Biology subjects

May, M. R.

Publications and source records attributed to May, M. R..

15 recordsLinked to original sources

bioRxiv2026

An explicit birth-death-reticulation model for studying the diversification of phylogenetic networks

Much of the history of life is reticulate and better represented by phylogenetic networks than by strictly bifurcating trees. Understanding the processes that generated that history thus requires models of diversification (speciation and extinction) that incorporate reticulation. However, we currently lack tractable reticulate diversification models. Here we develop a simple birth-death-reticulation model that includes unidirectional and bidirectional gene flow, homoploid hybrid speciation, and allopolyploidization, and derive a practical probability density function for networks under this model. We demonstrate that the model can extract information about reticulation processes from known phylogenetic networks. We also explore the empirical utility of the model using an allopolyploid network of ferns of the family Cystopteridaceae, revealing evidence in favor of the controversial hypothesis that polyploids have lower diversification rates than their diploid relatives. While the model represents an advance in our ability to learn about the diversification of reticulate lineages, we also identify significant statistical, computational, and empirical challenges that face this nascent framework.

evolutionary biology↗

bioRxiv2025

The Goldilocks effect drives plant diversification on middle-aged Hawaiian islands

Islands are natural laboratories for studying dispersal, speciation, and extinction, yet the historical dynamics of many insular radiations remain poorly understood because of the difficulty aligning the tempo and mode of diversification with paleogeography during phylogenetic inference. We introduce a phylogenetic modeling framework, named TimeFIG, that combines data about species ranges and genetic variation with paleogeographic information to simultaneously infer divergence times, ancestral ranges, and historical diversification rates, without relying on fossils to time-calibrate the phylogeny. Applying TimeFIG to the spectacular radiation of Hawaiian Kadua (Rubiaceae) points to colonization of either modern Kaua'i or ancient now-eroded islands, with island isolation as the strongest correlate of dispersal, and with a tendency for net diversification to be highest on "middle-aged" islands. Modeling diversification within an explicit spatiotemporal context, while accounting for historical uncertainty regarding the timing and placement of phylogenetic and biogeographic events, enables the rigorous testing of foundational hypotheses in island biology and evolutionary theory for clades beyond Kadua.

evolutionary biology↗

bioRxiv2025

Brain size dependent speciation and extinction rates in birds and the cognitive buffer hypothesis

Both brain and body size vary greatly across birds, with both traits hypothesized to play a key role in diversification patterns across the group. Larger brains facilitate the evolution of greater behavioural plasticity, which could facilitate diversification in two ways, either by driving increased speciation (behavioural drive) or by making lineages more resilient to extinction (cognitive buffer). Here, we model brain size dependent diversification dynamics from published endocranial volume data for a sample of 2291 extant and fossil bird taxa, jointly modelling speciation rate, extinction rate and fossilisation rate separately for perching birds and other groups. We find that increasing relative brain size primarily increases diversification rate through decreasing extinction rate, supporting the cognitive buffer hypothesis and suggesting that larger brains in birds promote diversification by making species more resilient to extinction. Although speciation and extinction are dependent on relative brain size in both perching birds and other groups, this dependence is non-linear. In perching birds, the highest diversification rates are found over a narrow range of relative brain sizes, in contrast to other bird groups which show lower diversification rates over a broader range of relative brain sizes. SignificanceThe potential for speciation and extinction are thought to be shaped by key phenotypic traits. In birds, brain size is one important trait hypothesized to have an impact on diversification. Testing this hypothesis requires the evolution of brain size, speciation rate, and extinction rate to be jointly modelled across the bird phylogeny. The inclusion of information on past diversity has been shown to be important in inferring diversification patterns, and so we include not only data from a broad sample of living birds but also information from the fossil record. Our study reveals patterns of brain size dependent diversification in birds which are consistent with the cognitive buffer hypothesis, with higher relative brain sizes being associated with lower extinction rates.

evolutionary biology↗

bioRxiv2024

Quantifying transcriptome turnover on phylogenies bymodeling gene expression as a binary trait

