scholarly journals TREEasy: an automated workflow to infer gene trees, species trees, and phylogenetic networks from multilocus data

2019 ◽  
Author(s):  
Yafei Mao ◽  
Siqing Hou ◽  
Evan P. Economo
Keyword(s):  
Tree Species ◽  
Network Inference ◽  
Gene Tree ◽  
Phylogenetic Network ◽  
Handling Time ◽  
Phylogenetic Networks ◽  
Recent Analysis ◽  
Gene Trees ◽  
Species Trees ◽  
Tree Inference

AbstractMultilocus genomic datasets can be used to infer a rich set of information about the evolutionary history of a lineage, including gene trees, species trees, and phylogenetic networks. However, user-friendly tools to run such integrated analyses are lacking, and workflows often require tedious reformatting and handling time to shepherd data through a series of individual programs. Here, we present a tool written in Python—TREEasy—that performs automated sequence alignment (with MAFFT), gene tree inference (with IQ-Tree), species inference from concatenated data (with IQ-Tree), species tree inference from gene trees (with ASTRAL, MP-EST, and STELLS2), and phylogenetic network inference (with SNaQ and PhyloNet). The tool only requires FASTA files and nine parameters as inputs. The Tool can be run as command line or through a Graphical User Interface (GUI). As examples, we reproduced a recent analysis of staghorn coral evolution, and performed a new analysis on the evolution of the WGD clade of yeast. The latter revealed novel inferences that were not identified by previous analyses. TREEasy represents a reliable and simple tool to accelerate research in systematic biology (https://github.com/MaoYafei/TREEasy).

scholarly journals Disentangling Sources of Gene Tree Discordance in Phylogenomic Data Sets: Testing Ancient Hybridizations in Amaranthaceae s.l

2020 ◽  
Author(s):  
Diego F Morales-Briones ◽  
Gudrun Kadereit ◽  
Delphine T Tefarikis ◽  
Michael J Moore ◽  
Stephen A Smith ◽  
...  
Keyword(s):  
Network Inference ◽  
Incomplete Lineage Sorting ◽  
Gene Tree ◽  
Phylogenetic Network ◽  
Species Tree ◽  
Data Sets ◽  
Species Trees ◽  
Lineage Sorting ◽  
Data Set ◽  
Gene Tree Discordance

Abstract Gene tree discordance in large genomic data sets can be caused by evolutionary processes such as incomplete lineage sorting and hybridization, as well as model violation, and errors in data processing, orthology inference, and gene tree estimation. Species tree methods that identify and accommodate all sources of conflict are not available, but a combination of multiple approaches can help tease apart alternative sources of conflict. Here, using a phylotranscriptomic analysis in combination with reference genomes, we test a hypothesis of ancient hybridization events within the plant family Amaranthaceae s.l. that was previously supported by morphological, ecological, and Sanger-based molecular data. The data set included seven genomes and 88 transcriptomes, 17 generated for this study. We examined gene-tree discordance using coalescent-based species trees and network inference, gene tree discordance analyses, site pattern tests of introgression, topology tests, synteny analyses, and simulations. We found that a combination of processes might have generated the high levels of gene tree discordance in the backbone of Amaranthaceae s.l. Furthermore, we found evidence that three consecutive short internal branches produce anomalous trees contributing to the discordance. Overall, our results suggest that Amaranthaceae s.l. might be a product of an ancient and rapid lineage diversification, and remains, and probably will remain, unresolved. This work highlights the potential problems of identifiability associated with the sources of gene tree discordance including, in particular, phylogenetic network methods. Our results also demonstrate the importance of thoroughly testing for multiple sources of conflict in phylogenomic analyses, especially in the context of ancient, rapid radiations. We provide several recommendations for exploring conflicting signals in such situations. [Amaranthaceae; gene tree discordance; hybridization; incomplete lineage sorting; phylogenomics; species network; species tree; transcriptomics.]

scholarly journals Disentangling Sources of Gene Tree Discordance in Phylogenomic Datasets: Testing Ancient Hybridizations in Amaranthaceae s.l

2019 ◽  
Author(s):  
Diego F. Morales-Briones ◽  
Gudrun Kadereit ◽  
Delphine T. Tefarikis ◽  
Michael J. Moore ◽  
Stephen A. Smith ◽  
...  
Keyword(s):  
Network Inference ◽  
Incomplete Lineage Sorting ◽  
Gene Tree ◽  
Phylogenetic Network ◽  
Molecular Data ◽  
Species Trees ◽  
Lineage Sorting ◽  
Multiple Sources ◽  
Gene Tree Discordance ◽  
Phylogenomic Analyses

