Tree Inference Methods Research Articles

AleRax: a tool for gene and species tree co-estimation and reconciliation under a probabilistic model of gene duplication, transfer, and loss.

Genomes are a rich source of information on the pattern and process of evolution across biological scales. How best to make use of that information is an active area of research in phylogenetics. Ideally, phylogenetic methods should not only model substitutions along gene trees, which explain differences between homologous gene sequences, but also the processes that generate the gene trees themselves along a shared species tree. To conduct accurate inferences, one needs to account for uncertainty at both levels, that is, in gene trees estimated from inherently short sequences and in their diverse evolutionary histories along a shared species tree. We present AleRax, a software that can infer reconciled gene trees together with a shared species tree using a simple, yet powerful, probabilistic model of gene duplication, transfer, and loss. A key feature of AleRax is its ability to account for uncertainty in the gene tree and its reconciliation by using an efficient approximation to calculate the joint phylogenetic-reconciliation likelihood and sample reconciled gene trees accordingly. Simulations and analyses of empirical data show that AleRax is one order of magnitude faster than competing gene tree inference tools while attaining the same accuracy. It is consistently more robust than species tree inference methods such as SpeciesRax and ASTRAL-Pro 2 under gene tree uncertainty. Finally, AleRax can process multiple gene families in parallel thereby allowing users to compare competing phylogenetic hypotheses and estimate model parameters, such as duplication, transfer, and loss probabilities for genome-scale datasets with hundreds of taxa. GNU GPL at https://github.com/BenoitMorel/AleRax and data are made available at https://cme.h-its.org/exelixis/material/alerax_data.tar.gz.

Comparative Mitogenomic Analyses of Darkling Beetles (Coleoptera: Tenebrionidae) Provide Evolutionary Insights into tRNA-like Sequences.

Tenebrionidae is widely recognized owing to its species diversity and economic importance. Here, we determined the mitochondrial genomes (mitogenomes) of three Tenebrionidae species (Melanesthes exilidentata, Anatolica potanini, and Myladina unguiculina) and performed a comparative mitogenomic analysis to characterize the evolutionary characteristics of the family. The tenebrionid mitogenomes were highly conserved with respect to genome size, gene arrangement, base composition, and codon usage. All protein-coding genes evolved under purifying selection. The largest non-coding region (i.e., control region) showed several unusual features, including several conserved repetitive fragments (e.g., A+T-rich regions, G+C-rich regions, Poly-T tracts, TATA repeat units, and longer repetitive fragments) and tRNA-like structures. These tRNA-like structures can bind to the appropriate anticodon to form a cloverleaf structure, although base-pairing is not complete. We summarized the quantity, types, and conservation of tRNA-like sequences and performed functional and evolutionary analyses of tRNA-like sequences with various anticodons. Phylogenetic analyses based on three mitogenomic datasets and two tree inference methods largely supported the monophyly of each of the three subfamilies (Stenochiinae, Pimeliinae, and Lagriinae), whereas both Tenebrioninae and Diaperinae were consistently recovered as polyphyletic. We obtained a tenebrionid mitogenomic phylogeny: (Lagriinae, (Pimeliinae, ((Tenebrioninae + Diaperinae), Stenochiinae))). Our results provide insights into the evolution and function of tRNA-like sequences in tenebrionid mitogenomes and contribute to our general understanding of the evolution of Tenebrionidae.

Phylogenetic congruence, conflict and consilience between molecular and morphological data

Morphology and molecules are important data sources for estimating evolutionary relationships. Modern studies often utilise morphological and molecular partitions alongside each other in combined analyses. However, the effect of combining phenomic and genomic partitions is unclear. This is exacerbated by their size imbalance, and conflict over the efficacy of different inference methods when using morphological characters. To systematically address the effect of topological incongruence, size imbalance, and tree inference methods, we conduct a meta-analysis of 32 combined (molecular + morphology) datasets across metazoa. Our results reveal that morphological-molecular topological incongruence is pervasive: these data partitions yield very different trees, irrespective of which method is used for morphology inference. Analysis of the combined data often yields unique trees that are not sampled by either partition individually, even with the inclusion of relatively small quantities of morphological characters. Differences between morphology inference methods in terms of resolution and congruence largely relate to consensus methods. Furthermore, stepping stone Bayes factor analyses reveal that morphological and molecular partitions are not consistently combinable, i.e. data partitions are not always best explained under a single evolutionary process. In light of these results, we advise that the congruence between morphological and molecular data partitions needs to be considered in combined analyses. Nonetheless, our results reveal that, for most datasets, morphology and molecules can, and should, be combined in order to best estimate evolutionary history and reveal hidden support for novel relationships. Studies that analyse only phenomic or genomic data in isolation are unlikely to provide the full evolutionary picture.

