Rapid and accurate species tree estimation for phylogeographic investigations using replicated subsampling

Phylogenomic species delimitation in microendemic frogs of the Brazilian Atlantic Forest

The advent of next-generation sequencing allows researchers to use large-scale datasets for species delimitation analyses, yet one can envision an inflection point where the added accuracy of including more loci does not offset the increased computational burden. One alternative to including all loci could be to prioritize the analysis of loci for which there is an expectation of high informativeness. Here, we explore the issue of species delimitation and locus selection with montane species from two anuran genera that have been isolated in sky islands across the southern Brazilian Atlantic Forest: Melanophryniscus (Bufonidae) and Brachycephalus (Brachycephalidae). To delimit species, we obtained genetic data using target enrichment of ultraconserved elements from 32 populations (13 for Melanophryniscus and 19 for Brachycephalus), and we were able to create datasets that included over 800 loci with no missing data. We ranked loci according to their number of parsimony-informative sites, and we performed species delimitation analyses using BPP with the most informative 10, 20, 40, 80, 160, 320, and 640 loci. We identified three types of phylogenetic node: nodes with either consistently high or low support regardless of the number of loci or their informativeness and nodes that were initially poorly supported where support became stronger as we included more data. When viewed across all sensitivity analyses, our results suggest that the current species richness in both genera is likely underestimated. In addition, our results show the effects of different sampling strategies on species delimitation using phylogenomic datasets.

Inferring processes of coevolutionary diversification in a community of Panamanian strangler figs and associated pollinating wasps

The fig and pollinator wasp obligate mutualism is diverse (∼750 described species), ecologically important, and ancient (∼80 Ma). Once thought to be an example of strict one-to-one cospeciation, current thinking suggests genera of pollinator wasps codiversify with corresponding sections of figs, but the degree to which cospeciation or other processes contribute to the association at finer scales is unclear. Here, we use genome-wide sequence data from a community of Panamanian strangler figs and associated wasp pollinators to estimate the relative contributions of four evolutionary processes generating cophylogenetic patterns in this mutualism: cospeciation, host switching, pollinator speciation, and pollinator extinction. Using a model-based approach adapted from the study of gene family evolution, our results demonstrate the importance of host switching of pollinator wasps at this fine phylogenetic and regional scale. Although we estimate a modest amount of cospeciation, simulations reveal the number of putative cospeciation events to be consistent with what would be expected by chance. Additionally, model selection tests identify host switching as a critical parameter for explaining cophylogenetic patterns in this system. Our study demonstrates a promising approach through which the history of evolutionary association between interacting lineages can be rigorously modeled and tested in a probabilistic phylogenetic framework.

The influence of locus number and information content on species delimitation: an empirical test case in an endangered Mexican salamander

Perhaps the most important recent advance in species delimitation has been the development of model-based approaches to objectively diagnose species diversity from genetic data. Additionally, the growing accessibility of next-generation sequence data sets provides powerful insights into genome-wide patterns of divergence during speciation. However, applying complex models to large data sets is time-consuming and computationally costly, requiring careful consideration of the influence of both individual and population sampling, as well as the number and informativeness of loci on species delimitation conclusions. Here, we investigated how locus number and information content affect species delimitation results for an endangered Mexican salamander species, Ambystoma ordinarium. We compared results for an eight-locus, 137-individual data set and an 89-locus, seven-individual data set. For both data sets, we used species discovery methods to define delimitation models and species validation methods to rigorously test these hypotheses. We also used integrated demographic model selection tools to choose among delimitation models, while accounting for gene flow. Our results indicate that while cryptic lineages may be delimited with relatively few loci, sampling larger numbers of loci may be required to ensure that enough informative loci are available to accurately identify and validate shallow-scale divergences. These analyses highlight the importance of striking a balance between dense sampling of loci and individuals, particularly in shallowly diverged lineages. They also suggest the presence of a currently unrecognized, endangered species in the western part of A. ordinarium's range.

