Biology subjects

O'Meara, B. C.

Publications and source records attributed to O'Meara, B. C..

13 recordsLinked to original sources

bioRxiv2025

Statistical and structural bias in birth-death models

Accurate estimation of speciation ({lambda}) and extinction ({micro}) rates from phylogenetic trees is central to studies of diversification, yet it remains unclear whether commonly used estimators are unbiased. Here we examine two sources of error: (1) statistical bias in the estimators themselves, and the (2) structural bias introduced by how small trees are handled in likelihood calculations. For the Yule process, we re-derive the expected bias of the standard estimator, showing that [Formula] underestimates{lambda} by a factor of (n - 2)/(n - 1). Extending to the general birth-death model, we use symbolic regression to find functional forms that minimize the bias in both{lambda} and {micro}. The best-performing correction for{lambda} is identical to the Yule result, while the bias in {micro} depends on both sample size and the estimated extinction fraction ({micro}/{lambda}). Applying these corrections substantially improves the fit between the estimated and generating values. When these corrected estimators are used to derive other diversification-related parameters, turnover is nearly unbiased, but net diversification ({lambda} - {micro}) remains systematically underestimated due to the slight overestimation of {micro}. On the whole, these results clarify the statistical and structural sources of bias in diversification rate estimation and provide a general framework for improving inference under birth-death models.

evolutionary biology↗

bioRxiv2024

Navigating "tip fog": Embracing uncertainty in tip measurements

Nature is full of messy variation, which serves as the raw material for evolution. However, in comparative biology this variation is smoothed into averages. Overlooking this variation not only weakens our analyses but also risks selecting inaccurate models, generating false precision in parameter estimates, and creating artificial patterns. Furthermore, the complexity of uncertainty extends beyond traditional "measurement error," encompassing various sources of intraspecific variance. To address this, we propose the term "tip fog" to describe the variance between the true species mean and what is recorded, without implying a specific mechanism. We show why accounting for tip fog remains critical by showing its impact on continuous comparative models and discrete comparative and diversification models. We rederive methods to estimate this variance and use simulations to assess its feasibility and importance in a comparative context. Our findings reveal that ignoring tip fog substantially affects the accuracy of rate estimates, with higher tip fog levels showing greater biases from the true rates, as well as affecting which models are chosen. The findings underscore the importance of model selection and the potential consequences of neglecting tip fog, providing insights for improving the accuracy of comparative methods in evolutionary biology.

evolutionary biology↗

bioRxiv2024

Error causes a perceived pull to the present in evolutionary rates

Across a variety of biological datasets, from genomes to conservation to the fossil record, evolutionary rates appear to increase toward the present or over short time scales. This has long been seen as an indication of processes operating differently at different time scales, even potentially as an indicator of a need for new theory connecting macroevolution and microevolution. Here we introduce a set of models that assess the relationship between rate and time and demonstrate that these patterns are statistical artifacts of time-independent errors present across ecological and evolutionary datasets, which produce hyperbolic patterns of rates through time. We show that plotting a noisy numerator divided by time versus time leads to the observed hyperbolic pattern; in fact, randomizing the amount of change over time generates patterns functionally identical to observed patterns. Ignoring errors can not only obscure true patterns but create novel patterns that have long misled scientists.

evolutionary biology↗

bioRxiv2022

Identifying climatic drivers of hybridization in Heuchereae (Saxifragaceae)

Applications of molecular phylogenetic approaches have uncovered evidence of hybridization across numerous clades of life, yet the environmental factors responsible for driving opportunities for hybridization remain obscure. Verbal models implicating geographic range shifts that brought species together during the Pleistocene have often been invoked, but quantitative tests using paleoclimatic data are needed to validate these models. Here, we produce a phylogeny for Heuchereae, a clade of 15 genera and 83 species in Saxifragaceae, with complete sampling of recognized species, using 277 nuclear loci and nearly complete chloroplast genomes. We then employ an improved framework with a coalescent simulation approach to test and ultimately confirm previous hybridization hypotheses and identify one new intergeneric hybridization event. Focusing on the North American distribution of Heuchereae, we introduce and implement a newly developed approach to reconstruct potential past distributions for ancestral lineages across all species in the clade and across a paleoclimatic record extending from the late Pliocene. Time calibration based on both nuclear and chloroplast trees recovers a mid- to late-Pleistocene date for most inferred hybridization events, a timeframe concomitant with repeated geographic range restriction into overlapping refugia. Our results indicate an important role for past episodes of climate change, and the contrasting responses of species with differing ecological strategies, in generating novel patterns of range contact among plant communities and therefore new opportunities for hybridization.