First Report of Anthracnose Crown Rot on Strawberry (Fragaria × ananassa Duch.) Caused by Colletotrichum pandanicola in Yunnan Provence, China.

Strawberry (Fragaria × ananassa Duch.), a widely grown octoploid species, is one of the most important economic fruit crops and has been widely cultivated in the world, including China. In December 2021, a serious crown rot disease (approximately 50% incidence) was observed in strawberry (cultivar Miaoxiang) plantations in Qujing City, Yunnan Province, China. Symptoms observed on aboveground part withered rapidly, reddish-brown marbled necrosis on crown. The roots were healthy and strong, but the plants finally died. To isolate the causal agent of this disease, crown tissues from five strawberry plants showing typical symptoms were cut into pieces of 5×5 mm, and the pieces were surface-sterilized with 75% ethanol for 45 s followed by 2.5% NaClO for 3 min and rinsed thrice with sterile water, and then placed onto potato dextrose agar (PDA) for 7 days at 25 ºC. After 3 to 4 days, extended single hyphal tips from the tissues were transferred to PDA and incubated for 7 days at 25 ºC. The colonies were initially white, later became somewhat zonate, velvety, cyan gray on the upper side and cyan ink pigment ring on the reverse side of plates, with concentric rings of salmon sporodochia. Many yellowish or orange creamy conidial droplets formed on PDA after 14 days at 25 ºC. Fifty-nine isolates were obtained, and three isolates QLYRR1, QLMCR9, and QLMCR39 were selected for further experiments. Conidia were hyaline, cylindrical with rounded ends, 12.17-19.35×3.71-6.30 μm (average±SD, 15.24±1.37×5.09±0.45 μm, n=150), L/W ratio = 2.99. The three isolates were molecularly identified using the genomic regions of internal transcribed spacer (ITS), actin (ACT), chitin synthase (CHS-1), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), and beta-tubulin (TUB2) genes, and the sequences were deposited in GenBank (accession nos. QLYRR1, QLMCR9, QLMCR39: ON668272, ON668256, ON668257[ITS], ON684302, ON684300, ON684301[ACT], ON684316, ON684314, ON684315[CHS-1], ON684292, ON684290, ON684291[GAPDH], ON684286, ON684284, ON684285[TUB2]). The phylogenetic analysis of experimental strains was performed by Maximum-likelihood (ML) tree and Bayesian inference (BI) method. Nucleotide sequences exhibited three isolates were clustered with the ex-type strain C. pandanicola strain MFLUCC 170571T found in Thailand, C. pandanicola strains (SAUCC201152, SAUCC200204) found in Shandong Province, and the holotype stain C. parvisporum YMF 1.06942T found in Guangxi Province, China. Morphologically, isolates were easily distinguished from C. parvisporum by the colony on PDA and the size of conidia (Yu et al. 2022). Morphological characteristics and phylogenetic analyses revealed that QLYRR1, QLMCR9, and QLMCR39 belong to C. pandanicola, the members of the C. gloeosporioides species complex (Tibpromma et al. 2018; Mu et al. 2021). Koch's postulates were tested by strawberry plants (two cultivars, Akihime and Miaoxiang) in vivo, strawberry plants were tested for the three isolates by spraying 1×106 conidia/mL suspension on three seedlings. Three seedlings sprayed with sterile distilled water were served as control. All of the plants were transferred to a glasshouse with a 28/20 °C day/night temperature range and natural sunlight. After 6 weeks, QLYRR1-, QLMCR9-, and QLMCR39-sprayed seedlings were stunted and developed typical wilt symptoms similar to those observed in the field with the incidence for 3, 3, and 3 seedlings, respectively. The negative control remained asymptomatic. The fungi were reisolated again from lesions of diseased plants and leaves with 100% frequency, and morphological characteristics and tested gene sequences were identical to the original isolates in this note, thus fulfilling Koch's postulates. C. pandanicola was described from the healthy leaves of Pandanus sp. and the lesion fruits of Juglans regia. To our knowledge, this is the first report confirming C. pandanicola causes anthracnose crown rot on strawberries in China. C. pandanicola has the potential for causing serious losses to the strawberry industry, and research is needed on management strategies to minimize losses.