Changes in gene expression are a key driver of phenotypic evolution, leading to a persistent interest in the evolution of transcriptomes. Traditionally, gene expression is modeled as a continuous trait, leaving qualitative transitions largely unexplored. In this paper, we detail the development of new Bayesian inference techniques to study the evolutionary turnover of organ-specific transcriptomes, which we define as instances where orthologous genes gain or lose expression in a particular organ. To test these techniques, we analyze the transcriptomes of two male reproductive organs, testes and accessory glands, across 11 species of the Drosophila melanogaster species group. We first discretize gene expression states by estimating the probability that each gene is expressed in each organ and species. We then define a phylogenetic model of correlated transcriptome evolution in two or more organs and fit it to the expression state data. Inferences under this model show that many genes have gained and lost expression in each organ, and that the two organs experienced accelerated transcriptome turnover on different branches of the Drosophila phylogeny.

evolutionary biology↗

bioRxiv2024

Assessing the Adequacy of Morphological Models used in Palaeobiology

Reconstructing the evolutionary history of different groups of organisms provides insight into how life originated and diversified on Earth. Phylogenetic trees are commonly used to estimate this evolutionary history, providing a hypothesis of the events. Within Bayesian phylogenetics a major step in estimating a tree is in choosing an appropriate model of character evolution. In the case of most extinct species, our only source of information to decipher their phylogenetic relationships is through the morphology of fossils. We therefore use a model of morphological character evolution, the most common of which being the Mk Lewis model. While it is frequently used in palaeobiology, it is not known whether the simple Mk substitution model, or any extensions to it, provide a sufficiently good description of the process of morphological evolution. To determine whether or not the Mk model is appropriate for fossil data we used posterior predictive simulations, a model adequacy approach, to estimate absolute fit of the model to morphological data sets. We first investigate the impact that different versions of the Mk model have on key parameter estimates using tetrapod data sets. We show that choice of substitution model has an impact on both topology and branch lengths, highlighting the importance of model choice. Next, we use simulations to investigate the power of posterior predictive simulations for morphology. Having validated this approach we show that current variations of the Mk model are in fact performing adequately in capturing the evolutionary dynamics that generated our data. We do not find any preference for a particular model extension across multiple data sets, indicating that there is no one size fits all when it comes to morphological data and that careful consideration should be given to choosing models of discrete character evolution. By using suitable models of character evolution, we can increase our confidence in our phylogenetic estimates, which should in turn allow us to gain more accurate insights into the evolutionary history of both extinct and extant taxa.

paleontology↗

bioRxiv2023

Detecting shifts in the mode of chromosomal speciation across the cosmopolitan plant lineage Carex

O_LIThe effects of single chromosome number change--dysploidy--mediating diversification remain poorly understood. Dysploidy modifies recombination rates, linkage, or reproductive isolation, especially for one-fifth of all eukaryote lineages with holocentric chromosomes. Dysploidy effects on diversification have not been estimated because modeling chromosome numbers linked to diversification with heterogeneity along phylogenies is quantitatively challenging. C_LIO_LIWe propose a new state-dependent diversification model of chromosome evolution that links diversification rates to dysploidy rates considering heterogeneity and differentiates between anagenetic and cladogenetic changes. We apply this model to Carex (Cyperaceae), a cosmopolitan flowering plant clade with holocentric chromosomes. C_LIO_LIWe recover two distinct modes of chromosomal evolution and speciation in Carex. In one diversification mode, dysploidy occurs frequently and drives faster diversification rates. In the other mode, dysploidy is rare and diversification is driven by hidden, unmeasured factors. When we use a model that excludes hidden states, we mistakenly infer a strong, uniform positive effect of dysploidy on diversification, showing that standard models may lead to confident but incorrect conclusions about diversification. C_LIO_LIThis study demonstrates that dysploidy can have a significant role in large plant clade speciation despite the presence of other unmeasured factors that simultaneously affect diversification. C_LI