evolutionary biology↗

bioRxiv2022

Two shifts in evolutionary lability underlie independent gains and losses of root-nodule symbiosis in a single clade of plants

Root nodule symbiosis (RNS) allows plants to access atmospheric nitrogen converted into usable forms through a mutualistic relationship with soil bacteria. RNS is a complex trait requiring coordination from both the plant host and the bacterial symbiont, and pinpointing the evolutionary origins of root nodules is critical for understanding the genetic basis of RNS. This endeavor is complicated by data limitations and the intermittent presence of RNS in a single clade of ca. 30,000 species of flowering plants, i.e., the nitrogen-fixing clade (NFC). We developed the most extensive de novo phylogeny for all major lineages of the NFC and an enhanced root nodule trait database to reconstruct the evolution of RNS. Through identification of the evolutionary pathway to RNS gain, we show that shifts among heterogeneous evolutionary rates can explain how a complex trait such as RNS can arise many times across a large phylogeny. Our analysis identifies a two-step process in which an ancestral precursor state gave rise to a more labile state from which RNS was quickly gained at specific points in the NFC. Our rigorous reconstruction of ancestral states illustrates how a two-step pathway could have led to multiple independent gains and losses of RNS, contrary to recent hypotheses invoking just a single gain and numerous losses. RNS may be an example of multi-level convergent evolution, thus requiring a broader phylogenetic and genetic scope for genome-phenome mapping to elucidate mechanisms enabling fully functional RNS.

evolutionary biology↗

bioRxiv2021

Fossils Do Not Substantially Improve, and May Even Harm, Estimates of Diversification Rate Heterogeneity

The fossilized birth-death (FBD) model is a naturally appealing way of directly incorporating fossil information when estimating diversification rates. However, an important yet often overlooked property of the original FBD derivation is that it distinguishes between two types of sampled lineages. Here we first discuss and demonstrate the impact of severely undersampling, and even not including fossils that represent samples of lineages that also had sampled descendants. We then explore the benefits of including fossils, generally, by implementing and then testing two-types of FBD models, including one that converts a fossil set into stratigraphic ranges, in more complex likelihood-based models that assume multiple rate classes across the tree. Under various simulation scenarios, including a scenario that exists far outside the set of models we evaluated, including fossils rarely outperforms analyses that exclude them altogether. At best, the inclusion of fossils improves precision but does not influence bias. Similarly, we found that converting the fossil set to stratigraphic ranges, which is one way to remedy the effects of undercounting the number of k-type fossils, results in turnover rates and extinction fraction estimates that are generally underestimated. While fossils remain essential for understanding diversification through time, in the specific case of understanding diversification given an existing, largely modern tree, they are not especially beneficial.

evolutionary biology↗

bioRxiv2021

Hidden-state-only speciation and extinction models provide accurate tip estimates of diversification rates

Estimates of diversification rates at the tips of a phylogeny provide a flexible approach for correlation analyses with multiple traits and to map diversification rates in space, while also avoiding the uncertainty of deep time rate reconstructions. Available methods for tip rate estimation make different assumptions, and thus their accuracy usually depends on characteristics of the underlying model generating the tree. Here we introduce MiSSE, a trait-free, state-dependent speciation and extinction approach that can be used to estimate varying speciation, extinction, net-diversification, turnover rates, and extinction fraction at the tips of the tree. We compare the accuracy of tip rates inferred by MiSSE against similar methods and demonstrate that, due to certain characteristics of the model, the error is generally low across a broad range of speciation and extinction scenarios. MiSSE can be used alongside regular phylogenetic comparative methods in trait related diversification hypotheses, and we also describe a simple correction to avoid pseudoreplication from sister tips in analyses of independent contrasts. Finally, we demonstrate the capabilities of MiSSE, with a renewed focus on classic comparative methods, to examine correlation between plant height and turnover rates in eucalypts, a species-rich lineage of flowering plants.

