Systematic Biology最新文献

Accurately reconstructing the reticulate histories of polyploids remains a central challenge for understanding plant evolution. Although phylogenetic networks can provide insights into relationships among polyploid lineages, inferring networks may be hindered by the complexities of homology determination in polyploid taxa. We use simulations to show that phasing alleles from allopolyploid individuals can improve phylogenetic network inference under the multispecies coalescent by obtaining the true network with fewer loci compared with haplotype consensus sequences or sequences with heterozygous bases represented as ambiguity codes. Phased allelic data can also improve divergence time estimates for networks, which is helpful for evaluating allopolyploid speciation hypotheses and proposing mechanisms of speciation. To achieve these outcomes in empirical data, we present a novel pipeline that leverages a recently developed phasing algorithm to reliably phase alleles from polyploids. This pipeline is especially appropriate for target enrichment data, where the depth of coverage is typically high enough to phase entire loci. We provide an empirical example in the North American Dryopteris fern complex that demonstrates insights from phased data as well as the challenges of network inference. We establish that our pipeline (PATÉ: Phased Alleles from Target Enrichment data) is capable of recovering a high proportion of phased loci from both diploids and polyploids. These data may improve network estimates compared with using haplotype consensus assemblies by accurately inferring the direction of gene flow, but statistical nonidentifiability of phylogenetic networks poses a barrier to inferring the evolutionary history of reticulate complexes.

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 important samples are used. Conversely, we show that the common practice of using a single point estimate can be biased, for example, a single phylogeny estimate can 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 3 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 3 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.

Rates of nucleotide substitution vary substantially across the Tree of Life, with potentially confounding effects on phylogenetic and evolutionary analyses. A large acceleration in mitochondrial substitution rate occurs in the cockroach family Nocticolidae, which predominantly inhabit subterranean environments. To evaluate the impacts of this among-lineage rate heterogeneity on estimates of phylogenetic relationships and evolutionary timescales, we analyzed nuclear ultraconserved elements (UCEs) and mitochondrial genomes from nocticolids and other cockroaches. Substitution rates were substantially elevated in nocticolid lineages compared with other cockroaches, especially in mitochondrial protein-coding genes. This disparity in evolutionary rates is likely to have led to different evolutionary relationships being supported by phylogenetic analyses of mitochondrial genomes and UCE loci. Furthermore, Bayesian dating analyses using relaxed-clock models inferred much deeper divergence times compared with a flexible local clock. Our phylogenetic analysis of UCEs, which is the first genome-scale study to include all 13 major cockroach families, unites Corydiidae and Nocticolidae and places Anaplectidae as the sister lineage to the rest of Blattoidea. We uncover an extraordinary level of genetic divergence in Nocticolidae, including two highly distinct clades that separated ~115 million years ago despite both containing representatives of the genus Nocticola. The results of our study highlight the potential impacts of high among-lineage rate variation on estimates of phylogenetic relationships and evolutionary timescales.

The molluskan order Neogastropoda encompasses over 15,000 almost exclusively marine species playing important roles in benthic communities and in the economies of coastal countries. Neogastropoda underwent intensive cladogenesis in the early stages of diversification, generating a "bush" at the base of their evolutionary tree, which has been hard to resolve even with high throughput molecular data. In the present study to resolve the bush, we use a variety of phylogenetic inference methods and a comprehensive exon capture dataset of 1817 loci (79.6% data occupancy) comprising 112 taxa of 48 out of 60 Neogastropoda families. Our results show consistent topologies and high support in all analyses at (super)family level, supporting monophyly of Muricoidea, Mitroidea, Conoidea, and, with some reservations, Olivoidea and Buccinoidea. Volutoidea and Turbinelloidea as currently circumscribed are clearly paraphyletic. Despite our analyses consistently resolving most backbone nodes, 3 prove problematic: First, the uncertain placement of Cancellariidae, as the sister group to either a Ficoidea-Tonnoidea clade or to the rest of Neogastropoda, leaves monophyly of Neogastropoda unresolved. Second, relationships are contradictory at the base of the major "core Neogastropoda" grouping. Third, coalescence-based analyses reject monophyly of the Buccinoidea in relation to Vasidae. We analyzed phylogenetic signal of targeted loci in relation to potential biases, and we propose the most probable resolutions in the latter 2 recalcitrant nodes. The uncertain placement of Cancellariidae may be explained by orthology violations due to differential paralog loss shortly after the whole genome duplication, which should be resolved with a curated set of longer loci.