AbstractGene tree discordance in large genomic datasets can be caused by evolutionary processes such as incomplete lineage sorting and hybridization, as well as model violation, and errors in data processing, orthology inference, and gene tree estimation. Species tree methods that identify and accommodate all sources of conflict are not available, but a combination of multiple approaches can help tease apart alternative sources of conflict. Here, using a phylotranscriptomic analysis in combination with reference genomes, we test a hypothesis of ancient hybridization events within the plant family Amaranthaceae s.l. that was previously supported by morphological, ecological, and Sanger-based molecular data. The dataset included seven genomes and 88 transcriptomes, 17 generated for this study. We examined gene-tree discordance using coalescent-based species trees and network inference, gene tree discordance analyses, site pattern tests of introgression, topology tests, synteny analyses, and simulations. We found that a combination of processes might have generated the high levels of gene tree discordance in the backbone of Amaranthaceae s.l. Furthermore, we found evidence that three consecutive short internal branches produce anomalous trees contributing to the discordance. Overall, our results suggest that Amaranthaceae s.l. might be a product of an ancient and rapid lineage diversification, and remains, and probably will remain, unresolved. This work highlights the potential problems of identifiability associated with the sources of gene tree discordance including, in particular, phylogenetic network methods. Our results also demonstrate the importance of thoroughly testing for multiple sources of conflict in phylogenomic analyses, especially in the context of ancient, rapid radiations. We provide several recommendations for exploring conflicting signals in such situations.

scholarly journals Maximum Parsimony Inference of Phylogenetic Networks in the Presence of Polyploid Complexes

2020 ◽  
Author(s):  
Zhi Yan ◽  
Zhen Cao ◽  
Yushu Liu ◽  
Luay Nakhleh
Keyword(s):  
Network Inference ◽  
Incomplete Lineage Sorting ◽  
Phylogenetic Network ◽  
Biological Data ◽  
Phylogenetic Networks ◽  
Data Sets ◽  
Gene Trees ◽  
Polyploid Species ◽  
Lineage Sorting ◽  
Work Done

AbstractPhylogenetic networks provide a powerful framework for modeling and analyzing reticulate evolutionary histories. While polyploidy has been shown to be prevalent not only in plants but also in other groups of eukaryotic species, most work done thus far on phylogenetic network inference assumes diploid hybridization. These inference methods have been applied, with varying degrees of success, to data sets with polyploid species, even though polyploidy violates the mathematical assumptions underlying these methods. Statistical methods were developed recently for handling specific types of polyploids and so were parsimony methods that could handle polyploidy more generally yet while excluding processes such as incomplete lineage sorting. In this paper, we introduce a new method for inferring most parsimonious phylogenetic networks on data that include polyploid species. Taking gene trees as input, the method seeks a phylogenetic network that minimizes deep coalescences while accounting for polyploidy. The method could also infer trees, thus potentially distinguishing between auto- and allo-polyploidy. We demonstrate the performance of the method on both simulated and biological data. The inference method as well as a method for evaluating given phylogenetic networks are implemented and publicly available in the PhyloNet software package.

scholarly journals Maximum Parsimony Inference of Phylogenetic Networks in the Presence of Polyploid Complexes

2021 ◽  
Author(s):  
Zhi Yan ◽  
Zhen Cao ◽  
Yushu Liu ◽  
Huw A Ogilvie ◽  
Luay Nakhleh
Keyword(s):  
Network Inference ◽  
Incomplete Lineage Sorting ◽  
Gene Tree ◽  
Phylogenetic Network ◽  
Biological Data ◽  
Phylogenetic Networks ◽  
Data Sets ◽  
Polyploid Species ◽  
Lineage Sorting ◽  
Work Done

Abstract Phylogenetic networks provide a powerful framework for modeling and analyzing reticulate evolutionary histories. While polyploidy has been shown to be prevalent not only in plants but also in other groups of eukaryotic species, most work done thus far on phylogenetic network inference assumes diploid hybridization. These inference methods have been applied, with varying degrees of success, to data sets with polyploid species, even though polyploidy violates the mathematical assumptions underlying these methods. Statistical methods were developed recently for handling specific types of polyploids and so were parsimony methods that could handle polyploidy more generally yet while excluding processes such as incomplete lineage sorting. In this paper, we introduce a new method for inferring most parsimonious phylogenetic networks on data that include polyploid species. Taking gene tree topologies as input, the method seeks a phylogenetic network that minimizes deep coalescences while accounting for polyploidy. We demonstrate the performance of the method on both simulated and biological data. The inference method as well as a method for evaluating evolutionary hypotheses in the form of phylogenetic networks are implemented and publicly available in the PhyloNet software package.