An empirical evaluation of two-stage species tree inference strategies using a multilocus dataset from North American pines

Background

As it becomes increasingly possible to obtain DNA sequences of orthologous genes from diverse sets of taxa, species trees are frequently being inferred from multilocus data. However, the behavior of many methods for performing this inference has remained largely unexplored. Some methods have been proven to be consistent given certain evolutionary models, whereas others rely on criteria that, although appropriate for many parameter values, have peculiar zones of the parameter space in which they fail to converge on the correct estimate as data sets increase in size.

Results

Here, using North American pines, we empirically evaluate the behavior of 24 strategies for species tree inference using three alternative outgroups (72 strategies total). The data consist of 120 individuals sampled in eight ingroup species from subsection Strobus and three outgroup species from subsection Gerardianae, spanning ∼47 kilobases of sequence at 121 loci. Each “strategy” for inferring species trees consists of three features: a species tree construction method, a gene tree inference method, and a choice of outgroup. We use multivariate analysis techniques such as principal components analysis and hierarchical clustering to identify tree characteristics that are robustly observed across strategies, as well as to identify groups of strategies that produce trees with similar features. We find that strategies that construct species trees using only topological information cluster together and that strategies that use additional non-topological information (e.g., branch lengths) also cluster together. Strategies that utilize more than one individual within a species to infer gene trees tend to produce estimates of species trees that contain clades present in trees estimated by other strategies. Strategies that use the minimize-deep-coalescences criterion to construct species trees tend to produce species tree estimates that contain clades that are not present in trees estimated by the Concatenation, RTC, SMRT, STAR, and STEAC methods, and that in general are more balanced than those inferred by these other strategies.

Conclusions

When constructing a species tree from a multilocus set of sequences, our observations provide a basis for interpreting differences in species tree estimates obtained via different approaches that have a two-stage structure in common, one step for gene tree estimation and a second step for species tree estimation. The methods explored here employ a number of distinct features of the data, and our analysis suggests that recovery of the same results from multiple methods that tend to differ in their patterns of inference can be a valuable tool for obtaining reliable estimates.

Discordance of species trees with their most likely gene trees: a unifying principle

A labeled gene tree topology that disagrees with a labeled species tree topology is said to be anomalous if it is more probable under a coalescent model for gene lineage evolution than the labeled gene tree topology that matches the species tree. It has previously been shown that as a consequence of short internal branches of the species tree, for every labeled species tree topology with five or more taxa, and for asymmetric four-taxon species tree topologies, an assignment of species tree branch lengths can be made which gives rise to anomalous gene trees (AGTs). Here, I offer an alternative characterization of this result—a labeled species tree topology produces AGTs if and only if it contains two consecutive internal branches in an ancestor–descendant relationship—and I provide a proof that follows from the change in perspective. The reformulation and alternative proof of the existence result for AGTs provide the insight that it is not merely short internal branches that generate AGTs, but instead, short internal branches that are arranged consecutively.

Robustness to divergence time underestimation when inferring species trees from estimated gene trees

To infer species trees from gene trees estimated from phylogenomic data sets, tractable methods are needed that can handle dozens to hundreds of loci. We examine several computationally efficient approaches-MP-EST, STAR, STEAC, STELLS, and STEM-for inferring species trees from gene trees estimated using maximum likelihood (ML) and Bayesian approaches. Among the methods examined, we found that topology-based methods often performed better using ML gene trees and methods employing coalescent times typically performed better using Bayesian gene trees, with MP-EST, STAR, STEAC, and STELLS outperforming STEM under most conditions. We examine why the STEM tree (also called GLASS or Maximum Tree) is less accurate on estimated gene trees by comparing estimated and true coalescence times, performing species tree inference using simulations, and analyzing a great ape data set keeping track of false positive and false negative rates for inferred clades. We find that although true coalescence times are more ancient than speciation times under the multispecies coalescent model, estimated coalescence times are often more recent than speciation times. This underestimation can lead to increased bias and lack of resolution with increased sampling (either alleles or loci) when gene trees are estimated with ML. The problem appears to be less severe using Bayesian gene-tree estimates.