Evaluating impacts of syntenic block detection strategies on rearrangement phylogeny using Mycobacterium tuberculosis isolates.

The phylogenetic signal of structural variation informs a more comprehensive understanding of evolution. As (near-)complete genome assembly becomes more commonplace, the next methodological challenge for inferring genome rearrangement trees is the identification of syntenic blocks of orthologous sequences. In this article, we studied 94 reference quality genomes of primarily Mycobacterium tuberculosis (Mtb) isolates as a benchmark to evaluate these methods. The clonal nature of Mtb evolution, the manageable genome sizes, along with substantial levels of structural variation make this an ideal benchmarking dataset. We tested several methods for detecting homology and obtaining syntenic blocks and two methods for inferring phylogenies from them, then compared the resulting trees to the standard method's tree, inferred from nucleotide substitutions. We found that, not only the choice of methods, but also their parameters can impact results, and that the tree inference method had less impact than the block determination method. Interestingly, a rearrangement tree based on blocks from the Cactus whole-genome aligner was fully compatible with the highly supported branches of the substitution-based tree, enabling the combination of the two into a high-resolution supertree. Overall, our results indicate that accurate trees can be inferred using genome rearrangements, but the choice of the methods for inferring homology requires care. Analysis scripts and code written for this study are available at https://gitlab.com/LPCDRP/rearrangement-homology.pub and https://gitlab.com/LPCDRP/syntement. Supplementary data are available at Bioinformatics online.

Untying the Gordian knot of plastid phylogenomic conflict: A case from ferns.

Phylogenomic studies based on plastid genome have resolved recalcitrant relationships among various plants, yet the phylogeny of Dennstaedtiaceae at the level of family and genera remains unresolved due to conflicting plastid genes, limited molecular data and incomplete taxon sampling of previous studies. The present study generated 30 new plastid genomes of Dennstaedtiaceae (9 genera, 29 species), which were combined with 42 publicly available plastid genomes (including 24 families, 27 genera, 42 species) to explore the evolution of Dennstaedtiaceae. In order to minimize the impact of systematic errors on the resolution of phylogenetic inference, we applied six strategies to generate 30 datasets based on CDS, intergenic spacers, and whole plastome, and two tree inference methods (maximum-likelihood, ML; and multispecies coalescent, MSC) to comprehensively analyze the plastome-scale data. Besides, the phylogenetic signal among all loci was quantified for controversial nodes using ML framework, and different topologies hypotheses among all datasets were tested. The species trees based on different datasets and methods revealed obvious conflicts at the base of the polypody ferns. The topology of the "CDS-codon-align-rm3" (CDS with the removal of the third codon) matrix was selected as the primary reference or summary tree. The final phylogenetic tree supported Dennstaedtiaceae as the sister group to eupolypods, and Dennstaedtioideae was divided into four clades with full support. This robust reconstructed phylogenetic backbone establishes a framework for future studies on Dennstaedtiaceae classification, evolution and diversification. The present study suggests considering plastid phylogenomic conflict when using plastid genomes. From our results, reducing saturated genes or sites can effectively mitigate tree conflicts for distantly related taxa. Moreover, phylogenetic trees based on amino acid sequences can be used as a comparison to verify the confidence of nucleotide-based trees.

