Biology subjects

Höhna, S.

Publications and source records attributed to Höhna, S..

8 recordsLinked to original sources

bioRxiv2025

Phylogenetic Estimation of branch-specific Shifts in the Tempo of Origination

AO_SCPLOWBSTRACTC_SCPLOWStudying rates of species diversification is one of the key themes in macroevolution. In particular, we are interested in if some clades in a phylogeny diversify more rapidly/slowly than others due to branch-specific diversification rates. A common approach in neontological studies is to use a phylogenetic birth-death process to model species diversification. Specifically, the birth-death-shift process is used to model branch-specific shifts in the tempo of diversification. Here, we present Pesto, a new method and software for estimating branch-specific diversification rates that does not rely on Markov chain Monte Carlo simulations for fitting the model and instead deterministically computes the posterior mean branch-specific diversification rates using only two traversals of the tree. This method is blazingly fast: the birth-death-shift model can be fitted to large phylogenies (> 20k taxa) in minutes on a personal computer while also providing branch-specific inference of diversification rate shift events. Thus, we can robustly infer branch-specific diversification rates and the number of diversification rate shift events for large-scale phylogenies as well as exploring the characteristic of the birth-death-shift model through complex and large-scale simulations. Here, we first describe the method and the software implementation Pesto and explore its behavior using trees simulated under the birth-death-shift model. Then, we explore the behavior of inferring significant branch-specific diversification rate shifts using both Bayes factors and effect sizes. We find few to none false positive inferences of diversification rate shift events but many false negatives (reduced power). The most difficult parameter to estimate is the rate at which diversification rate shifts occur (shift rate). Despite this, branch-specific diversification rate estimates are precise and nearly unbiased.

evolutionary biology↗

bioRxiv2023

Commonly used Bayesian diversification-rate models produce biologically meaningful differences on empirical phylogenies

Identifying along which lineages shifts in diversification rates occur is a central goal of comparative phylogenetics; these shifts may coincide with key evolutionary events such as the development of novel morphological characters, the acquisition of adaptive traits, polyploidization or other structural genomic changes, or dispersal to a new habitat and subsequent increase in environmental niche space. However, while multiple methods now exist to estimate diversification rates and identify shifts using phylogenetic topologies, the appropriate use and accuracy of these methods is hotly debated. Here we test whether five Bayesian methods--Bayesian Analysis of Macroevolutionary Mixtures (BAMM), two implementations of the Lineage-Specific Birth-Death-Shift model (LSBDS and PESTO), the approximate Multi-Type Birth-Death model (MTBD; implemented in BEAST2), and the cladogenetic diversification rate shift model (CLaDS2)--produce comparable results. We apply each of these methods to a set of 65 empirical time-calibrated phylogenies and compare inferences of speciation rate, extinction rate, and net diversification rate. We find that the five methods often infer different speciation, extinction, and net-diversification rates. Consequently, these different estimates may lead to different interpretations of the macroevolutionary dynamics. The different estimates can be attributed to fundamental differences among the compared models. Therefore, the inference of shifts in diver-sification rates is strongly method-dependent. We advise biologists to apply multiple methods to test the robustness of the conclusions or to carefully select the method based on the validity of the underlying model assumptions to their particular empirical system. Lay SummaryUnderstanding why some groups of organisms have more species than others is key to understanding the origin of biodiversity. Theory and empirical evidence suggest that multiple distinct historical events--such as the evolution of particular morphological features (e.g., the flower, the tetrapod limb) and competition amongst species--can produce this pattern of divergent species richness. Identifying when and where on the tree of life shifts in diversification rates occur is important for explaining the origin of modern-day biodiversity and understanding how disparity among species evolves. Several statistical methods have been developed to infer diversification rates and identify these shifts. While these methods each attempt to make inferences about changes in the tempo of diversification, they differ in their underlying statistical models and assumptions. Here we test if these methods draw similar conclusions using a dataset of 65 time-calibrated phylogenies from across multicellular life. We find that inferences of where rate shifts occur strongly depends on the chosen method. Therefore, biologists should choose the model whose assumptions they believe to be the most valid and justify their model choice a priori, or consider using several independent methods to test an evolutionary hypothesis.