scholarly journals Empirical Performance of Tree-based Inference of Phylogenetic Networks

2019 ◽  
Author(s):  
Zhen Cao ◽  
Luay Nakhleh
Keyword(s):  
Network Inference ◽  
Computational Cost ◽  
Phylogenetic Network ◽  
Large Data ◽  
Phylogenetic Networks ◽  
Divide And Conquer ◽  
Maximum Likelihood Estimates ◽  
Tree Inference ◽  
Backbone Tree ◽  
Network Space

AbstractPhylogenetic networks extend the phylogenetic tree structure and allow for modeling vertical and horizontal evolution in a single framework. Statistical inference of phylogenetic networks is prohibitive and currently limited to small networks. An approach that could significantly improve phylogenetic network space exploration is based on first inferring an evolutionary tree of the species under consideration, and then augmenting the tree into a network by adding a set of “horizontal” edges to better fit the data.In this paper, we study the performance of such an approach on networks generated under a birth-hybridization model and explore its feasibility as an alternative to approaches that search the phylogenetic network space directly (without relying on a fixed underlying tree). We find that the concatenation method does poorly at obtaining a “backbone” tree that could be augmented into the correct network, whereas the popular species tree inference method ASTRAL does significantly better at such a task. We then evaluated the tree-to-network augmentation phase under the minimizing deep coalescence and pseudo-likelihood criteria. We find that even though this is a much faster approach than the direct search of the network space, the accuracy is much poorer, even when the backbone tree is a good starting tree.Our results show that tree-based inference of phylogenetic networks could yield very poor results. As exploration of the network space directly in search of maximum likelihood estimates or a representative sample of the posterior is very expensive, significant improvements to the computational complexity of phylogenetic network inference are imperative if analyses of large data sets are to be performed. We show that a recently developed divide-and-conquer approach significantly outperforms tree-based inference in terms of accuracy, albeit still at a higher computational cost.

scholarly journals Inference of Species Phylogenies from Bi-allelic Markers Using Pseudo-likelihood

2018 ◽  
Author(s):  
Jiafan Zhu ◽  
Luay Nakhleh
Keyword(s):  
Network Inference ◽  
Sequence Data ◽  
Phylogenetic Network ◽  
Simulated Data ◽  
Biological Data ◽  
Phylogenetic Networks ◽  
Gene Trees ◽  
Multispecies Coalescent ◽  
Pseudo Likelihood ◽  
Computational Bottleneck

AbstractMotivationPhylogenetic networks represent reticulate evolutionary histories. Statistical methods for their inference under the multispecies coalescent have recently been developed. A particularly powerful approach uses data that consist of bi-allelic markers (e.g., single nucleotide polymorphism data) and allows for exact likelihood computations of phylogenetic networks while numerically integrating over all possible gene trees per marker. While the approach has good accuracy in terms of estimating the network and its parameters, likelihood computations remain a major computational bottleneck and limit the method’s applicability.ResultsIn this paper, we first demonstrate why likelihood computations of networks take orders of magnitude more time when compared to trees. We then propose an approach for inference of phylo-genetic networks based on pseudo-likelihood using bi-allelic markers. We demonstrate the scalability and accuracy of phylogenetic network inference via pseudo-likelihood computations on simulated data. Furthermore, we demonstrate aspects of robustness of the method to violations in the underlying assumptions of the employed statistical model. Finally, we demonstrate the application of the method to biological data. The proposed method allows for analyzing larger data sets in terms of the numbers of taxa and reticulation events. While pseudo-likelihood had been proposed before for data consisting of gene trees, the work here uses sequence data directly, offering several advantages as we discuss.AvailabilityThe methods have been implemented in PhyloNet (http://bioinfocs.rice.edu/phylonet)[email protected], [email protected]

scholarly journals The Implications of Over-Estimating Gene Tree Discordance on a Rapid-Radiation Species Tree (Blattodea: Blaberidae)

2019 ◽  
Author(s):  
Dominic A. Evangelista ◽  
Michael A. Gilchrist ◽  
Frédéric Legendre ◽  
Brian O’Meara
Keyword(s):  
Gene Tree ◽  
Predictive Ability ◽  
Species Tree ◽  
Gene Trees ◽  
Species Trees ◽  
Rapid Radiation ◽  
Tree Inference ◽  
Tree Topologies ◽  
Gene Tree Discordance ◽  
Support Relationships

