Bayesian Phylogenetic Inference Research Articles

On the importance of assessing topological convergence in Bayesian phylogenetic inference.

Modern phylogenetics research is often performed within a Bayesian framework, using sampling algorithms such as Markov chain Monte Carlo (MCMC) to approximate the posterior distribution. These algorithms require careful evaluation of the quality of the generated samples. Within the field of phylogenetics, one frequently adopted diagnostic approach is to evaluate the effective sample size and to investigate trace graphs of the sampled parameters. A major limitation of these approaches is that they are developed for continuous parameters and therefore incompatible with a crucial parameter in these inferences: the tree topology. Several recent advancements have aimed at extending these diagnostics to topological space. In this reflection paper, we present two case studies-one on Ebola virus and one on HIV-illustrating how these topological diagnostics can contain information not found in standard diagnostics, and how decisions regarding which of these diagnostics to compute can impact inferences regarding MCMC convergence and mixing. Our results show the importance of running multiple replicate analyses and of carefully assessing topological convergence using the output of these replicate analyses. To this end, we illustrate different ways of assessing and visualizing the topological convergence of these replicates. Given the major importance of detecting convergence and mixing issues in Bayesian phylogenetic analyses, the lack of a unified approach to this problem warrants further action, especially now that additional tools are becoming available to researchers.

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. Values for all model parameters need to be evaluated as well. 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.

Variational Supertrees for Bayesian Phylogenetics

Bayesian phylogenetic inference is powerful but computationally intensive. Researchers may find themselves with two phylogenetic posteriors on overlapping data sets and may wish to approximate a combined result without having to re-run potentially expensive Markov chains on the combined data set. This raises the question: given overlapping subsets of a set of taxa (e.g. species or virus samples), and given posterior distributions on phylogenetic tree topologies for each of these taxon sets, how can we optimize a probability distribution on phylogenetic tree topologies for the entire taxon set? In this paper we develop a variational approach to this problem and demonstrate its effectiveness. Specifically, we develop an algorithm to find a suitable support of the variational tree topology distribution on the entire taxon set, as well as a gradient-descent algorithm to minimize the divergence from the restrictions of the variational distribution to each of the given per-subset probability distributions, in an effort to approximate the posterior distribution on the entire taxon set.

Curating BOLD records via Bayesian phylogenetic assignments enables harmonization of regional subgeneric classifications and cryptic species detection within the genus Tachina (Diptera: Tachinidae)

Abstract DNA barcoding is a popular tool for species identification of insect samples, with important applications for plant protection. However, Barcode of Life Database queries related to tachinid samples can produce ambiguous results due to contradictory species assignments. Therefore, we applied Bayesian phylogenetic inference to 811 Tachina Meigen, 1803 COI-5P sequences containing all contradictory species assignments of Tachina Barcode Index Numbers. Based on phylogenetic assignment, the assemble species by automatic partitioning (ASAP) analysis, the MonoPhy test and analyses of genetic divergence, we identified 805 sequences representing species of the Tachina genus, whereas six sequences were incorrectly assigned to Tachina. The dataset contained 21 described species and at least seven unidentified species. Additionally, we found that the described species Tachina marklini Zetterstedt, 1838, includes two cryptic species based on ASAP partitioning of sequences, phylogenetic inference and geographical metadata. Furthermore, we harmonized conflicting subgeneric classifications of the Palearctic and Nearctic by employing different subgenera assignments from both partitions. We aimed at monophyletic subgenera partitions. We largely confirmed the validity of the Palearctic Tachina subgenera and Nowickia as a subgenus of Tachina. However, Palearctic Nowickia species formerly allocated to the outdated genus Fabriciella appeared to constitute one monophyletic group with the subgenus Rhachogaster. We conclude that this set of bioinformatics tools is suitable for curating COI-5P-based DNA barcode libraries. Although, curation is limited due to possible species introgression, horizontal gene transfer, incomplete lineage sorting and human errors the resulting dataset enabled the revision of subgenera concepts and the unambiguous cryptic species detection.

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.

Sequential Bayesian Phylogenetic Inference.