evolutionary biology↗

bioRxiv2022

Rapidly changing speciation and extinction rates can be inferred in spite of non-identifiability

The birth-death model is commonly used to infer speciation and extinction rates by fitting the model to extant phylogenetic trees. Recently, it was demonstrated that speciation and extinction rates are not identifiable if the rates are allowed to vary freely over time. The group of birth-death models that are not identifiable from each other is called a congruence class. Every model in a congruence class is equally likely, and there is no statistical evidence that can be used to favor one over the other. This issue has led researchers to question if and what patterns can reliably be inferred, and whether time-variable birth-death models should be fitted at all. We explore the congruence class in the context of several empirical phylogenies as well as hypothetical scenarios and summarize shared patterns in the congruence class. We show that strong directional trends in speciation and extinction rates are ubiquitous among most models within the congruence class, and conclude that inference of strong directional trends is therefore robust. Conversely, estimates of constant rates or gentle slopes are not robust and must be treated with caution. Additionally, most conflict in trends within the congruence class is observed near the present, implying that very recent rate changes should be treated carefully. Interestingly, the space of valid speciation rates is limited in contrast to extinction rates, which are less constrained. These results provide further evidence and insights that speciation rates can be estimated more reliably than extinction rates.

evolutionary biology↗

bioRxiv2022

Bayesian inference of phylogeny is robust to substitution model over-parameterization

Model selection aims to choose the most adequate model for the statistical analysis at hand. The model must be complex enough to capture the complexity of the data but should be simple enough to not overfit. In phylogenetics, the most common model selection scenario concerns selecting an appropriate substitution and partition model for sequence evolution to infer a phylogenetic tree. Here we explored the impact of substitution model over-parameterization in a Bayesian statistical framework. We performed simulations under the simplest substitution model, the Jukes-Cantor model, and compare posterior estimates of phylogenetic tree topologies and tree length under the true model to the most complex model, the GTR+{Gamma}+I substitution model, including over-splitting the data into additional subsets (i.e., applying partitioned models). We explored four choices of prior distributions: the default substitution model priors of MrBayes, BEAST2 and RevBayes and a newly devised prior choice (Tame). Our results show that Bayesian inference of phylogeny is robust to substitution model over-parameterization but only under our new prior settings. All three default priors introduced biases for the estimated tree length. We conclude that substitution and partition model selection are superfluous steps in Bayesian phylogenetic inference pipelines if well behaved prior distributions are applied.

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

Impact of K-Pg Mass Extinction Event on Crocodylomorpha Inferred from Phylogeny of Extinct and Extant Taxa

Crocodilians and their allies have survived several mass extinction events. However, the impact of the K-Pg mass extinction event on crocodylomorphs is considered as minor or non-existent although other clades of archosaurs, e.g., non-avian dinosaurs and pterosaurs, went extinct completely. Previous approaches using fossil occurrence data alone have proven inconclusive. In this paper, we take a phylogenetic approach using extant and extinct species. The time-calibrated phylogeny of extant crocodilians provides insights into the pattern of recent biodiversity changes whereas fossil occurrence data provide insights about the more ancient past. The two data sources combined into a single phylogeny with extinct and extant taxa provide a holistic view of the historical biodiversity. To utilize this combined data and to infer the impact of the K-Pg mass extinction event, we derive the likelihood function for a time-varying (episodic) serially sampled birth-death model that additionally incorporates mass extinctions and bursts of births. We implemented the likelihood function in a Bayesian framework with recently developed smoothing priors to accommodate for both abrupt and gradual changes in speciation, extinction and fossilization rates. Contrary to previous research, we find strong evidence for the K-Pg extinction event in crocodiles and their allies. This signal is robust to uncertainty in the phylogeny and the prior on the mass extinctions. Through simulated data analyses, we show that there is high power to detect this mass extinction and little risk of false positives.

evolutionary biology↗

bioRxiv2019

Locally adaptive Bayesian birth-death model successfully detects slow and rapid rate shifts