Phylogeny Reconciles Classification in Antarctic Plunderfishes

The resolution of phylogenetic relationships within rapid radiations poses a significant challenge in systematic biology. However, the integration of genome-scale DNA data with multispecies coalescent-based tree inference methods offers a strategy to resolve historically recalcitrant nodes within radiations of closely related species. Here, we analyze a dataset of over 60,000 loci captured via double digest restriction site-associated DNA sequencing (ddRADseq) using both concatenation- and coalescent-based approaches to infer the phylogenetic relationships of the Antarctic notothenioid lineage Artedidraconinae. Previous studies identify artedidraconines as the most rapidly diversifying subclade of notothenioids, but evolutionary studies of the clade are stymied by pervasive phylogenetic and taxonomic uncertainty. The results of our phylogenomic analyses provide clarity to several long-standing challenges in the systematics of artedidraconines, including the deep paraphyly of Artedidraco. Our findings enable the construction of a classification that reflects phylogenetic relationships, including the description of a new genus and the resurrection of a classification of Notothenioidei that places Artedidraconinae as a subfamily of Harpagiferidae. This work provides a phylogenetic perspective for investigations of the tempo and mode of diversification in artedidraconines, which is likely to provide new insights on the dynamics of the notothenioid adaptive radiation as a whole.

Weighting by Gene Tree Uncertainty Improves Accuracy of Quartet-based Species Trees.

Phylogenomic analyses routinely estimate species trees using methods that account for gene tree discordance. However, the most scalable species tree inference methods, which summarize independently inferred gene trees to obtain a species tree, are sensitive to hard-to-avoid errors introduced in the gene tree estimation step. This dilemma has created much debate on the merits of concatenation versus summary methods and practical obstacles to using summary methods more widely and to the exclusion of concatenation. The most successful attempt at making summary methods resilient to noisy gene trees has been contracting low support branches from the gene trees. Unfortunately, this approach requires arbitrary thresholds and poses new challenges. Here, we introduce threshold-free weighting schemes for the quartet-based species tree inference, the metric used in the popular method ASTRAL. By reducing the impact of quartets with low support or long terminal branches (or both), weighting provides stronger theoretical guarantees and better empirical performance than the unweighted ASTRAL. Our simulations show that weighting improves accuracy across many conditions and reduces the gap with concatenation in conditions with low gene tree discordance and high noise. On empirical data, weighting improves congruence with concatenation and increases support. Together, our results show that weighting, enabled by a new optimization algorithm we introduce, improves the utility of summary methods and can reduce the incongruence often observed across analytical pipelines.

Phylogenies in yeast species descriptions: In defense of neighbor-joining.

The neighbor-joining (NJ) method of tree inference is examined, with special attention to its use in yeast species descriptions. How the often-vilified method works is often misunderstood. More importantly, given the right kind of data, its output is a phylogram that illustrates a hypothetical phylogeny that is just as credible as that obtained by any other method. And as with any other method, the result is greatly affected by sampling intensity, particularly the number of aligned positions used for analysis. I address various allegations, including the claim that the method is phenetic, and, therefore, not phylogenetic. I argue that NJ is the most suitable tree inference method to use in yeast species descriptions, primarily because it is best at visually preserving the extent of sequence divergence between close relatives, which continues to be the primary criterion for yeast species delineation. The relevance of bootstraps in the application of the phylogenetic species concept is discussed.

Invariant transformers of Robinson and Foulds distance matrices for Convolutional Neural Network.