The ideal approach to Bayesian phylogenetic inference is to estimate all parameters of interest jointly in a single hierarchical model. However, this is often not feasible in practice due to the high computational cost. Instead, phylogenetic pipelines generally consist of sequential analyses, whereby a single point estimate from a given analysis is used as input for the next analysis (e.g., a single multiple sequence alignment is used to estimate a gene tree). In this framework, uncertainty is not propagated from step to step, which can lead to inaccurate or spuriously confident results. Here, we formally develop and test a sequential inference approach for Bayesian phylogenetic inference, which uses importance sampling to generate observations for the next step of an analysis pipeline from the posterior distribution produced in the previous step. Our sequential inference approach presented here not only accounts for uncertainty between analysis steps, but also allows for greater flexibility in software choice (and hence model availability) and can be computationally more efficient than the traditional joint inference approach when multiple models are being tested. We show that our sequential inference approach is identical in practice to the joint inference approach only if sufficient information in the data is present (a narrow posterior distribution) and/or sufficiently many importance samples are used. Conversely, we show that the common practice of using a single point estimate can be biased, e.g., a single phylogeny estimate to transform an unrooted phylogeny into a time-calibrated phylogeny. We demonstrate the theory of sequential Bayesian inference using both a toy example and an empirical case study of divergence-time estimation in insects using a relaxed clock model from transcriptome data. In the empirical example, we estimate three posterior distributions of branch lengths from the same data (DNA character matrix with a GTR+Γ+I substitution model, an amino acid data matrix with empirical substitution models, and an amino acid data matrix with the PhyloBayes CAT-GTR model). Finally, we apply three different node-calibration strategies and show that divergence-time estimates are affected by both the data source and underlying substitution process to estimate branch lengths as well as the node-calibration strategies. Thus, our new sequential Bayesian phylogenetic inference provides the opportunity to efficiently test different approaches for divergence time estimation, including branch-length estimation from other software.

Variational Bayesian phylogenies through matrix representation of tree space.

In this article, we study the distance matrix as a representation of a phylogeny by way of hierarchical clustering. By defining a multivariate normal distribution on (a subset of) the entries in a matrix, this allows us to represent a distribution over rooted time trees. Here, we demonstrate tree distributions can be represented accurately this way for a number of published tree distributions. Though such a representation does not map to unique trees, restriction to a subspace, in particular one we call a "cube", makes the representation bijective at the cost of not being able to represent all possible trees. We introduce an algorithm "cubeVB" specifically for cubes and show through well calibrated simulation study that it is possible to recover parameters of interest like tree height and length. Although a cube cannot represent all of tree space, it is a great improvement over a single summary tree, and it opens up exciting new opportunities for scaling up Bayesian phylogenetic inference. We also demonstrate how to use a matrix representation of a tree distribution to get better summary trees than commonly used maximum clade credibility trees. An open source implementation of the cubeVB algorithm is available from https://github.com/rbouckaert/cubevb as the cubevb package for BEAST 2.

First Byzantinia from Afro-Arabia and the evolutionary history of extinct cricetodontine rodents investigated through Bayesian phylogenetic inference

The Cricetodontinae is a subfamily of extinct rodents from Europe, northern Africa, and Asia. Byzantinia is a cricetodontine genus that currently includes 10 species. This genus originated in Anatolia in the late Middle Miocene and became extinct at the end of the Miocene. Until now, Byzantinia was known only from Anatolia and Greece. Here, we report isolated molars of Byzantinia from a new locality close to Zahleh, Lebanon. These represent the first remains of Byzantinia from the Arabian area. All these teeth but one, which is very close to Byzantinia dardanellensis, belong to the new taxon Byzantinia rosamariae sp. nov. The evolutionary position of the two Lebanese Byzantinia species allows us to infer an age for this site of approximately 10.9–10 Ma. Bayesian tip-dating phylogenetic analyses, using morphological data for a large variety of cricetodontines, revealed that Anatolia served as the primary centre for speciation and dispersal of this rodent subfamily. This approach allowed us to infer the biogeographical history and time of divergence of the main cricetodontine lineages and sheds light on the evolutionary history of this group. The evolutionary position of the new Lebanese species is intermediate between Byzantinia sp. from Direcik I (Turkey) and B. nikosi from Biodrak (Greece), from which it diverged c. 11.85 Ma. These new Lebanese fossils provide the first physical evidence of the dispersal of these rodents into Afro-Arabia. http://zoobank.org/urn:lsid:zoobank.org:pub:2D8FD3C8-26E1-4C62-8D65-9D58666D70A3

Identification of a novel HIV-1 third-generation circulating recombinant form (CRF126_0755) in Guangdong, China