Concatenation and concordance in the reconstruction of mouse lemur phylogeny: an empirical demonstration of the effect of allele sampling in phylogenetics

The systematics and speciation literature is rich with discussion relating to the potential for gene tree/species tree discordance. Numerous mechanisms have been proposed to generate discordance, including differential selection, long-branch attraction, gene duplication, genetic introgression, and/or incomplete lineage sorting. For speciose clades in which divergence has occurred recently and rapidly, recovering the true species tree can be particularly problematic due to incomplete lineage sorting. Unfortunately, the availability of multilocus or "phylogenomic" data sets does not simply solve the problem, particularly when the data are analyzed with standard concatenation techniques. In our study, we conduct a phylogenetic study for a nearly complete species sample of the dwarf and mouse lemur clade, Cheirogaleidae. Mouse lemurs (genus, Microcebus) have been intensively studied over the past decade for reasons relating to their high level of cryptic species diversity, and although there has been emerging consensus regarding the evolutionary diversity contained within the genus, there is no agreement as to the inter-specific relationships within the group. We attempt to resolve cheirogaleid phylogeny, focusing especially on the mouse lemurs, by employing a large multilocus data set. We compare the results of Bayesian concordance methods with those of standard gene concatenation, finding that though concatenation yields the strongest results as measured by statistical support, these results are found to be highly misleading. By employing an approach where individual alleles are treated as operational taxonomic units, we show that phylogenetic results are substantially influenced by the selection of alleles in the concatenation process.

Multilocus phylogeny and species delimitation within the Natterer's bat species complex in the Western Palearctic

Delimiting species is a crucial issue for many biological disciplines and is of primary importance for designing effective conservation plans. Traditional taxonomy based on morphological characters can be misled by the presence of phenotypic plesiomorphism or adaptative convergence. The use of multiple locus genetic data appears thus as a powerful tool for recognizing species boundaries. In this study, we used six nuclear introns and two mitochondrial markers to conduct a phylogenetic study of the Myotis nattereri species complex in the Western Palearctic. We combined tree-based and non-tree-based analyses, and also used concatenated phylogenetic methods of the separated nuclear and mitochondrial dataset as well as a recent coalescence-based multilocus approach. The strong concordance between the results of the analyses conducted confirms that M. nattereri is a paraphyletic group that is composed of four well-differentiated lineages in the study area. In the framework of the unified species concept, these four clades can be confidently considered as four valid species. This recognition of new cryptic species in the Western Mediterranean region shows that the biodiversity of this well-studied area is still not fully understood.

Estimating species trees using approximate Bayesian computation

Development of methods for estimating species trees from multilocus data is a current challenge in evolutionary biology. We propose a method for estimating the species tree topology and branch lengths using approximate Bayesian computation (ABC). The method takes as data a sample of observed rooted gene tree topologies, and then iterates through the following sequence of steps: First, a randomly selected species tree is used to compute the distribution of rooted gene tree topologies. This distribution is then compared to the observed gene topology frequencies, and if the fit between the observed and the predicted distributions is close enough, the proposed species tree is retained. Repeating this many times leads to a collection of retained species trees that are then used to form the estimate of the overall species tree. We test the performance of the method, which we call ST-ABC, using both simulated and empirical data. The simulation study examines both symmetric and asymmetric species trees over a range of branch lengths and sample sizes. The results from the simulation study show that the model performs very well, giving accurate estimates for both the topology and the branch lengths across the conditions studied, and that a sample size of 25 loci appears to be adequate for the method. Further, we apply the method to two empirical cases: a 4-taxon data set for primates and a 7-taxon data set for yeast. In both cases, we find that estimates obtained with ST-ABC agree with previous studies. The method provides efficient estimation of the species tree, and does not require sequence data, but rather the observed distribution of rooted gene topologies without branch lengths. Therefore, this method is a useful alternative to other currently available methods for species tree estimation.