A Systematist's Guide to Estimating Bayesian Phylogenies From Morphological Data

Practical guidelines for Bayesian phylogenetic inference using Markov Chain Monte Carlo (MCMC)

Phylogenetic estimation is, and has always been, a complex endeavor. Estimating a phylogenetic tree involves evaluating many possible solutions and possible evolutionary histories that could explain a set of observed data, typically by using a model of evolution. Modern statistical methods involve not just the estimation of a tree, but also solutions to more complex models involving fossil record information and other data sources. Markov Chain Monte Carlo (MCMC) is a leading method for approximating the posterior distribution of parameters in a mathematical model. It is deployed in all Bayesian phylogenetic tree estimation software. While many researchers use MCMC in phylogenetic analyses, interpreting results and diagnosing problems with MCMC remain vexing issues to many biologists. In this manuscript, we will offer an overview of how MCMC is used in Bayesian phylogenetic inference, with a particular emphasis on complex hierarchical models, such as the fossilized birth-death (FBD) model. We will discuss strategies to diagnose common MCMC problems and troubleshoot difficult analyses, in particular convergence issues. We will show how the study design, the choice of models and priors, but also technical features of the inference tools themselves can all be adjusted to obtain the best results. Finally, we will also discuss the unique challenges created by the incorporation of fossil information in phylogenetic inference, and present tips to address them.

Developing a bioinformatics pipeline for comparative protein classification analysis

BACKGROUND

Protein classification is a task of paramount importance in various fields of biology. Despite the great momentum of modern implementation of protein classification, machine learning techniques such as Random Forest and Neural Network could not always be used for several reasons: data collection, unbalanced classification or labelling of the data.As an alternative, I propose the use of a bioinformatics pipeline to search for and classify information from protein databases. Hence, to evaluate the efficiency and accuracy of the pipeline, I focused on the carotenoid biosynthetic genes and developed a filtering approach to retrieve orthologs clusters in two well-studied plants that belong to the Brassicaceae family: Arabidopsis thaliana and Brassica rapa Pekinensis group. The result obtained has been compared with previous studies on carotenoid biosynthetic genes in B. rapa where phylogenetic analysis was conducted.

RESULTS

The developed bioinformatics pipeline relies on commercial software and multiple databeses including the use of phylogeny, Gene Ontology terms (GOs) and Protein Families (Pfams) at a protein level. Furthermore, the phylogeny is coupled with "population analysis" to evaluate the potential orthologs. All the steps taken together give a final table of potential orthologs. The phylogenetic tree gives a result of 43 putative orthologs conserved in B. rapa Pekinensis group. Different A. thaliana proteins have more than one syntenic ortholog as also shown in a previous finding (Li et al., BMC Genomics 16(1):1-11, 2015).

CONCLUSIONS

This study demonstrates that, when the biological features of proteins of interest are not specific, I can rely on a computational approach in filtering steps for classification purposes. The comparison of the results obtained here for the carotenoid biosynthetic genes with previous research confirmed the accuracy of the developed pipeline which can therefore be applied for filtering different types of datasets.

The Occurrence Birth-Death Process for combined-evidence analysis in macroevolution and epidemiology

Phylodynamic models generally aim at jointly inferring phylogenetic relationships, model parameters, and more recently, the number of lineages through time, based on molecular sequence data. In the fields of epidemiology and macroevolution, these models can be used to estimate, respectively, the past number of infected individuals (prevalence) or the past number of species (paleodiversity) through time. Recent years have seen the development of “total-evidence” analyses, which combine molecular and morphological data from extant and past sampled individuals in a unified Bayesian inference framework. Even sampled individuals characterized only by their sampling time, that is, lacking morphological and molecular data, which we call occurrences, provide invaluable information to estimate the past number of lineages. Here, we present new methodological developments around the fossilized birth–death process enabling us to (i) incorporate occurrence data in the likelihood function; (ii) consider piecewise-constant birth, death, and sampling rates; and (iii) estimate the past number of lineages, with or without knowledge of the underlying tree. We implement our method in the RevBayes software environment, enabling its use along with a large set of models of molecular and morphological evolution, and validate the inference workflow using simulations under a wide range of conditions. We finally illustrate our new implementation using two empirical data sets stemming from the fields of epidemiology and macroevolution. In epidemiology, we infer the prevalence of the coronavirus disease 2019 outbreak on the Diamond Princess ship, by taking into account jointly the case count record (occurrences) along with viral sequences for a fraction of infected individuals. In macroevolution, we infer the diversity trajectory of cetaceans using molecular and morphological data from extant taxa, morphological data from fossils, as well as numerous fossil occurrences. The joint modeling of occurrences and trees holds the promise to further bridge the gap between traditional epidemiology and pathogen genomics, as well as paleontology and molecular phylogenetics. [Birth–death model; epidemiology; fossils; macroevolution; occurrences; phylogenetics; skyline.]