The genetic recombination patterns and genetic distribution of HIV-1 are valuable for elucidating the epidemic and genetic diversity of HIV. Numerous HIV-1 circulating recombinant forms (CRFs) have recently emerged and disseminated rapidly. In China, at least 32 CRFs have been reported to account for more than 80% of all HIV infections. However, CRFs derived from the CRF07_BC and CRF55_01B lineages have never been recorded. Here, a novel third-generation CRF involving HIV-1 was identified in four HIV-1-infected patients in Guangdong, China, who had no epidemiological association with each other. Phylogenetic and recombinant analyses confirmed that these strains shared highly similar recombination patterns, with the CRF07_BC backbone substituted by a CRF55_01B segment; therefore, these strains were classified as CRF126_0755. This is the first study of a CRF derived from CRF07_BC and CRF55_01B. Bayesian phylogenetic inference suggested that CRF126_0755 originated in approximately 2005-2007. The present findings reveal that the genotype composition of HIV-1 has become more complex than that of other viruses and highlight the urgent need for continuous molecular screening and epidemic surveillance within HIV-1-infected populations to advance our understanding of viral transmission mechanisms.

Multilocus Molecular Phylogeny of the Umbilicaria aprina Group (Umbilicariaceae, Lichenized Ascomycota) Supports Species Level and Neo-Endemic Status of Umbilicaria krascheninnikovii.

The Northeast Asian endemic species of lichen-forming fungus Umbilicaria krascheninnikovii is herein discussed in the global context of biogeography and phylogeny of the U. aprina group. The name U. krascheninnikovii has been erroneously used by lichenologists for Umbilicaria spp. from high latitudes or altitudes worldwide, as there are omphalodisc apothecia and rough "crystals" of a necral layer on the upper surface. To test the monophyly and phylogenetic relationships within the U. aprina group, four independent DNA regions (nrITS/5.8S, RPB2, mtLSU, and mtSSU) were used for six rare species, including a dozen specimens of U. krascheninnikovii from its locus classicus in Kamchatka. The study is based on the phylograms obtained using maximum likelihood and a Bayesian phylogenetic inference framework. As a result of phylogenetic and biogeographic analyses, it was shown that U. krascheninnikovii is a neo-endemic of the areas of modern volcanism in Kamchatka, Japan, as well as in the Kurile Islands, where this species was recorded for the first time. The morphology of U. krascheninnikovii is herein described and illustrated. Increasing the role of the sexual process and reducing asexual thalloconidiogenesis are shown to be apomorphic traits in the U. aprina group. The combination of sexual and asexual reproduction provides adaptive advantages in changing environmental conditions.

Ranked Subtree Prune and Regraft

Phylogenetic trees are a mathematical formalisation of evolutionary histories between organisms, species, genes, cancer cells, etc. For many applications, e.g. when analysing virus transmission trees or cancer evolution, (phylogenetic) time trees are of interest, where branch lengths represent times. Computational methods for reconstructing time trees from (typically molecular) sequence data, for example Bayesian phylogenetic inference using Markov Chain Monte Carlo (MCMC) methods, rely on algorithms that sample the treespace. They employ tree rearrangement operations such as SPR\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extrm{SPR}$$\\end{document} (Subtree Prune and Regraft) and NNI\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extrm{NNI}$$\\end{document} (Nearest Neighbour Interchange) or, in the case of time tree inference, versions of these that take times of internal nodes into account. While the classic SPR\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extrm{SPR}$$\\end{document} tree rearrangement is well-studied, its variants for time trees are less understood, limiting comparative analysis for time tree methods. In this paper we consider a modification of the classical SPR\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extrm{SPR}$$\\end{document} rearrangement on the space of ranked phylogenetic trees, which are trees equipped with a ranking of all internal nodes. This modification results in two novel treespaces, which we propose to study. We begin this study by discussing algorithmic properties of these treespaces, focusing on those relating to the complexity of computing distances under the ranked SPR\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extrm{SPR}$$\\end{document} operations as well as similarities and differences to known tree rearrangement based treespaces. Surprisingly, we show the counterintuitive result that adding leaves to trees can actually decrease their ranked SPR\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extrm{SPR}$$\\end{document} distance, which may have an impact on the results of time tree sampling algorithms given uncertain “rogue taxa”.

First Report of Cladosporium scabrellum Causing Stipe Spot Disease of Morchella importuna in China.