evolutionary biology↗

bioRxiv2022

PrioriTree: a utility for improving phylodynamic analyses in BEAST

SummaryPhylodynamic methods are central to studies of the geographic and demographic history of disease outbreaks. Inference under discrete-geographic phylodynamic models--which involve many parameters that must be inferred from minimal information--is inherently sensitive to our prior beliefs about the model parameters. We present an interactive utility, PrioriTree, to help researchers identify and accommodate prior sensitivity in discrete-geographic inferences. Specifically, PrioriTree provides a suite of functions to generate input files for--and summarize output from--BEAST analyses for performing robust Bayesian inference, data-cloning analyses, and assessing the relative and absolute fit of candidate discrete-geographic (prior) models to empirical datasets. Availability and ImplementationPrioriTree is distributed as an R package available at https://github.com/jsigao/prioritree, with a comprehensive user manual provided at https://bookdown.org/jsigao/prioritree_manual/. Contactjsigao@ucdavis.edu

evolutionary biology↗

bioRxiv2021

Unearthing modes of climatic adaptation in underground storage organs across Liliales

Testing adaptive hypotheses about how continuous traits evolve in association with developmentally-structured discrete traits, while accounting for the confounding influence of other, hidden, evolutionary forces, remains a challenge in evolutionary biology. For example, geophytes are herbaceous plants--with underground buds--that use underground storage organs (USOs) to survive extended periods of unfavorable conditions. Such plants have evolved multiple times independently across all major vascular plant lineages. Even within closely related lineages, however, geophytes show impressive variation in the morphological modifications and structures (i.e., "types" of USOs) that allow them to survive underground. Despite the developmental and structural complexity of USOs, the prevailing hypothesis is that they represent convergent evolutionary "solutions" to a common ecological problem, though some recent research has drawn this conclusion into question. We extend existing phylogenetic comparative methods to test for links between the hierarchical discrete morphological traits associated with USOs and adaptation to environmental variables, using a phylogeny of 621 species in Liliales. We found that plants with different USO type do not differ in climatic niche more than expected by chance, with the exception of root morphology, where modified roots are associated with lower temperature seasonality. These findings suggest that root tubers may reflect adaptations to different climatic conditions than those represented by other types of USOs. Thus, the tissue type and developmental origin of the USO structure may influence the way it mediates ecological relationships, which draws into question the appropriateness of ascribing broad ecological patterns uniformly across geophytic taxa. This work provides a new framework for testing adaptive hypotheses and for linking ecological patterns across morphologically varying taxa while accounting for developmental (non-independent) relationships in morphological data. [Macroevolution, geophytes, climatic niche evolution, imperfect correspondence]

evolutionary biology↗

bioRxiv2021

Mistreating birth-death models as priors in phylogenetic analysis compromises our ability to compare models

Time-calibrated phylogenetic trees are a tremendously powerful tool for studying evolutionary, ecological, and epidemiological phenomena. Such trees are predominantly inferred in a Bayesian framework, with the phylogeny itself treated as a parameter with a prior distribution (a "tree prior"). However, we show that the tree "parameter" consists, in part, of data, in the form of taxon samples. Treating the tree as a parameter fails to account for these data and compromises our ability to compare among models. Since accuracy of the inferred phylogeny strongly depends on how well the tree prior approximates the true diversification process that gave rise to the tree, the inability to accurately compare competing tree priors has broad implications for applications based on time-calibrated trees. We outline potential remedies to this problem, and provide guidance for researchers interested in assessing the fit of tree models.

evolutionary biology↗

bioRxiv2021

RevGadgets: an R Package for visualizing Bayesian phylogenetic analyses from RevBayes

O_LIStatistical phylogenetic methods are the foundation for a wide range of evolutionary and epidemiological studies. However, as these methods grow increasingly complex, users often encounter significant challenges with summarizing, visualizing, and communicating their key results. C_LIO_LIWe present RevGadgets, an R package for creating publication-quality figures from the results of a large variety of phylogenetic analyses performed in RevBayes (and other phylogenetic software packages). C_LIO_LIWe demonstrate how to use RevGadgets through a set of vignettes that cover the most common use cases that researchers will encounter. C_LIO_LIRevGadgets is an open-source, extensible package that will continue to evolve in parallel with RevBayes, helping researchers to make sense of and communicate the results of a diverse array of analyses. C_LI [Bayesian phylogenetics, data visualization, R, RevBayes]

evolutionary biology↗

bioRxiv2021

Phylodynamic insights on the early spread of the COVID-19 pandemic and the efficacy of intervention measures