The evolutionary histories of genes are susceptible of differing greatly from each other which could be explained by evolutionary variations in horizontal gene transfers or biological recombinations. A phylogenetic tree would therefore represent the evolutionary history of each gene, which may present different patterns from the species tree that defines the main evolutionary patterns. In addition, phylogenetic trees of closely related species should be merged, thus minimizing the topological conflicts they present and obtaining consensus trees (in the case of homogeneous data) or supertrees (in the case of heterogeneous data). The traditional approaches are consensus tree inference (if the set of trees contains the same set of species) or supertrees (if the set of trees contains different, but overlapping sets of species). Consensus trees and supertrees are constructed to produce unique trees. However, these methods lose precision with respect to different evolutionary variability. Other approaches have been implemented to preserve this variability using the [Formula: see text]-means algorithm or the [Formula: see text]-medoids algorithm. Using a new method, we determine all possible consensus trees and supertrees that best represent the most significant evolutionary models in a set of phylogenetic trees, thereby increasing the precision of the results and decreasing the time required. Results: This paper presents in detail a new method for predicting the number of clusters in a Robinson and Foulds (RF) distance matrix using a convolutional neural network (CNN). We developed a new CNN approach (called CNNTrees) for multiple tree classification. This new strategy returns a number of clusters of the input phylogenetic trees for different-size sets of trees, which makes the new approach more stable and more robust. The paper provides an in-depth analysis of the relevant, but very difficult, problem of constructing alternative supertrees using phylogenies with different but overlapping sets of taxa. This new model will play an important role in the inference of Trees of Life (ToL). Availability and implementation: CNNTrees is available through a web server at https://tahirinadia.github.io/. The source code, data and information about installation procedures are also available at https://github.com/TahiriNadia/CNNTrees. Supplementary information: Supplementary data are available on GitHub platform. The evolutionary history of species is not unique, but is specific to sets of genes. Indeed, each gene has its own evolutionary history that differs considerably from one gene to another. For example, some individual genes or operons may be affected by specific horizontal gene transfer and recombination events. Thus, the evolutionary history of each gene must be represented by its own phylogenetic tree, which may exhibit different evolutionary patterns than the species tree that accounts for the major vertical descent patterns. The result of traditional consensus tree or supertree inference methods is a single consensus tree or supertree. In this paper, we present in detail a new method for predicting the number of clusters in a Robinson and Foulds (RF) distance matrix using a convolutional neural network (CNN). We developed a new CNN approach (CNNTrees) to construct multiple tree classification. This new strategy returns a number of clusters in the order of the input trees, which allows this new approach to be more stable and also more robust.

Using all Gene Families Vastly Expands Data Available for Phylogenomic Inference.

Traditionally, single-copy orthologs have been the gold standard in phylogenomics. Most phylogenomic studies identify putative single-copy orthologs using clustering approaches and retain families with a single sequence per species. This limits the amount of data available by excluding larger families. Recent advances have suggested several ways to include data from larger families. For instance, tree-based decomposition methods facilitate the extraction of orthologs from large families. Additionally, several methods for species tree inference are robust to the inclusion of paralogs and could use all of the data from larger families. Here, we explore the effects of using all families for phylogenetic inference by examining relationships among 26 primate species in detail and by analyzing five additional data sets. We compare single-copy families, orthologs extracted using tree-based decomposition approaches, and all families with all data. We explore several species tree inference methods, finding that identical trees are returned across nearly all subsets of the data and methods for primates. The relationships among Platyrrhini remain contentious; however, the species tree inference method matters more than the subset of data used. Using data from larger gene families drastically increases the number of genes available and leads to consistent estimates of branch lengths, nodal certainty and concordance, and inferences of introgression in primates. For the other data sets, topological inferences are consistent whether single-copy families or orthologs extracted using decomposition approaches are analyzed. Using larger gene families is a promising approach to include more data in phylogenomics without sacrificing accuracy, at least when high-quality genomes are available.

Building alternative consensus trees and supertrees using k-means and Robinson and Foulds distance.

Each gene has its own evolutionary history which can substantially differ from evolutionary histories of other genes. For example, some individual genes or operons can be affected by specific horizontal gene transfer or recombination events. Thus, the evolutionary history of each gene should be represented by its own phylogenetic tree which may display different evolutionary patterns from the species tree that accounts for the main patterns of vertical descent. However, the output of traditional consensus tree or supertree inference methods is a unique consensus tree or supertree. We present a new efficient method for inferring multiple alternative consensus trees and supertrees to best represent the most important evolutionary patterns of a given set of gene phylogenies. We show how an adapted version of the popular k-means clustering algorithm, based on some remarkable properties of the Robinson and Foulds distance, can be used to partition a given set of trees into one (for homogeneous data) or multiple (for heterogeneous data) cluster(s) of trees. Moreover, we adapt the popular Caliński-Harabasz, Silhouette, Ball and Hall, and Gap cluster validity indices to tree clustering with k-means. Special attention is given to the relevant but very challenging problem of inferring alternative supertrees. The use of the Euclidean property of the objective function of the method makes it faster than the existing tree clustering techniques, and thus better suited for analyzing large evolutionary datasets. Our KMeansSuperTreeClustering program along with its C++ source code is available at: https://github.com/TahiriNadia/KMeansSuperTreeClustering. Supplementary data are available at Bioinformatics online.