Morchella is a genus of edible and medicinal fungi with a global distribution and economic value. Artificial cultivation of Morchella has risen to 8,000 hectares in China in last 5 years (Zhao et al. 2020). In the early March of 2021, a peculiar stipe spot disease was first detected on Morchella importuna at a manufacturing base in Yangxian county (33°02' N, 108°11' E), Shaanxi, China. Several dark brown patches were observed on the surface of M. importuna fruiting bodies, with approximately 40% of the fruiting bodies infected at a late stage of production. This symptom typically manifests in March to May each year during the growing season of M. importuna. Following infection of the fruiting body, a light brown spot (2 to 4 mm) appears at the base of the stipe when the fruiting body is about 3 cm long. The spot progressively darkens and proceeds to cover the large stipe of the fruiting body. At 5 to 7 days after the appearance of the first spot, infected young fruiting bodies soften and decay. Temperature (>20℃) or humidity (80 to 90%) increases the likelihood of disease. To isolate the causal agent, the edge of a lesion was carefully scraped, inoculated into potato dextrose agar (PDA), and then incubated in the dark at 24±2°C (Bensch et al. 2010). The colonies were grayish-green in front, green to black on the reverse, and grew as concentric rings after 14 days of culture. The conidiophore was thin, branched with warty ramoconidia, and 2.5 to 4.7 µm long by 1.5 to 2.0 µm wide (length×width, mean=0.72, n=150). The ramoconidia were cylindrical and long at 14.3 to 28.7 µm by 6.4 to 10.7 µm (length×width, mean=2.52, n=150); the secondary ramoconidia were narrower and rod-shaped at 3.8 to 4.9 µm by 2.4 to 3.6 µm (length×width, mean=0.19, n=150). These morphological features were consistent with Cladosporium scabrellum (Bensch et al. 2012). Genomic DNA was extracted from mycelia of the pathogen using an Ezup column fungal genomic DNA extraction kit (Sangon Biotech, Shanghai, China). To confirm the identity of the pathogen (C. scabrellum), the genomic fragments for the internal transcribed spacer (ITS), translation elongation factor 1 alpha (EF-1α) and actin (ACT) gene of the isolate were amplified by PCR (Carbone et al. 1999; Walker et al. 2016; Xu et al. 2021). The resultant sequence was uploaded to the GenBank database with accession number (GeneBank ID of gene ITS, EF-1α, ACT are MZ736660, OQ982380, OQ982381, respectively). BLAST results showed >99% identity with those of C. scabrellum(GeneBank ID of gene ITS, EF-1α, ACT are HM148195, HM148440, HM148685, respectively). Phylogenetic analysis was performed using the maximum-likelihood (ML) method and Bayesian phylogenetic inference (BI) analyses in MEGA7 software (Kumar et al., 2018). For pathogenicity testing, 20 naturally occurring M. importuna fruiting bodies in an artificial climate chamber were randomly selected, inoculated by spraying with a conidial suspension of the pathogen (1×106 conidia/ml sterile water), and incubated at 20°C and 90 to 95% humidity. On the third day after inoculation, a yellow-brown spot appeared around the grafting sites, the spot gradually darkened and began to cover the stipe; the infection rate was 80 to 85%. Ten control fruiting bodies of M. importuna sprayed with sterile water grew normally and were symptomless. The pathogen was reisolated from infected fruiting bodies and confirmed as C. scabrellum by morphology and ITS, EF-1α, ACT sequence. To our knowledge, this is the first report of M. importuna stipe spot disease caused by C. scabrellum. According to a farmer in Yangxian, these spots rapidly spread every year, drastically reducing the production and market value of Morchella. This is a major problem for producers of this edible mushroom.

Bayesian phylogenetic analysis of pitch-accent systems based on accentual class merger: a new method applied to Japanese dialects