AO_SCPLOWBSTRACTC_SCPLOWBirth-death processes have given biologists a model-based framework to answer questions about changes in the birth and death rates of lineages in a phylogenetic tree. Therefore birth-death models are central to macroevolutionary as well as phylodynamic analyses. Early approaches to studying temporal variation in birth and death rates using birth-death models faced difficulties due to the restrictive choices of birth and death rate curves through time. Sufficiently flexible time-varying birth-death models are still lacking. We use a piecewise-constant birth-death model, combined with both Gaussian Markov random field (GMRF) and horseshoe Markov random field (HSMRF) prior distributions, to approximate arbitrary changes in birth rate through time. We implement these models in the widely used statistical phylogenetic software platform RevBayes, allowing us to jointly estimate birth-death process parameters, phylogeny, and nuisance parameters in a Bayesian framework. We test both GMRF-based and HSMRF-based models on a variety of simulated diversification scenarios, and then apply them to both a macroevolutionary and an epidemiological dataset. We find that both models are capable of inferring variable birth rates and correctly rejecting variable models in favor of effectively constant models. In general the HSMRF-based model has higher precision than its GMRF counterpart, with little to no loss of accuracy. Applied to a macroevolutionary dataset of the Australian gecko family Pygopodidae (where birth rates are interpretable as speciation rates), the GMRF-based model detects a slow decrease whereas the HSMRF-based model detects a rapid speciation-rate decrease in the last 12 million years. Applied to an infectious disease phylodynamic dataset of sequences from HIV subtype A in Russia and Ukraine (where birth rates are interpretable as the rate of accumulation of new infections), our models detect a strongly elevated rate of infection in the 1990s. AO_SCPLOWUTHORC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWSUMMARYC_SCPLOWBoth the growth of groups of species and the spread of infectious diseases through populations can be modeled as birth-death processes. Birth events correspond either to speciation or infection, and death events to extinction or becoming noninfectious. The rates of birth and death may vary over time, and by examining this variation researchers can pinpoint important events in the history of life on Earth or in the course of an outbreak. Time-calibrated phylogenies track the relationships between a set of species (or infections) and the times of all speciation (or infection) events, and can thus be used to infer birth and death rates. We develop two phylogenetic birth-death models with the goal of discerning signal of rate variation from noise due to the stochastic nature of birth-death models. Using a variety of simulated datasets, we show that one of these models can accurately infer slow and rapid rate shifts without sacrificing precision. Using real data, we demonstrate that our new methodology can be used for simultaneous inference of phylogeny and rates through time.

evolutionary biology↗

bioRxiv2018

Drift and directional selection are the evolutionary forces driving gene expression divergence in eye and brain tissue of Heliconius butterflies

Investigating gene expression evolution over micro- and macroevolutionary timescales will expand our understanding of the role of gene expression in adaptation and speciation. In this study, we characterized which evolutionary forces are acting on gene expression levels in eye and brain tissue of five Heliconius butterflies with divergence times of ~5-12 MYA. We developed and applied Brownian motion and Ornstein-Uhlenbeck models to identify genes whose expression levels are evolving through drift, stabilizing selection, or a lineage-specific shift. We find that 81% of the genes evolve under genetic drift. When testing for branch-specific shifts in gene expression, we detected 368 (16%) shift events. Genes showing a shift towards up-regulation have significantly lower gene expression variance than those genes showing a shift leading towards down-regulation. We hypothesize that directional selection is acting in shifts causing up-regulation, since transcription is costly. We further uncover through simulations that parameter estimation of Ornstein-Uhlenbeck models is biased when using small phylogenies and only becomes reliable with phylogenies having at least 50 taxa. Therefore, we developed a new statistical test based on Brownian motion to identify highly conserved genes (i.e., evolving under strong stabilizing selection), which comprised 3% of the orthoclusters. In conclusion, we found that drift is the dominant evolutionary force driving gene expression evolution in eye and brain tissue in Heliconius. Nevertheless, the higher proportion of genes evolving under directional than under stabilizing selection might reflect species-specific selective pressures on vision and brain necessary to fulfill species-specific requirements.

evolutionary biology↗