the inferred transmission time was driven more by uncertainty from time-calibration of the phylogeny than from the model inference itself. Encouragingly, comparable performance of the Markov time-slice model and the coalescent model-which make use of different information within a tree-suggests that a new method remains to be described that will make full use of the topology and node times for improved transmission time inference.

Swift and extensive Omicron outbreak in China after sudden exit from 'zero-COVID' policy.

In late 2022, China transitioned from a strict 'zero-COVID' policy to rapidly abandoning nearly all interventions and data reporting. This raised great concern about the presumably-rapid but unreported spread of the SARS-CoV-2 Omicron variant in a very large population of very low pre-existing immunity. By modeling a combination of case count and survey data, we show that Omicron spread extremely rapidly, at a rate of 0.42/day (95% credibility interval: [0.35, 0.51]/day), translating to an epidemic doubling time of 1.6 days ([1.6, 2.0] days) after the full exit from zero-COVID on Dec. 7, 2022. Consequently, we estimate that the vast majority of the population (97% [95%, 99%], sensitivity analysis lower limit of 90%) was infected during December, with the nation-wide epidemic peaking on Dec. 23. Overall, our results highlight the extremely high transmissibility of the variant and the importance of proper design of intervention exit strategies to avoid large infection waves.

Effects of Plasticity on Elevational Range Size and Species Richness.

AbstractElevational ranges within many taxa are greater in the north temperate region than the tropics. Two hypotheses to explain the pattern are, first, that large elevational ranges in the temperate region arise because species have evolved broad tolerance curves in response to seasonality and, second, that a low diversification rate in the temperate region (speciation minus extinction) has led to relatively few species, each of which occupies a large elevational range in the absence of competitors (character release). We build a quantitative genetic model of selection on a phenotypic trait, whereby increased tolerance is modeled as arising from plasticity in the trait. We show that broad tolerances result in evolution of large elevational ranges because they induce shallower genotypic clines and hence reduced maladaptive gene flow. The evolution of large elevational ranges results in relatively few competing species arranged along the elevational gradient at a species carrying capacity. In such saturated communities, species have much elevational overlap. In contrast, in similar-sized communities that could accommodate many more species, the resulting character release is associated with smaller elevational overlaps. Empirical assessment of these predictions should contribute to assessing any role for ecological limits in driving the latitudinal diversity gradient in species richness.

Estimating the strength of selection for new SARS-CoV-2 variants.

Controlling the SARS-CoV-2 pandemic becomes increasingly challenging as the virus adapts to human hosts through the continual emergence of more transmissible variants. Simply observing that a variant is increasing in frequency is relatively straightforward, but more sophisticated methodology is needed to determine whether a new variant is a global threat and the magnitude of its selective advantage. We present two models for quantifying the strength of selection for new and emerging variants of SARS-CoV-2 relative to the background of contemporaneous variants. These methods range from a detailed model of dynamics within one country to a broad analysis across all countries, and they include alternative explanations such as migration and drift. We find evidence for strong selection favoring the D614G spike mutation and B.1.1.7 (Alpha), weaker selection favoring B.1.351 (Beta), and no advantage of R.1 after it spreads beyond Japan. Cutting back data to earlier time horizons reveals that uncertainty is large very soon after emergence, but that estimates of selection stabilize after several weeks. Our results also show substantial heterogeneity among countries, demonstrating the need for a truly global perspective on the molecular epidemiology of SARS-CoV-2.

Estimating the strength of selection for new SARS-CoV-2 variants.

Controlling the SARS-CoV-2 pandemic becomes increasingly challenging as the virus adapts to human hosts through the continual emergence of more transmissible variants. Simply observing that a variant is increasing in frequency is relatively straightforward, but more sophisticated methodology is needed to determine whether a new variant is a global threat and the magnitude of its selective advantage. We present three methods for quantifying the strength of selection for new and emerging variants of SARS-CoV-2 relative to the background of contemporaneous variants. These methods range from a detailed model of dynamics within one country to a broad analysis across all countries, and they include alternative explanations such as migration and drift. We find evidence for strong selection favoring the D614G spike mutation and B.1.1.7 (Alpha), weaker selection favoring B.1.351 (Beta), and no advantage of R.1 after it spreads beyond Japan. Cutting back data to earlier time horizons reveals large uncertainty very soon after emergence, but that estimates of selection stabilize after several weeks. Our results also show substantial heterogeneity among countries, demonstrating the need for a truly global perspective on the molecular epidemiology of SARS-CoV-2.