Asymmetrical rates of cladogenesis and extinction abound in the tree of life, resulting in numerous minute clades that are dwarfed by larger sister groups. Such taxa are commonly regarded as phylogenetic relicts or "living fossils" when they exhibit an ancient first appearance in the fossil record and prolonged external morphological stasis, particularly in comparison to their more diversified sister groups. Due to their special status, various phylogenetic relicts tend to be well-studied and prioritized for conservation. A notable exception to this trend is found within Amblypygi ("whip spiders"), a visually striking order of functionally hexapodous arachnids that are notable for their antenniform first walking leg pair (the eponymous "whips"). Paleoamblypygi, the putative sister group to the remaining Amblypygi, is known from Late Carboniferous and Eocene deposits but is survived by a single living species, Paracharon caecusHansen (1921), that was last collected in 1899. Due to the absence of genomic sequence-grade tissue for this vital taxon, there is no global molecular phylogeny for Amblypygi to date, nor a fossil-calibrated estimation of divergences within the group. Here, we report a previously unknown species of Paleoamblypygi from a cave site in Colombia. Capitalizing upon this discovery, we generated the first molecular phylogeny of Amblypygi, integrating ultraconserved element sequencing with legacy Sanger datasets and including described extant genera. To quantify the impact of sampling Paleoamblypygi on divergence time estimation, we performed in silico experiments with pruning of Paracharon. We demonstrate that the omission of relicts has a significant impact on the accuracy of node dating approaches that outweighs the impact of excluding ingroup fossils, which bears upon the ancestral range reconstruction for the group. Our results underscore the imperative for biodiversity discovery efforts in elucidating the phylogenetic relationships of "dark taxa," and especially phylogenetic relicts in tropical and subtropical habitats. The lack of reciprocal monophyly for Charontidae and Charinidae leads us to subsume them into one family, Charontidae, new synonymy.

Phylogenetic and discrete-trait evolutionary inference depend heavily on an appropriate characterization of the underlying character substitution process. In this paper, we present random-effects substitution models that extend common continuous-time Markov chain models into a richer class of processes capable of capturing a wider variety of substitution dynamics. As these random-effects substitution models often require many more parameters than their usual counterparts, inference can be both statistically and computationally challenging. Thus, we also propose an efficient approach to compute an approximation to the gradient of the data likelihood with respect to all unknown substitution model parameters. We demonstrate that this approximate gradient enables scaling of sampling-based inference, namely Bayesian inference via Hamiltonian Monte Carlo, under random-effects substitution models across large trees and state-spaces. Applied to a dataset of 583 SARS-CoV-2 sequences, an HKY model with random-effects shows strong signals of nonreversibility in the substitution process, and posterior predictive model checks clearly show that it is a more adequate model than a reversible model. When analyzing the pattern of phylogeographic spread of 1441 influenza A virus (H3N2) sequences between 14 regions, a random-effects phylogeographic substitution model infers that air travel volume adequately predicts almost all dispersal rates. A random-effects state-dependent substitution model reveals no evidence for an effect of arboreality on the swimming mode in the tree frog subfamily Hylinae. Simulations reveal that random-effects substitution models can accommodate both negligible and radical departures from the underlying base substitution model. We show that our gradient-based inference approach is over an order of magnitude more time efficient than conventional approaches.

When communities are assembled through processes such as filtering or limiting similarity acting on phylogenetically conserved traits, the evolutionary signature of those traits may be reflected in patterns of community membership. We show how the model of trait evolution underlying community-structuring traits can be inferred from community membership data using both a variation of a traditional eco-phylogenetic metric-the mean pairwise phylogenetic distance (MPD) between taxa-and a recent machine learning tool, Convolutional Kitchen Sinks (CKS). Both methods perform well across a range of phylogenetically informative evolutionary models, but CKS outperforms MPD as tree size increases. We demonstrate CKS by inferring the evolutionary history of freeze tolerance in angiosperms. Our analysis is consistent with a late burst model, suggesting freeze tolerance evolved recently. We suggest that multiple data types that are ordered on phylogenies, such as trait values, species interactions, or community presence/absence, are good candidates for CKS modeling because the generative models produce structured differences between neighboring points that CKS is well-suited for. We introduce the R package kitchen to perform CKS for generic application of the technique.

Why and how organismal lineages radiate is commonly studied through either assessing abiotic factors (biogeography, geomorphological processes, and climate) or biotic factors (traits and interactions). Despite increasing awareness that both abiotic and biotic processes may have important joint effects on diversification dynamics, few attempts have been made to quantify the relative importance and timing of these factors, and their potentially interlinked direct and indirect effects, on lineage diversification. We here combine assessments of historical biogeography, geomorphology, climatic niche, vegetative, and floral trait evolution to test whether these factors jointly, or in isolation, explain diversification dynamics of a Neotropical plant clade (Merianieae, Melastomataceae). After estimating ancestral areas and the changes in niche and trait disparity over time, we employ Phylogenetic Path Analyses as a synthesis tool to test eleven hypotheses on the individual direct and indirect effects of these factors on diversification rates. We find strongest support for interlinked effects of colonization of the uplifting Andes during the mid-Miocene and rapid abiotic climatic niche evolution in explaining a burst in diversification rate in Merianieae. Within Andean habitats, later increases in floral disparity allowed for the exploitation of wider pollination niches (i.e., shifts from bee to vertebrate pollinators), but did not affect diversification rates. Our approach of including both vegetative and floral trait evolution, rare in assessments of plant diversification in general, highlights that the evolution of woody habit and larger flowers preceded the colonization of the Andes, but was likely critical in enabling the rapid radiation in montane environments. Overall, and in concert with the idea that ecological opportunity is a key element of evolutionary radiations, our results suggest that a combination of rapid niche evolution and trait shifts was critical for the exploitation of newly available niche space in the Andes in the mid-Miocene. Further, our results emphasize the importance of incorporating both abiotic and biotic factors into the same analytical framework if we aim to quantify the relative and interlinked effects of these processes on diversification.