evolutionary biology↗

bioRxiv2021

The Shape of Trees - Limits of Current Diversification Models

To investigate how biodiversity arose, the field of macroevolution largely relies on model-based approaches to estimate rates of diversification and what factors influence them. The number of available models is rising steadily, facilitating the modeling of an increasing number of possible diversification dynamics, and multiple hypotheses relating to what fueled or stifled lineage accumulation within groups of organisms. However, growing concerns about unchecked biases and limitations in the employed models suggest the need for rigorous validation of methods used to infer. Here, we address two points: the practical use of model adequacy testing, and what model adequacy can tell us about the overall state of diversification models. Using a large set of empirical phylogenies, and a new approach to test models using aspects of tree shape, we test how a set of staple models performs with regards to adequacy. Patterns of adequacy are described across trees and models and causes for inadequacy - particularly if all models are inadequate - are explored. The findings make clear that overall, only few empirical phylogenies cannot be described by at least one model. However, finding that the best fitting of a set of models might not necessarily be adequate makes clear that adequacy testing should become a step in the standard procedures for diversification studies.

evolutionary biology↗

bioRxiv2021

Age, Origin, and Biogeography: Unveiling the Factors Behind the Diversification of Dung Beetles

The remarkable diversity and global distribution of dung beetles has long attracted the interest of researchers. However, there is still an ongoing debate on their origin, the reasons behind their diversity, and their path to global distribution. The two most prominent hypotheses regarding their origin and biogeographic history involve either vicariance events after the breakup of Gondwana, or an African origin and subsequent dispersal. One of the key reasons why the question is still disputed is a dependence on knowing the age of the dung beetles - a Mesozoic origin would favor the scenario of Gondwanan vicariance, a Cenozoic origin would suggest the out-of-Africa scenario. To help settle this longstanding question, we provide a taxonomically expanded phylogeny, with divergence times estimated under two calibration schemes suggesting an older or younger origin respectively. Using model-based inference, we estimate the ancestral area of the group and test for the influence of ranges on diversification rates. Our results support the hypothesis of an old age for Scarabaeinae and Gondwanan origin but remain ambiguous about the exact relation of range on lineage diversification.

evolutionary biology↗

bioRxiv2020

BoskR - Testing Adequacy of Diversification Models Using Tree Shape

The study of diversification largely relies on model-based approaches, estimating rates of speciation and extinction from phylogenetic trees. While a plethora of different models exist - all with different features, strengths and weaknesses - there is increasing concern about the reliability of the inference we gain from them. Apart from simply finding the model with the best fit for the data, we should find ways to assess a models suitability to describe the data in an absolute sense. The R package BoskR implements a simple way of judging a models adequacy for a given phylogeny using metrics for tree shape, assuming that a model is inadequate for a phylogeny if it produces trees that are consistently dissimilar in shape from the tree that should be analyzed. Tree shape is assessed via metrics derived from the trees modified graph Laplacian spectrum, as provided by RPANDA. We exemplify the use of the method using simulated and empirical example phylogenies. BoskR was mostly able to correctly distinguish trees simulated under clearly different models and revealed that not all models are adequate for the empirical example trees. We believe the metrics of tree shape to be an intuitive and relevant means of assessing diversification model adequacy. Furthermore, by implementing the approach in an openly available R package, we enable and encourage researchers to adopt adequacy testing into their workflow.

evolutionary biology↗

bioRxiv2019

Gene Expression of Functionally-Related Genes Coevolves Across Fungal Species: Detecting Coevolution of Gene Expression Using Phylogenetic Comparative Methods

BackgroundResearchers often measure changes in gene expression across conditions to better understand the shared functional roles and regulatory mechanisms of different genes. Analogous to this is comparing gene expression across species, which can improve our understanding of the evolutionary processes shaping the evolution of both individual genes and functional pathways. One area of interest is determining genes showing signals of coevolution, which can also indicate potential functional similarity, analogous to co-expression analysis often performed across conditions for a single species. However, as with any trait, comparing gene expression across species can be confounded by the non-independence of species due to shared ancestry, making standard hypothesis testing inappropriate. ResultsWe compared RNA-Seq data across 18 fungal species using a multivariate Brownian Motion phylogenetic comparative method (PCM), which allowed us to quantify coevolution between protein pairs while directly accounting for the shared ancestry of the species. Our work indicates proteins which physically-interact show stronger signals of coevolution than randomly-generated pairs. Interactions with stronger empirical and computational evidence also showing stronger signals of coevolution. We examined the effects of number of protein interactions and gene expression levels on coevolution, finding both factors are overall poor predictors of the strength of coevolution between a protein pair. Simulations further demonstrate the potential issues of analyzing gene expression coevolution without accounting for shared ancestry in a standard hypothesis testing framework. Furthermore, our simulations indicate the use of a randomly-generated null distribution as a means of determining statistical significance for detecting coevolving genes with phylogenetically-uncorrected correlations, as has previously been done, is less accurate than PCMs, although is a significant improvement over standard hypothesis testing. These methods are further improved by using a phylogenetically-corrected correlation metric. ConclusionsOur work highlights potential benefits of using PCMs to detect gene expression coevolution from high-throughput omics scale data. This framework can be built upon to investigate other evolutionary hypotheses, such as changes in transcription regulatory mechanisms across species.