Diversification or Collapse of Self-Incompatibility Haplotypes as a Rescue Process.

AbstractIn angiosperm self-incompatibility systems, pollen with an allele matching the pollen recipient at the self-incompatibility locus is rejected. Extreme allelic polymorphism is maintained by frequency-dependent selection favoring rare alleles. However, two challenges result in a chicken-or-egg problem for the spread of a new allele (a tightly linked haplotype in this case) under the widespread "collaborative non-self-recognition" mechanism. A novel pollen function mutation alone would merely grant compatibility with a nonexistent style function allele: a neutral change at best. A novel pistil function mutation alone could be fertilized only by pollen with a nonexistent pollen function allele: a deleterious change that would reduce seed set to zero. However, a pistil function mutation complementary to a previously neutral pollen mutation may spread if it restores self-incompatibility to a self-compatible intermediate. We show that novel haplotypes can also drive elimination of existing ones with fewer siring opportunities. We calculate relative probabilities of increase and collapse in haplotype number given the initial collection of incompatibility haplotypes and the population gene conversion rate. Expansion in haplotype number is possible when population gene conversion rate is large, but large contractions are likely otherwise. A Markov chain model derived from these expansion and collapse probabilities generates a stable haplotype number distribution in the realistic range of 10-40 under plausible parameters. However, smaller populations might lose many haplotypes beyond those lost by chance during bottlenecks.

Heterogeneity in the rate of molecular sequence evolution substantially impacts the accuracy of detecting shifts in diversification rates.

As species richness varies along the tree of life, there is a great interest in identifying factors that affect the rates by which lineages speciate or go extinct. To this end, theoretical biologists have developed a suite of phylogenetic comparative methods that aim to identify where shifts in diversification rates had occurred along a phylogeny and whether they are associated with some traits. Using these methods, numerous studies have predicted that speciation and extinction rates vary across the tree of life. In this study, we show that asymmetric rates of sequence evolution lead to systematic biases in the inferred phylogeny, which in turn lead to erroneous inferences regarding lineage diversification patterns. The results demonstrate that as the asymmetry in sequence evolution rates increases, so does the tendency to select more complicated models that include the possibility of diversification rate shifts. These results thus suggest that any inference regarding shifts in diversification pattern should be treated with great caution, at least until any biases regarding the molecular substitution rate have been ruled out.

Memory in Trait Macroevolution.

The history of a trait within a lineage may influence its future evolutionary trajectory, but macroevolutionary theory of this process is not well developed. For example, consider the simplified binary trait of living in cave versus surface habitat. The longer a species has been cave dwelling, the more accumulated loss of vision, pigmentation, and defense may restrict future adaptation if the species encounters the surface environment. However, the Markov model of discrete trait evolution that is widely adopted in phylogenetics does not allow the rate of cave-to-surface transition to decrease with longer duration as a cave dweller. Here we describe three models of evolution that remove this memoryless constraint, using a renewal process to generalize beyond the typical Poisson process of discrete trait macroevolution. We then show how the two-state renewal process can be used for inference, and we investigate the potential of phylogenetic comparative data to reveal different influences of trait duration, or memory in trait evolution. We hope that such approaches may open new avenues for modeling trait evolution and for broad comparative tests of hypotheses that some traits become entrenched.

Interaction among ploidy, breeding system and lineage diversification.

If particular traits consistently affect rates of speciation and extinction, broad macroevolutionary patterns can be interpreted as consequences of selection at high levels of the biological hierarchy. Identifying traits associated with diversification rates is difficult because of the wide variety of characters under consideration and the statistical challenges of testing for associations from comparative phylogenetic data. Ploidy (diploid vs polyploid states) and breeding system (self-incompatible vs self-compatible states) are both thought to be drivers of differential diversification in angiosperms. We fit 29 diversification models to extensive trait and phylogenetic data in Solanaceae and investigate how speciation and extinction rate differences are associated with ploidy, breeding system, and the interaction between these traits. We show that diversification patterns in Solanaceae are better explained by breeding system and an additional unobserved factor, rather than by ploidy. We also find that the most common evolutionary pathway to polyploidy in Solanaceae occurs via direct breakdown of self-incompatibility by whole genome duplication, rather than indirectly via breakdown followed by polyploidization. Comparing multiple stochastic diversification models that include complex trait interactions alongside hidden states enhances our understanding of the macroevolutionary patterns in plant phylogenies.

Detecting the macroevolutionary signal of species interactions.