Abstract Unlike studies of the evolutionary relationship between languages, the dialect-level variation within a language has seldom been studied within the framework of a phylogenetic tree, because frequent lexical borrowing muddles the evidence of shared ancestry. The phonological history of Japanese is an exceptional case study where the phenomenon called accentual class merger enables the phylogenetic analysis of dialectal pitch-accent systems in a way that is not subject to borrowing. However, previous studies have lacked statistical analysis and failed to evaluate the relative credence of alternative hypotheses. Here we developed a novel substitution model that describes the mutation of pitch-accent systems driven by accentual class merger and integrated the model into the framework of Bayesian phylogenetic inference with geographical diffusion. Applying the method to data on the pitch-accent variation in modern Japanese dialects and historical documents collected from literature, we reconstructed the evolutionary history and spatial diffusion of pitch-accent systems. Our result supports the monophyly of each of three groups of pitch-accent systems in conventional categorization, namely Tokyo type, Keihan type, and N-kei (N-pattern) type of Kyushu, whereas the monophyly of the Tokyo type has been highly controversial in previous studies. The divergence time of the mainland pitch-accent systems was estimated to be from mid-Kofun to early Heian period. Also, it is suggested that the modern Kyoto dialect did not inherit its accent patterns from Bumoki but from an unrecorded lineage which survived from the Muromachi period. Analyses on geographical diffusion suggest that the most recent common ancestor (MRCA) of all the taxa and that of Keihan type were located in or around the Kinki region, whereas the MRCA of N-kei type was located in northern to central Kyushu. The geographical location of the MRCA of Tokyo type remains unclear, but the Kinki and Kanto regions are the most plausible candidates.

Evolutionary Analysis of a Parrot Bornavirus 2 Detected in a Sulphur-Crested Cockatoo (Cacatua galerita) Suggests a South American Ancestor.

Parrot bornavirus (PaBV) is an RNA virus that causes Proventricular Dilatation Disease (PDD), neurological disorders, and death in Psittaciformes. Its diversity in South America is poorly known. We examined a Cacatua galerita presenting neuropathies, PDD, and oculopathies as the main signs. We detected PaBV through reverse transcription polymerase chain reaction (RT-PCR) and partial sequencing of the nucleoprotein (N) and matrix (M) genes. Maximum likelihood and Bayesian phylogenetic inferences classified it as PaBV-2. The nucleotide identity of the sequenced strain ranged from 88.3% to 90.3% against genotype PaBV-2 and from 80.2% to 84.4% against other genotypes. Selective pressure analysis detected signs of episodic diversifying selection in both the N and M genes. No recombination events were detected. Phylodynamic analysis estimated the time to the most recent common ancestor (TMRCA) as the year 1758 for genotype PaBV-2 and the year 1049 for the Orthobornavirus alphapsittaciforme species. Substitution rates were estimated at 2.73 × 10-4 and 4.08 × 10-4 substitutions per year per site for N and M, respectively. The analysis of population dynamics showed a progressive decline in the effective population size during the last century. Timescale phylogeographic analysis revealed a potential South American ancestor as the origin of genotypes 1, 2, and 8. These results contribute to our knowledge of the evolutionary origin, diversity, and dynamics of PaBVs in South America and the world. Additionally, it highlights the importance of further studies in captive Psittaciformes and the potential impact on endangered wild birds.

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. Values for all model parameters need to be evaluated as well. 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.

Whole genome sequencing of outbreak strains from 2017 to 2018 reveals an endemic clade of dengue 1 virus in Cameroon

ABSTRACT Dengue fever is expanding as a global public health threat including countries within Africa. For the past few decades, Cameroon has experienced sporadic cases of arboviral infections including dengue fever. Here, we conducted genomic analyses to investigate the origin and phylogenetic profile of Cameroon DENV-1 outbreak strains and predict the impact of emerging therapeutics on these strains. Bayesian and maximum-likelihood phylogenetic inference approaches were employed in virus evolutionary analyses. An in silico analysis was performed to assess the divergence in immunotherapeutic and vaccine targets in the new genomes. Six complete DENV-1 genomes were generated from 50 samples that met a clinical definition for DENV infection. Phylogenetic analyses revealed that the strains from the current study belong to a sub-lineage of DENV-1 genotype V and form a monophyletic taxon with a 2012 strain from Gabon. The most recent common ancestor (TMRCA) of the Cameroon and Gabon strains was estimated to have existed around 2008. Comparing our sequences to the vaccine strains, 19 and 15 amino acid (aa) substitutions were observed in the immuno-protective prM-E protein segments of the Dengvaxia® and TetraVax-DV-TV003 vaccines, respectively. Epitope mapping revealed mismatches in aa residues at positions E155 and E161 located in the epitope of the human anti-DENV-1 monoclonal antibody HMAb 1F4. The new DENV strains constitute a conserved genomic pool of viruses endemic to the Central African region that needs prospective monitoring to track local viral evolution. Further work is needed to ascertain the performance of emerging therapeutics in DENV strains from the African region.