evolutionary biology↗

bioRxiv2019

Datelife: leveraging databases and analytical tools to reveal the dated Tree of Life.

Achieving a high-quality reconstruction of a phylogenetic tree with branch lengths proportional to absolute time (chronogram) is a difficult and time-consuming task. But the increased availability of fossil and molecular data, and time-efficient analytical techniques has resulted in many recent publications of large chronograms for a large number and wide diversity of organisms. Knowledge of the evolutionary time frame of organisms is key for research in the natural sciences. It also represent valuable information for education, science communication, and policy decisions. When chronograms are shared in public and open databases, this wealth of expertly-curated and peer-reviewed data on evolutionary timeframe is exposed in a programatic and reusable way, as intensive and localized efforts have improved data sharing practices, as well as incentivizited open science in biology. Here we present DateLife, a service implemented as an R package and an R Shiny website application available at www.datelife.org, that provides functionalities for efficient and easy finding, summary, reuse, and reanalysis of expert, peer-reviewed, public data on time frame of evolution. The main DateLife workflow constructs a chronogram for any given combination of taxon names by searching a local chronogram database constructed and curated from the Open Tree of Life Phylesystem phylogenetic database, which incorporates phylogenetic data from the TreeBASE database as well. We implement and test methods for summarizing time data from multiple source chronograms using supertree and congruification algorithms, and using age data extracted from source chronograms as secondary calibration points to add branch lengths proportional to absolute time to a tree topology. DateLife will be useful to increase awareness of the existing variation in alternative hypothesis of evolutionary time for the same organisms, and can foster exploration of the effect of alternative evolutionary timing hypotheses on the results of downstream analyses, providing a framework for a more informed interpretation of evolutionary results.

scientific communication and education↗

bioRxiv2019

Decomposing Mutation and Selection to Identify Mismatched Codon Usage

For decades, codon usage has been used as a measure of adaptation for translational efficiency and translation accuracy of a genes coding sequence. These patterns of codon usage reflect both the selective and mutational environment in which the coding sequences evolved. Over this same period, gene transfer between lineages has become widely recognized as an important biological phenomenon. Nevertheless, most studies of codon usage implicitly assume that all genes within a genome evolved under the same selective and mutational environment, an assumption violated when introgression occurs. In order to better understand the effects of introgression on codon usage patterns and vice versa, we examine the patterns of codon usage in Lachancea kluyveri, a yeast which has experienced a large introgression. We quantify the effects of mutation bias and selection for translation efficiency on the codon usage pattern of the endogenous and introgressed exogenous genes using a Bayesian mixture model, ROC SEMPPR, which is built on mechanistic assumptions about protein synthesis and grounded in population genetics. We find substantial differences in codon usage between the endogenous and exogenous genes, and show that these differences can be largely attributed to differences in mutation bias favoring A/T ending codons in the endogenous genes while favoring C/G ending codons in the exogenous genes. Recognizing the two different signatures of mutation bias and selection improves our ability to predict protein synthesis rate by 42% and allowed us to accurately assess the decaying signal of endogenous codon mutation and preferences. In addition, using our estimates of mutation bias and selection, we identify Eremothecium gossypii as the closest relative to the exogenous genes, providing an alternative hypothesis about the origin of the exogenous genes, estimate that the introgression occurred [~] 6 x 108 generation ago, and estimate its historic and current selection against mismatched codon usage. Our work illustrates how mechanistic, population genetic models like ROC SEMPPR can separate the effects of mutation and selection on codon usage and provide quantitative estimates from sequence data.

evolutionary biology↗