Species interactions lie at the heart of many theories of macroevolution, from adaptive radiation to the Red Queen. Although some theories describe the imprint that interactions will have over long timescales, we are still missing a comprehensive understanding of the effects of interactions on macroevolution. Current research shows strong evidence for the impact of interactions on macroevolutionary patterns of trait evolution and diversification, yet many macroevolutionary studies have only a tenuous relationship to ecological studies of interactions over shorter timescales. We review current research in this area, highlighting approaches that explicitly model species interactions and connect them to broad-scale macroevolutionary patterns. We also suggest that progress has been made by taking an integrative interdisciplinary look at individual clades. We focus on African cichlids as a case study of how this approach can be fruitful. Overall, although the evidence for species interactions shaping macroevolution is strong, further work using integrative and model-based approaches is needed to spur progress towards understanding the complex dynamics that structure communities over time and space.

The evolutionary response of mating system to heterosis.

Isolation allows populations to diverge and to fix different alleles. Deleterious alleles that reach locally high frequencies contribute to genetic load, especially in inbred or selfing populations, in which selection is relaxed. In the event of secondary contact, the recessive portion of the genetic load is masked in the hybrid offspring, producing heterosis. This advantage, only attainable through outcrossing, should favour evolution of greater outcrossing even if inbreeding depression has been purged from the contributing populations. Why, then, are selfing-to-outcrossing transitions not more common? To evaluate the evolutionary response of mating system to heterosis, we model two monomorphic populations of entirely selfing individuals, introduce a modifier allele that increases the rate of outcrossing and investigate whether the heterosis among populations is sufficient for the modifier to invade and fix. We find that the outcrossing mutation invades for many parameter choices, but it rarely fixes unless populations harbour extremely large unique fixed genetic loads. Reversions to outcrossing become more likely as the load becomes more polygenic, or when the modifier appears on a rare background, such as by dispersal of an outcrossing genotype into a selfing population. More often, the outcrossing mutation instead rises to moderate frequency, which allows recombination in hybrids to produce superior haplotypes that can spread without the mutation's further assistance. The transience of heterosis can therefore explain why secondary contact does not commonly yield selfing-to-outcrossing transitions.

Meiotic drive shapes rates of karyotype evolution in mammals.

Chromosome number is perhaps the most basic characteristic of a genome, yet generalizations that can explain the evolution of this trait across large clades have remained elusive. Using karyotype data from over 1000 mammals, we developed and applied a phylogenetic model of chromosome evolution that links chromosome number changes with karyotype morphology. Using our model, we infer that rates of chromosome number evolution are significantly lower in species with karyotypes that consist of either all bibrachial or all monobrachial chromosomes than in species with a mix of both types of morphologies. We suggest that species with homogeneous karyotypes may represent cases where meiotic drive acts to stabilize the karyotype, favoring the chromosome morphologies already present in the genome. In contrast, rapid bouts of chromosome number evolution in taxa with mixed karyotypes may indicate that a switch in the polarity of female meiotic drive favors changes in chromosome number. We do not find any evidence that karyotype morphology affects rates of speciation or extinction. Furthermore, we document that switches in meiotic drive polarity are likely common and have occurred in most major clades of mammals, and that rapid remodeling of karyotypes may be more common than once thought.

The origin and evolution of coral species richness in a marine biodiversity hotspot.

The Coral Triangle (CT) region of the Indo-Pacific realm harbors an extraordinary number of species, with richness decreasing away from this biodiversity hotspot. Despite multiple competing hypotheses, the dynamics underlying this regional diversity pattern remain poorly understood. Here, we use a time-calibrated evolutionary tree of living reef coral species, their current geographic ranges, and model-based estimates of regional rates of speciation, extinction, and geographic range shifts to show that origination rates within the CT are lower than in surrounding regions, a result inconsistent with the long-standing center of origin hypothesis. Furthermore, endemism of coral species in the CT is low, and the CT endemics are older than relatives found outside this region. Overall, our model results suggest that the high diversity of reef corals in the CT is largely due to range expansions into this region of species that evolved elsewhere. These findings strongly support the notion that geographic range shifts play a critical role in generating species diversity gradients. They also show that preserving the processes that gave rise to the striking diversity of corals in the CT requires protecting not just reefs within the hotspot, but also those in the surrounding areas.

Self-compatibility is over-represented on islands.