Towards the plastome evolution and phylogeny of Cycas L. (Cycadaceae): molecular-morphology discordance and gene tree space analysis

BackgroundPlastid genomes (plastomes) present great potential in resolving multiscale phylogenetic relationship but few studies have focused on the influence of genetic characteristics of plastid genes, such as genetic variation and phylogenetic discordance, in resolving the phylogeny within a lineage. Here we examine plastome characteristics of Cycas L., the most diverse genus among extant cycads, and investigate the deep phylogenetic relationships within Cycas by sampling 47 plastomes representing all major clades from six sections.ResultsAll Cycas plastomes shared consistent gene content and structure with only one gene loss detected in Philippine species C. wadei. Three novel plastome regions (psbA-matK, trnN-ndhF, chlL-trnN) were identified as containing the highest nucleotide variability. Molecular evolutionary analysis showed most of the plastid protein-coding genes have been under purifying selection except ndhB. Phylogenomic analyses that alternatively included concatenated and coalescent methods, both identified four clades but with conflicting topologies at shallow nodes. Specifically, we found three species-rich Cycas sections, namely Stangerioides, Indosinenses and Cycas, were not or only weakly supported as monophyly based on plastomic phylogeny. Tree space analyses based on different tree-inference methods both revealed three gene clusters, of which the cluster with moderate genetic properties showed the best congruence with the favored phylogeny.ConclusionsOur exploration in plastomic data for Cycas supports the idea that plastid protein-coding genes may exhibit discordance in phylogenetic signals. The incongruence between molecular phylogeny and morphological classification reported here may largely be attributed to the uniparental attribute of plastid, which cannot offer sufficient information to resolve the phylogeny. Contrasting to a previous consensus that genes with longer sequences and a higher proportion of variances are superior for phylogeny reconstruction, our result implies that the most effective phylogenetic signals could come from loci that own moderate variation, GC content, sequence length, and underwent modest selection.

Species Tree Inference Methods Intended to Deal with Incomplete Lineage Sorting Are Robust to the Presence of Paralogs.

Many recent phylogenetic methods have focused on accurately inferring species trees when there is gene tree discordance due to incomplete lineage sorting (ILS). For almost all of these methods, and for phylogenetic methods in general, the data for each locus are assumed to consist of orthologous, single-copy sequences. Loci that are present in more than a single copy in any of the studied genomes are excluded from the data. These steps greatly reduce the number of loci available for analysis. The question we seek to answer in this study is: what happens if one runs such species tree inference methods on data where paralogy is present, in addition to or without ILS being present? Through simulation studies and analyses of two large biological data sets, we show that running such methods on data with paralogs can still provide accurate results. We use multiple different methods, some of which are based directly on the multispecies coalescent model, and some of which have been proven to be statistically consistent under it. We also treat the paralogous loci in multiple ways: from explicitly denoting them as paralogs, to randomly selecting one copy per species. In all cases, the inferred species trees are as accurate as equivalent analyses using single-copy orthologs. Our results have significant implications for the use of ILS-aware phylogenomic analyses, demonstrating that they do not have to be restricted to single-copy loci. This will greatly increase the amount of data that can be used for phylogenetic inference.[Gene duplication and loss; incomplete lineage sorting; multispecies coalescent; orthology; paralogy.]

Quartet-based inference is statistically consistent under the unified duplication-loss-coalescence model.

MotivationThe classic multispecies coalescent (MSC) model provides the means for theoretical justification of incomplete lineage sorting-aware species tree inference methods. This has motivated an extensive body of work on phylogenetic methods that are statistically consistent under MSC. One such particularly popular method is ASTRAL, a quartet-based species tree inference method. Novel studies suggest that ASTRAL also performs well when given multi-locus gene trees in simulation studies. Further, Legried et al. recently demonstrated that ASTRAL is statistically consistent under the gene duplication and loss model (GDL). GDL is prevalent in evolutionary histories and is the first core process in the powerful duplication-loss-coalescence evolutionary model (DLCoal) by Rasmussen and Kellis.ResultsIn this work, we prove that ASTRAL is statistically consistent under the general DLCoal model. Therefore, our result supports the empirical evidence from the simulation-based studies. More broadly, we prove that the quartet-based inference approach is statistically consistent under DLCoal.Supplementary information Supplementary data are available at Bioinformatics online.