We performed phylodynamic analyses of all available SARS-CoV-2 genomes from the early phase of the COVID-19 pandemic--combined with a novel dataset on contemporary global air-travel volume--to assess the efficacy of public-health measures on viral geographic spread. Globally, viral dispersal rates are significantly correlated with air-travel volume, and widespread international air-travel bans imposed against China by early February coincide with a significant reduction in geographic viral spread. In North America, the efficacy of this travel ban was temporary, possibly due to the lack of both containment measures against other infected regions and domestic mitigation measures. By contrast, in China, domestic mitigation measures were correlated with a long-term reduction in viral spread, despite repeated international introductions. Our study supports a role for both targeted international containment and domestic mitigation measures as critical components of a more comprehensive public-health strategy to mitigate future outbreaks caused by the emergence of novel SARS-CoV-2 variants. One sentence summaryPhylodynamic analyses reveal that variation in rates of early geographic spread of COVID-19 are correlated with intervention measures.

evolutionary biology↗

bioRxiv2020

Inferring the Total-Evidence Timescale of Marattialean Fern Evolution in the Face of Model Sensitivity

Phylogenetic divergence-time estimation has been revolutionized by two recent developments: 1) total-evidence dating (or "tip-dating") approaches that allow for the incorporation of fossils as tips in the analysis, with their phylogenetic and temporal relationships to the extant taxa inferred from the data, and 2) the fossilized birth-death (FBD) class of tree models that capture the processes that produce the tree (speciation, extinction, and fossilization), and thus provide a coherent and biologically interpretable tree prior. To explore the behaviour of these methods, we apply them to marattialean ferns, a group that was dominant in Carboniferous landscapes prior to declining to its modest extant diversity of slightly over 100 species. We show that tree models have a dramatic influence on estimates of both divergence times and topological relationships. This influence is driven by the strong, counter-intuitive informativeness of the uniform tree prior and the inherent nonidentifiability of divergence-time models. In contrast to the strong influence of the tree models, we find minor effects of differing the morphological transition model or the morphological clock model. We compare the performance of a large pool of candidate models using a combination of posterior-predictive simulation and Bayes factors. Notably, an FBD model with epoch-specific speciation and extinction rates was strongly favored by Bayes factors. Our best-fitting model infers stem and crown divergences for the Marattiales in the mid-Devonian and Late Cretaceous, respectively, with elevated speciation rates in the Mississippian and elevated extinction rates in the Cisuralian leading to a peak diversity of [~]2800 species at the end of the Carboniferous, representing the heyday of the Psaroniaceae. This peak is followed by the rapid decline and ultimate extinction of the Psaroniaceae, with their descendants, the Marattiaceae, persisting at approximately stable levels of diversity until the present. This general diversification pattern appears to be insensitive to potential biases in the fossil record; despite the preponderance of available fossils being from Pennsylvanian coal balls, incorporating fossilization-rate variation does not improve model fit. In addition, by incorporating temporal data directly within the model and allowing for the inference of the phylogenetic position of the fossils, our study makes the surprising inference that the clade of extant Marattiales is relatively young, younger than any of the fossils historically thought to be congeneric with extant species. This result is a dramatic demonstration of the dangers of node-based approaches to divergence-time estimation, where the assignment of fossils to particular clades are made a priori (earlier node-based studies that constrained the minimum ages of extant genera based on these fossils resulted in much older age estimates than in our study) and of the utility of explicit models of morphological evolution and lineage diversification.

evolutionary biology↗

bioRxiv2019

A hierarchical Bayesian mixture model for distinguishing active gene expression from transcriptional noise