Early cephalopod evolution clarified through Bayesian phylogenetic inference

BACKGROUND

Despite the excellent fossil record of cephalopods, their early evolution is poorly understood. Different, partly incompatible phylogenetic hypotheses have been proposed in the past, which reflected individual author's opinions on the importance of certain characters but were not based on thorough cladistic analyses. At the same time, methods of phylogenetic inference have undergone substantial improvements. For fossil datasets, which typically only include morphological data, Bayesian inference and in particular the introduction of the fossilized birth-death model have opened new possibilities. Nevertheless, many tree topologies recovered from these new methods reflect large uncertainties, which have led to discussions on how to best summarize the information contained in the posterior set of trees.

RESULTS

We present a large, newly compiled morphological character matrix of Cambrian and Ordovician cephalopods to conduct a comprehensive phylogenetic analysis and resolve existing controversies. Our results recover three major monophyletic groups, which correspond to the previously recognized Endoceratoidea, Multiceratoidea, and Orthoceratoidea, though comprising slightly different taxa. In addition, many Cambrian and Early Ordovician representatives of the Ellesmerocerida and Plectronocerida were recovered near the root. The Ellesmerocerida is para- and polyphyletic, with some of its members recovered among the Multiceratoidea and early Endoceratoidea. These relationships are robust against modifications of the dataset. While our trees initially seem to reflect large uncertainties, these are mainly a consequence of the way clade support is measured. We show that clade posterior probabilities and tree similarity metrics often underestimate congruence between trees, especially if wildcard taxa are involved.

CONCLUSIONS

Our results provide important insights into the earliest evolution of cephalopods and clarify evolutionary pathways. We provide a classification scheme that is based on a robust phylogenetic analysis. Moreover, we provide some general insights on the application of Bayesian phylogenetic inference on morphological datasets. We support earlier findings that quartet similarity metrics should be preferred over the Robinson-Foulds distance when higher-level phylogenetic relationships are of interest and propose that using a posteriori pruned maximum clade credibility trees help in assessing support for phylogenetic relationships among a set of relevant taxa, because they provide clade support values that better reflect the phylogenetic signal.

New opabiniid diversifies the weirdest wonders of the euarthropod stem group

Once considered 'weird wonders' of the Cambrian, the emblematic Burgess Shale animals Anomalocaris and Opabinia are now recognized as lower stem-group euarthropods and have provided crucial data for constraining the polarity of key morphological characters in the group. Anomalocaris and its relatives (radiodonts) had worldwide distribution and survived until at least the Devonian. However, despite intense study, Opabinia remains the only formally described opabiniid to date. Here we reinterpret a fossil from the Wheeler Formation of Utah as a new opabiniid, Utaurora comosa nov. gen. et sp. By visualizing the sample of phylogenetic topologies in treespace, our results fortify support for the position of U. comosa beyond the nodal support traditionally applied. Our phylogenetic evidence expands opabiniids to multiple Cambrian stages. Our results underscore the power of treespace visualization for resolving imperfectly preserved fossils and expanding the known diversity and spatio-temporal ranges within the euarthropod lower stem group.

Evolution: Morphological saturation and release in mammals

Mammal evolution in the Mesozoic was thought to be heavily constrained by competition and predation by dinosaurs. A new study suggests that placental mammals remained constrained for several million years after non-avian dinosaurs perished, perhaps due to competition from archaic mammals.