Gene Tree Estimation Error with Ultraconserved Elements: An Empirical Study on Pseudapis Bees.

Summarizing individual gene trees to species phylogenies using two-step coalescent methods is now a standard strategy in the field of phylogenomics. However, practical implementations of summary methods suffer from gene tree estimation error, which is caused by various biological and analytical factors. Greatly understudied is the choice of gene tree inference method and downstream effects on species tree estimation for empirical data sets. To better understand the impact of this method choice on gene and species tree accuracy, we compare gene trees estimated through four widely used programs under different model-selection criteria: PhyloBayes, MrBayes, IQ-Tree, and RAxML. We study their performance in the phylogenomic framework of $>$800 ultraconserved elements from the bee subfamily Nomiinae (Halictidae). Our taxon sampling focuses on the genus Pseudapis, a distinct lineage with diverse morphological features, but contentious morphology-based taxonomic classifications and no molecular phylogenetic guidance. We approximate topological accuracy of gene trees by assessing their ability to recover two uncontroversial, monophyletic groups, and compare branch lengths of individual trees using the stemminess metric (the relative length of internal branches). We further examine different strategies of removing uninformative loci and the collapsing of weakly supported nodes into polytomies. We then summarize gene trees with ASTRAL and compare resulting species phylogenies, including comparisons to concatenation-based estimates. Gene trees obtained with the reversible jump model search in MrBayes were most concordant on average and all Bayesian methods yielded gene trees with better stemminess values. The only gene tree estimation approach whose ASTRAL summary trees consistently produced the most likely correct topology, however, was IQ-Tree with automated model designation (ModelFinder program). We discuss these findings and provide practical advice on gene tree estimation for summary methods. Lastly, we establish the first phylogeny-informed classification for Pseudapis s. l. and map the distribution of distinct morphological features of the group. [ASTRAL; Bees; concordance; gene tree estimation error; IQ-Tree; MrBayes, Nomiinae; PhyloBayes; RAxML; phylogenomics; stemminess].

Topological Metrizations of Trees, and New Quartet Methods of Tree Inference.

Topological phylogenetic trees can be assigned edge weights in several natural ways, highlighting different aspects of the tree. Here, the rooted triple and quartet metrizations are introduced, and applied to formulate novel methods of inferring large trees from rooted triple and quartet data. These methods lead to new statistically consistent procedures for inference of a species tree from gene trees under the multispecies coalescent model.

Converging on the orb: denser taxon sampling elucidates spider phylogeny and new analytical methods support repeated evolution of the orb web.

High throughput sequencing and phylogenomic analyses focusing on relationships among spiders have both reinforced and upturned long-standing hypotheses. Likewise, the evolution of spider webs-perhaps their most emblematic attribute-is being understood in new ways. With a matrix including 272 spider species and close arachnid relatives, we analyze and evaluate the relationships among these lineages using a variety of orthology assessment methods, occupancy thresholds, tree inference methods and support metrics. Our analyses include families not previously sampled in transcriptomic analyses, such as Symphytognathidae, the only araneoid family absent in such prior works. We find support for the major established spider lineages, including Mygalomorphae, Araneomorphae, Synspermiata, Palpimanoidea, Araneoidea and the Retrolateral Tibial Apophysis Clade, as well as the uloborids, deinopids, oecobiids and hersiliids Grade. Resulting trees are evaluated using bootstrapping, Shimodaira-Hasegawa approximate likelihood ratio test, local posterior probabilities and concordance factors. Using structured Markov models to assess the evolution of spider webs while accounting for hierarchically nested traits, we find multiple convergent occurrences of the orb web across the spider tree-of-life. Overall, we provide the most comprehensive spider tree-of-life to date using transcriptomic data and use new methods to explore controversial issues of web evolution, including the origins and multiple losses of the orb web.