Because establishing a new population often depends critically on finding mates, individuals capable of uniparental reproduction may have a colonization advantage. Accordingly, there should be an over-representation of colonizing species in which individuals can reproduce without a mate, particularly in isolated locales such as oceanic islands. Despite the intuitive appeal of this colonization filter hypothesis (known as Baker's law), more than six decades of analyses have yielded mixed findings. We assembled a dataset of island and mainland plant breeding systems, focusing on the presence or absence of self-incompatibility. Because this trait enforces outcrossing and is unlikely to re-evolve on short timescales if it is lost, breeding system is especially likely to reflect the colonization filter. We found significantly more self-compatible species on islands than mainlands across a sample of > 1500 species from three widely distributed flowering plant families (Asteraceae, Brassicaceae and Solanaceae). Overall, 66% of island species were self-compatible, compared with 41% of mainland species. Our results demonstrate that the presence or absence of self-incompatibility has strong explanatory power for plant geographical patterns. Island floras around the world thus reflect the role of a key reproductive trait in filtering potential colonizing species in these three plant families.

FiSSE: A simple nonparametric test for the effects of a binary character on lineage diversification rates.

It is widely assumed that phenotypic traits can influence rates of speciation and extinction, and several statistical approaches have been used to test for correlations between character states and lineage diversification. Recent work suggests that model-based tests of state-dependent speciation and extinction are sensitive to model inadequacy and phylogenetic pseudoreplication. We describe a simple nonparametric statistical test ("FiSSE") to assess the effects of a binary character on lineage diversification rates. The method involves computing a test statistic that compares the distributions of branch lengths for lineages with and without a character state of interest. The value of the test statistic is compared to a null distribution generated by simulating character histories on the observed phylogeny. Our tests show that FiSSE can reliably infer trait-dependent speciation on phylogenies of several hundred tips. The method has low power to detect trait-dependent extinction but can infer state-dependent differences in speciation even when net diversification rates are constant. We assemble a range of macroevolutionary scenarios that are problematic for likelihood-based methods, and we find that FiSSE does not show similarly elevated false positive rates. We suggest that nonparametric statistical approaches, such as FiSSE, provide an important complement to formal process-based models for trait-dependent diversification.

Macroevolutionary synthesis of flowering plant sexual systems.

Sexual system is a key determinant of genetic variation and reproductive success, affecting evolution within populations and within clades. Much research in plants has focused on evolutionary transitions away from the most common state of hermaphroditism and toward the rare state of dioecy (separate sexes). Rather than transitions predominantly toward greater sexual differentiation, however, evolution may proceed in the direction of lesser sexual differentiation. We analyzed the macroevolutionary dynamics of sexual system in angiosperm genera that contain both dioecious and nondioecious species. Our phylogenetic analyses encompass a total of 2145 species from 40 genera. Overall, we found little evidence that rates of sexual system transitions are greater in any direction. Counting the number of inferred state changes revealed a mild prevalence of transitions away from hermaphroditism and away from dioecy, toward states of intermediate sexual differentiation. We identify genera in which future studies of sexual system evolution might be especially productive, and we discuss how integrating genetic or population-level studies of sexual system could improve the power of phylogenetic comparative analyses. Our work adds to the evidence that different selective pressures and constraints act in different groups, helping maintain the variety of sexual systems observed among plants.

Phylogenetic evidence for cladogenetic polyploidization in land plants.

PREMISE OF THE STUDY: Polyploidization is a common and recurring phenomenon in plants and is often thought to be a mechanism of "instant speciation". Whether polyploidization is associated with the formation of new species (cladogenesis) or simply occurs over time within a lineage (anagenesis), however, has never been assessed systematically. METHODS: We tested this hypothesis using phylogenetic and karyotypic information from 235 plant genera (mostly angiosperms). We first constructed a large database of combined sequence and chromosome number data sets using an automated procedure. We then applied likelihood models (ClaSSE) that estimate the degree of synchronization between polyploidization and speciation events in maximum likelihood and Bayesian frameworks. KEY RESULTS: Our maximum likelihood analysis indicated that 35 genera supported a model that includes cladogenetic transitions over a model with only anagenetic transitions, whereas three genera supported a model that incorporates anagenetic transitions over one with only cladogenetic transitions. Furthermore, the Bayesian analysis supported a preponderance of cladogenetic change in four genera but did not support a preponderance of anagenetic change in any genus. CONCLUSIONS: Overall, these phylogenetic analyses provide the first broad confirmation that polyploidization is temporally associated with speciation events, suggesting that it is indeed a major speciation mechanism in plants, at least in some genera.