Bayesian phylogenetics is now facing a critical point. Over the last 20 years, Bayesian methods have reshaped phylogenetic inference and gained widespread popularity due to their high accuracy, the ability to quantify the uncertainty of inferences and the possibility of accommodating multiple aspects of evolutionary processes in the models that are used. Unfortunately, Bayesian methods are computationally expensive, and typical applications involve at most a few hundred sequences. This is problematic in the age of rapidly expanding genomic data and increasing scope of evolutionary analyses, forcing researchers to resort to less accurate but faster methods, such as maximum parsimony and maximum likelihood. Does this spell doom for Bayesian methods? Not necessarily. Here, we discuss some recently proposed approaches that could help scale up Bayesian analyses of evolutionary problems considerably. We focus on two particular aspects: online phylogenetics, where new data sequences are added to existing analyses, and alternatives to Markov chain Monte Carlo (MCMC) for scalable Bayesian inference. We identify five specific challenges and discuss how they might be overcome. We believe that online phylogenetic approaches and Sequential Monte Carlo hold great promise and could potentially speed up tree inference by orders of magnitude. We call for collaborative efforts to speed up the development of methods for real-time tree expansion through online phylogenetics.

Mangrove pit vipers of the Trimeresurus purpureomaculatus-erythrurus complex are the only species of viper known to inhabit mangroves. Despite serving integral ecological functions in mangrove ecosystems, the evolutionary history, distribution, and species boundaries of mangrove pit vipers remain poorly understood, partly due to overlapping distributions, confusing phenotypic variations, and the lack of focused studies. Here, we present the first genomic study on mangrove pit vipers and introduce a robust hypothesis-driven species delimitation framework that considers gene flow and phylogenetic uncertainty in conjunction with a novel application of a new class of speciation-based delimitation model implemented through the program Delineate.Our results showed that gene flow produced phylogenetic conflict in our focal species and substantiates the artefactual branch effect where highly admixed populations appear as divergent non-monophyletic lineages arranged in a stepwise manner at the basal position of clades. Despite the confounding effects of gene flow, we were able to obtain unequivocal support for the recognition of a new species based on the intersection and congruence of multiple lines of evidence. This study demonstrates that an integrative hypothesis-driven approach predicated on the consideration of multiple plausible evolutionary histories, population structure/differentiation, gene flow, and the implementation of a speciation-based delimitation model can effectively delimit species in the presence of gene flow and phylogenetic conflict.

Natural selection plays a key role in deterministic evolution, as clearly illustrated by the multiple cases of repeated evolution of ecomorphological characters observed in adaptive radiations. Unlike most spiders, Dysdera species display a high variability of cheliceral morphologies, which has been suggested to reflect different levels of specialisation to feed on isopods. In this study, we integrate geometric morphometrics and experimental trials with a fully resolved phylogeny of the highly diverse endemic species from the Canary Islands to 1) quantitatively delimit the different cheliceral morphotypes present in the archipelago, 2) test their association with trophic specialisation, as reported for continental species, 3) reconstruct the evolution of these ecomorphs throughout the diversification of the group, 4) test the hypothesis of convergent evolution of the different morphotypes, and 5) examine whether specialisation constitutes a case of evolutionary irreversibility in this group. We show the existence of nine cheliceral morphotypes and uncovered their significance for trophic ecology. Further, we demonstrate that similar ecomorphs evolved multiple times in the archipelago, providing a novel study system to explain how convergent evolution and irreversibility due to specialization may be combined to shape phenotypic diversification in adaptive radiations.

Divergence time estimation is crucial to provide temporal signals for dating biologically important events, from species divergence to viral transmissions in space and time. With the advent of high-throughput sequencing, recent Bayesian phylogenetic studies have analyzed hundreds to thousands of sequences. Such large-scale analyses challenge divergence time reconstruction by requiring inference on highly-correlated internal node heights that often become computationally infeasible. To overcome this limitation, we explore a ratio transformation that maps the original N-1 internal node heights into a space of one height parameter and N-2 ratio parameters. To make the analyses scalable, we develop a collection of linear-time algorithms to compute the gradient and Jacobian-associated terms of the log-likelihood with respect to these ratios. We then apply Hamiltonian Monte Carlo sampling with the ratio transform in a Bayesian framework to learn the divergence times in four pathogenic viruses (West Nile virus, rabies virus, Lassa virus and Ebola virus) and the coralline red algae. Our method both resolves a mixing issue in the West Nile virus example and improves inference efficiency by at least 5-fold for the Lassa and rabies virus examples as well as for the algae example. Our method now also makes it computationally feasible to incorporate mixed-effects molecular clock models for the Ebola virus example, confirms the findings from the original study and reveals clearer multimodal distributions of the divergence times of some clades of interest. [Divergence time estimation, Bayesian inference, Hamiltonian Monte Carlo, ratio transformation, effective sample size, phylogenetics, pathogens.

In the presence of recombination individuals may inherit different regions of their genome from different ancestors, resulting in a mosaic of phylogenetic histories across their genome. Ancestral recombination graphs (ARGs) can capture how phylogenetic relationships vary across the genome due to recombination, but reconstructing ARGs from genomic sequence data is notoriously difficult. Here we present a method for reconciling discordant phylogenetic trees and reconstructing ARGs using maximum agreement forests (MAFs). Given two discordant trees, a MAF identifies the smallest possible set of topologically concordant subtrees present in both trees. We show how discordant trees can be reconciled through their MAF in a way that retains discordances strongly supported by sequence data while eliminating conflicts likely attributable to phylogenetic noise. We further show how MAFs and our reconciliation approach can be combined to select a path of local trees across the genome that maximizes the likelihood of the genomic sequence data, minimizes discordance between neighboring local trees, and identifies the recombination events necessary to explain remaining discordances to obtain a fully connected ARG. While heuristic, our ARG reconstruction approach is often as accurate as more exact methods while being much more computationally efficient. Moreover, important demographic parameters such as recombination rates can be accurately estimated from reconstructed ARGs. Finally, we apply our approach to plant infecting RNA viruses in the genus Potyvirus to demonstrate how true recombination events can be disentangled from phylogenetic noise using our ARG reconstruction methods.

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 GTR+Γ+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 and over-partitioning but only under our new prior settings. All three 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.

Despite the economic, ecological, and scientific importance of the genera Salix L. (willows) and Populus L. (poplars, cottonwoods, and aspens) Salicaceae, we know little about the sources of differences in species diversity between the genera and of the phylogenetic conflict that often confounds estimating phylogenetic trees. Salix subgenera and sections, in particular, have been difficult to classify, with one recent attempt termed a 'spectacular failure' due to a speculated radiation of the subgenera Vetrix and Chamaetia. Here we use targeted sequence capture to understand the evolutionary history of this portion of the Salicaceae plant family. Our phylogenetic hypothesis was based on 787 gene regions and identified extensive phylogenetic conflict among genes. Our analysis supported some previously described subgeneric relationships and confirmed polyphyly of others. Using an fbranch analysis we identified several cases of hybridization in deep branches of the phylogeny, which likely contributed to discordance among gene trees. In addition, we identified a rapid increase in diversification rate near the origination of the Vetrix-Chamaetia clade in Salix. This region of the tree coincided with several nodes that lacked strong statistical support, indicating a possible increase in incomplete lineage sorting due to rapid diversification. The extraordinary level of both recent and ancient hybridization in both Salix and Populus have played important roles in the diversification and diversity in these two genera.