Investigating Morphological Complexes Using Informational Dissonance and Bayes Factors: A Case Study in Corbiculate Bees

It is widely recognized that different regions of a genome often have different evolutionary histories and that ignoring this variation when estimating phylogenies can be misleading. However, the extent to which this is also true for morphological data is still largely unknown. Discordance among morphological traits might plausibly arise due to either variable convergent selection pressures or else phenomena such as hemiplasy. Here, we investigate patterns of discordance among 282 morphological characters, which we scored for 50 bee species particularly targeting corbiculate bees, a group that includes the well-known eusocial honeybees and bumblebees. As a starting point for selecting the most meaningful partitions in the data, we grouped characters as morphological modules, highly integrated trait complexes that as a result of developmental constraints or coordinated selection we expect to share an evolutionary history and trajectory. In order to assess conflict and coherence across and within these morphological modules, we used recently developed approaches for computing Bayesian phylogenetic information allied with model comparisons using Bayes factors. We found that despite considerable conflict among morphological complexes, accounting for among-character and among-partition rate variation with individual gamma distributions, rate multipliers, and linked branch lengths can lead to coherent phylogenetic inference using morphological data. We suggest that evaluating information content and dissonance among partitions is a useful step in estimating phylogenies from morphological data, just as it is with molecular data. Furthermore, we argue that adopting emerging approaches for investigating dissonance in genomic datasets may provide new insights into the integration and evolution of anatomical complexes. [Apidae; entropy; morphological modules; phenotypic integration; phylogenetic information.].

A relictual troglomorphic harvestman discovered in a volcanic cave of western Argentina: Otilioleptes marcelae, new genus, new species, and Otilioleptidae, new family (Arachnida, Opiliones, Gonyleptoidea)

The troglomorphic harvestman Otilioleptes marcelae gen. nov., sp. nov. from the basaltic cave Doña Otilia, Payunia region, Mendoza Province, Argentina, is described. Its systematic affinities were studied through cladistic and Bayesian analyses that included representatives of Gonyleptoidea; it was determined to represent a new monotypic family, Otilioleptidae fam. nov., occupying a basal position within the clade Laminata. This species shows accentuated troglomorphic traits, typical for troglobitic harvestmen: elongated appendages, depigmentation, reduction of eyes and fading of scutal sulci. Additionally, it almost lacks sexual dimorphism, the distal portion of coxa IV is not completely fused to the stigmatic segment, and penis morphology is remarkably divergent with other Laminata; these features cannot be attributed to cave adaptation and may reflect early lineage divergence. Otilioleptes marcelae is the first troglobitic gonyleptoid known from a lava tube. The xeric environments around the cave (Patagonian ecoregion) and the paleoenvironmental history of the area suggest the relictual character of O. marcelae. Scattered evidence supports a long time evolutionary scenario and a presumable relationship with the Chilean opiliofauna (especially with genus Osornogyndes). A comparative overview of all known troglobitic gonyleptoids is provided. The urgent need to protect this new species and its unique cave environment is emphasized.

Estimating the phylogeny of geoemydid turtles (Cryptodira) from landmark data: an assessment of different methods

BACKGROUND

In the last 20 years, a general picture of the evolutionary relationships between geoemydid turtles (ca. 70 species distributed over the Northern hemisphere) has emerged from the analysis of molecular data. However, there is a paucity of good traditional morphological characters that correlate with the phylogeny, which are essential for the robust integration of fossil and molecular data. Part of this problem might be due to intrinsic limitations of traditional discrete characters. Here, we explore the use of continuous data in the form of 3D coordinates of homologous landmarks on the turtle shell for phylogenetic inference and the phylogenetic placement of single species on a scaffold molecular tree. We focus on the performance yielded by sampling the carapace and/or plastral lobes and using various phylogenetic methods.

METHODS

We digitised the landmark coordinates of the carapace and plastron of 42 and 46 extant geoemydid species, respectively. The configurations were superimposed and we estimated the phylogenetic tree of geoemydids with landmark analysis under parsimony, traditional Farris parsimony, unweighted squared-change parsimony, maximum likelihood with a Brownian motion model, and neighbour-joining on a matrix of pairwise Procrustes distances. We assessed the performance of those analyses by comparing the trees against a reference phylogeny obtained from seven molecular markers. For comparisons between trees we used difference measures based on quartets and splits. We used the same reference tree to evaluate phylogenetic placement performance by a leave-one-out validation procedure.

RESULTS

Whatever method we used, similarity to the reference phylogeny was low. The carapace alone gave slightly better results than the plastron or the complete shell. Assessment of the potential for placement of single species on the reference tree with landmark data gave much better results, with similar accuracy and higher precision compared to the performance of discrete characters with parsimony.