Larger, unfiltered datasets are more effective at resolving phylogenetic conflict: Introns, exons, and UCEs resolve ambiguities in Golden-backed frogs (Anura: Ranidae; genus Hylarana)

Using FrogCap, a recently-developed sequence-capture protocol, we obtained >12,000 highly informative exons, introns, and ultraconserved elements (UCEs), which we used to illustrate variation in evolutionary histories of these classes of markers, and to resolve long-standing systematic problems in Southeast Asian Golden-backed frogs of the genus-complex Hylarana. We also performed a comprehensive suite of analyses to assess the relative performance of different genetic markers, data filtering strategies, tree inference methods, and different measures of branch support. To reduce gene tree estimation error, we filtered the data using different thresholds of taxon completeness (missing data) and parsimony informative sites (PIS). We then estimated species trees using concatenated datasets and Maximum Likelihood (IQ-TREE) in addition to summary (ASTRAL-III), distance-based (ASTRID), and site-based (SVDQuartets) multispecies coalescent methods. Topological congruence and branch support were examined using traditional bootstrap, local posterior probabilities, gene concordance factors, quartet frequencies, and quartet scores. Our results did not yield a single concordant topology. Instead, introns, exons, and UCEs clearly possessed different phylogenetic signals, resulting in conflicting, yet strongly-supported phylogenetic estimates. However, a combined analysis comprising the most informative introns, exons, and UCEs converged on a similar topology across all analyses, with the exception of SVDQuartets. Bootstrap values were consistently high despite high levels of incongruence and high proportions of gene trees supporting conflicting topologies. Although low bootstrap values did indicate low heuristic support, high bootstrap support did not necessarily reflect congruence or support for the correct topology. This study reiterates findings of some previous studies, which demonstrated that traditional bootstrap values can produce positively misleading measures of support in large phylogenomic datasets. We also showed a remarkably strong positive relationship between branch length and topological congruence across all datasets, implying that very short internodes remain a challenge to resolve, even with orders of magnitude more data than ever before. Overall, our results demonstrate that more data from unfiltered or combined datasets produced superior results. Although data filtering reduced gene tree incongruence, decreased amounts of data also biased phylogenetic estimation. A point of diminishing returns was evident, at which higher congruence (from more stringent filtering) at the expense of amount of data led to topological error as assessed by comparison to more complete datasets across different genomic markers. Additionally, we showed that applying a parameter-rich model to a partitioned analysis of concatenated data produces better results compared to unpartitioned, or even partitioned analysis using model selection. Despite some lingering uncertainties, a combined analysis of our genomic data and sequences supplemented from GenBank (on the basis of a few gene regions) revealed highly supported novel systematic arrangements. Based on these new findings, we transfer Amnirana nicobariensis into the genus Indosylvirana; and I. milleti and Hylarana celebensis to the genus Papurana. We also provisionally place H. attigua in the genus Papurana pending verification from positively identified (voucher substantiated) samples.

Phylogenomics unravels Quaternary vicariance and allopatric speciation patterns in temperate-montane plant species: A case study on the Ranunculus auricomus species complex.

The time frame and geographical patterns of diversification processes in European temperate-montane herbs are still not well understood. We used the sexual species of the Ranunculus auricomus complex as a model system to understand how vicariance versus dispersal processes in the context of Pleistocene climatic fluctuations have triggered speciation in temperate-montane plant species. We used target enrichment sequence data from about 600 nuclear genes and coalescent-based species tree inference methods to resolve phylogenetic relationships among the sexual taxa of the complex. We estimated absolute divergence times and, using ancestral range reconstruction, we tested if speciation was enhanced by vicariance or by dispersal processes. Phylogenetic relationships among taxa were fully resolved with some incongruence in the position of the tetraploid R.marsicus. Speciation events took place in a very short time at the end of the Mid-Pleistocene Transition (830-580 thousand years ago [ka]). A second wave of intraspecific geographical differentiation occurred at the end of the Riss glaciation or during the Eemian interglacial between 200 and 100ka. Ancestral range reconstruction suggests a widespread European ancestor of the R.auricomus complex. Vicariance has triggered allopatric speciation in temperate-montane plant species during the climatic deterioration that occurred during the last phase of the Mid-Pleistocene Transition. Vegetation restructuring from forest into tundra could have confined these forest species into isolated glacial macro- and microrefugia. During subsequent warming periods, range expansions of these species could have been hampered by apomictic derivatives and by other congeneric competitors in the same habitat.