Word order evolves at similar rates in main and subordinate clauses

Abstract In syntactic change, it remains an open issue whether word orders are more conservative or innovative in subordinate clauses compared with main clauses. Using 47 dependency-annotated corpora and Bayesian phylogenetic inference, we explore the evolution of S/V, V/O, and S/O orders across main and subordinate clauses in Indo-European. Our results reveal similar rates of change across clause types, with no evidence for any inherent conservatism of subordinate or main clauses. Our models also support evolutionary biases towards SV, VO, and SO orders, consistent with theories of dependency length minimization that favor verb-medial orders and with theories of a subject preference that favor SO orders. Finally, our results show that while the word order in the proto-language cannot be estimated with any reasonable degree of certainty, the early history of the family was dominated by a moderate preference for SVO orders, with substantial uncertainty between VO and OV orders in both main and subordinate clauses.

Nucleotide Substitution Model Selection Is Not Necessary for Bayesian Inference of Phylogeny With Well-Behaved Priors.

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 not to overfit. In phylogenetics, the most common model selection scenario concerns selecting an adequate substitution and partition model for sequence evolution to infer a phylogenetic tree. Previously, several studies showed that substitution model under-parameterization can bias phylogenetic studies. 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 $\text{GTR}+\Gamma+\text{I}$ substitution model, including over-splitting the data into additional subsets (i.e., applying partitioned models). We explored 4 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 and over-partitioning but only under our new prior settings. All 3 current 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 and more effort should focus on more complex and biologically realistic substitution models.

Cinderella’s Family Tree. A Phylomemetic Case Study of ATU 510/511

Abstract This case study contributes to recent attempts to apply “phylomemetic” methods derived from computational biology to oral traditions, where the aim is to trace the mutation and diversification of folk narratives as they get passed on from generation to generation and spread from society to society. Our study focuses on one of the most famous and widespread tales in the folktale record: Cinderella. Thousands of Cinderella-like stories have been documented from around the world, which folklorists have attempted to classify into different “types” representing distinct, though related, international traditions. The most comprehensive of Cinderella typologies was developed by Anna Birgitta Rooth (1951), who divided the tales into five principal types: A, B, AB, BI and C, and suggested several hypotheses pertaining to their origins and relationships to one another. Here, we test Rooth’s theories on a sample of 266 versions of Cinderella using Bayesian phylogenetic inference, phylogenetic networks (NeighborNet) and a model-based clustering method that was originally designed to elicit population structure from multi-locus genotype data (implemented in the program STRUCTURE). Our results find varying levels of support for the types identified by Rooth, and suggest that mixing among traditions was widespread, especially in Type AB tales. Despite these complexities, it was still possible to delineate and quantify the influence of distinct ancestral sources on the variation observed in contemporary versions of Cinderella. Our study highlights the value and versatility of phylomemetic methods in uncovering the historical relationships among types and sub-types of international folktale, as well as the evolutionary processes that have shaped them.

The ClaDS rate-heterogeneous birth-death prior for full phylogenetic inference in BEAST2.

Bayesian phylogenetic inference requires a tree prior, which models the underlying diversification process that gives rise to the phylogeny. Existing birth-death diversification models include a wide range of features, for instance, lineage-specific variations in speciation and extinction (SSE) rates. While across-lineage variation in SSE rates is widespread in empirical datasets, few heterogeneous rate models have been implemented as tree priors for Bayesian phylogenetic inference. As a consequence, rate heterogeneity is typically ignored when reconstructing phylogenies, and rate heterogeneity is usually investigated on fixed trees. In this paper, we present a new BEAST2 package implementing the cladogenetic diversification rate shift (ClaDS) model as a tree prior. ClaDS is a birth-death diversification model designed to capture small progressive variations in birth and death rates along a phylogeny. Unlike previous implementations of ClaDS, which were designed to be used with fixed, user-chosen phylogenies, our package is implemented in the BEAST2 framework and thus allows full phylogenetic inference, where the phylogeny and model parameters are co-estimated from a molecular alignment. Our package provides all necessary components of the inference, including a new tree object and operators to propose moves to the Monte-Carlo Markov chain. It also includes a graphical interface through BEAUti. We validate our implementation of the package by comparing the produced distributions to simulated data and show an empirical example of the full inference, using a dataset of cetaceans.