Transcriptomes are key to understanding the relationship between genotype and phenotype. The ability to infer the expression state (active or inactive) of genes in the transcriptome offers unique benefits for addressing this issue. For example, qualitative changes in gene expression may underly the origin of novel phenotypes, and expression states are readily comparable between tissues and species. However, inferring the expression state of genes is a surprisingly difficult problem, owing to the complex biological and technical processes that give rise to observed transcriptomic datasets. Here, we develop a hierarchical Bayesian mixture model that describes this complex process, and allows us to infer expression state of genes from replicate transcriptomic libraries. We explore the statistical behavior of this method with analyses of simulated datasets--where we demonstrate its ability to correctly infer true (known) expression states--and empirical-benchmark datasets, where we demonstrate that the expression states inferred from RNA-seq datasets using our method are consistent with those based on independent evidence. The power of our method to correctly infer expression states is generally high and, remarkably, approaches the maximum possible power for this inference problem. We present an empirical analysis of primate-brain transcriptomes, which identifies genes that have a unique expression state in humans. Our method is implemented in the freely-available R package zigzag.\n\nSignificance StatementHow do the cells of an organism--each with an identical genome--give rise to tissues of incredible phenotypic diversity? Key to answering this question is the transcriptome: the set of genes expressed in a given tissue. We would clearly benefit from the ability to identify qualitative differences in expression (whether a gene is active or inactive in a given tissue/species). Inferring the expression state of genes is surprisingly difficult, owing to the complex biological processes that give rise to transcriptomes, and to the vagaries of techniques used to generate transcriptomic datasets. We develop a hierarchical Bayesian mixture model that--by describing those biological and technical processes--allows us to infer the expression state of genes from replicate transcriptomic datasets.

genomics↗

bioRxiv2019

A Bayesian Approach for Inferring the Impact of a Discrete Character on Rates of Continuous-Character Evolution in the Presence of Background Rate Variation

Understanding how and why rates of character evolution vary across the Tree of Life is central to many evolutionary questions; e.g., does the trophic apparatus (a set of continuous characters) evolve at a higher rate in fish lineages that dwell in reef versus non-reef habitats (a discrete character)? Existing approaches for inferring the relationship between a discrete character and rates of continuous-character evolution rely on comparing a null model (in which rates of continuous-character evolution are constant across lineages) to an alternative model (in which rates of continuous-character evolution depend on the state of the discrete character under consideration). However, these approaches are susceptible to a \"straw-man\" effect: the influence of the discrete character is inflated because the null model is extremely unrealistic. Here, we describe MuSSCRat, a Bayesian approach for inferring the impact of a discrete trait on rates of continuous-character evolution in the presence of alternative sources of rate variation (\"background-rate variation\"). We demonstrate by simulation that our method is able to reliably infer the degree of state-dependent rate variation, and show that ignoring background-rate variation leads to biased inferences regarding the degree of state-dependent rate variation in grunts (the fish group Haemulidae). [continuous-character evolution; discrete-character evolution; Bayesian phylogenetic comparative methods; data augmentation]

evolutionary biology↗

bioRxiv2019

A Bayesian Approach for Estimating Branch-Specific Speciation and Extinction Rates

Species richness varies considerably among the tree of life which can only be explained by heterogeneous rates of diversification (speciation and extinction). Previous approaches use phylogenetic trees to estimate branch-specific diversification rates. However, all previous approaches disregard diversification-rate shifts on extinct lineages although 99% of species that ever existed are now extinct. Here we describe a lineage-specific birth-death-shift process where lineages, both extant and extinct, may have heterogeneous rates of diversification. To facilitate probability computation we discretize the base distribution on speciation and extinction rates into k rate categories. The fixed number of rate categories allows us to extend the theory of state-dependent speciation and extinction models (e.g., BiSSE and MuSSE) to compute the probability of an observed phylogeny given the set of speciation and extinction rates. To estimate branch-specific diversification rates, we develop two independent and theoretically equivalent approaches: numerical integration with stochastic character mapping and data-augmentation with reversible-jump Markov chain Monte Carlo sampling. We validate the implementation of the two approaches in RevBayes using simulated data and an empirical example study of primates. In the empirical example, we show that estimates of the number of diversification-rate shifts are, unsurprisingly, very sensitive to the choice of prior distribution. Instead, branch-specific diversification rate estimates are less sensitive to the assumed prior distribution on the number of diversification-rate shifts and consistently infer an increased rate of diversification for Old World Monkeys. Additionally, we observe that as few as 10 diversification-rate categories are sufficient to approximate a continuous base distribution on diversification rates. In conclusion, our implementation of the lineage-specific birth-death-shift model in RevBayes provides biologists with a method to estimate branch-specific diversification rates under a mathematically consistent model.

evolutionary biology↗