AbstractPatterns of discordance between gene trees and the species trees they reside in are crucial to the debate over the superiority of coalescent or concatenation approaches to tree inference. However, errors in estimating gene tree topologies obfuscate the issue by making gene trees appear erroneously discordant with the species tree. We thus test the prevalence of discordance between gene trees and their species tree using an empirical dataset for a clade with a rapid radiation (Blaberidae). We find that one model of codon evolution (FMutSel0) prefers gene trees that are less discordant, while another (SelAC) shows no such preference. We compare the species trees resulting from the selected sets of gene trees on the basis of internal consistency, predictive ability, and congruence with independent data. The species tree resulting from gene trees those chosen by FMutSel0, a set with low discordance, is the most robust and biologically plausible. Thus, we conclude that the results from FMutSel0 are better supported: simple models (i.e., GTR and ECM) infer trees with erroneously high levels of gene tree discordance. Furthermore, the amount of discordance in the set of gene trees has a large effect on the downstream phylogeny. Thus, decreasing gene tree error by lessening erroneous discordance can result in higher quality species trees. These results allow us to support relationships among blaberid cockroaches that were previously in flux as they now demonstrate molecular and morphological congruence.

scholarly journals Impact of Ghost Introgression on Coalescent-based Species Tree Inference and Estimation of Divergence Time

2022 ◽  
Author(s):  
XiaoXu Pang ◽  
Da-Yong Zhang
Keyword(s):  
Incomplete Lineage Sorting ◽  
Divergence Time ◽  
Species Tree ◽  
Gene Trees ◽  
Species Trees ◽  
Lineage Sorting ◽  
Multispecies Coalescent ◽  
Tree Inference ◽  
Tree Methods ◽  
The Impact

The species studied in any evolutionary investigation generally constitute a very small proportion of all the species currently existing or that have gone extinct. It is therefore likely that introgression, which is widespread across the tree of life, involves "ghosts," i.e., unsampled, unknown, or extinct lineages. However, the impact of ghost introgression on estimations of species trees has been rarely studied and is thus poorly understood. In this study, we use mathematical analysis and simulations to examine the robustness of species tree methods based on a multispecies coalescent model under gene flow sourcing from an extant or ghost lineage. We found that very low levels of extant or ghost introgression can result in anomalous gene trees (AGTs) on three-taxon rooted trees if accompanied by strong incomplete lineage sorting (ILS). In contrast, even massive introgression, with more than half of the recipient genome descending from the donor lineage, may not necessarily lead to AGTs. In cases involving an ingroup lineage (defined as one that diverged no earlier than the most basal species under investigation) acting as the donor of introgression, the time of root divergence among the investigated species was either underestimated or remained unaffected, but for the cases of outgroup ghost lineages acting as donors, the divergence time was generally overestimated. Under many conditions of ingroup introgression, the stronger the ILS was, the higher was the accuracy of estimating the time of root divergence, although the topology of the species tree is more prone to be biased by the effect of introgression.

scholarly journals How to Tackle Phylogenetic Discordance in Recent and Rapidly Radiating Groups? Developing a Workflow Using Loricaria (Asteraceae) as an Example

2022 ◽  
Vol 12 ◽  
Author(s):  
Martha Kandziora ◽  
Petr Sklenář ◽  
Filip Kolář ◽  
Roswitha Schmickl
Keyword(s):  
Incomplete Lineage Sorting ◽  
Gene Tree ◽  
Species Tree ◽  
Secondary Contact ◽  
Gene Trees ◽  
Species Trees ◽  
Lineage Sorting ◽  
Phylogenetic Discordance ◽  
Gene Tree Discordance ◽  
High Degree

A major challenge in phylogenetics and -genomics is to resolve young rapidly radiating groups. The fast succession of species increases the probability of incomplete lineage sorting (ILS), and different topologies of the gene trees are expected, leading to gene tree discordance, i.e., not all gene trees represent the species tree. Phylogenetic discordance is common in phylogenomic datasets, and apart from ILS, additional sources include hybridization, whole-genome duplication, and methodological artifacts. Despite a high degree of gene tree discordance, species trees are often well supported and the sources of discordance are not further addressed in phylogenomic studies, which can eventually lead to incorrect phylogenetic hypotheses, especially in rapidly radiating groups. We chose the high-Andean Asteraceae genus Loricaria to shed light on the potential sources of phylogenetic discordance and generated a phylogenetic hypothesis. By accounting for paralogy during gene tree inference, we generated a species tree based on hundreds of nuclear loci, using Hyb-Seq, and a plastome phylogeny obtained from off-target reads during target enrichment. We observed a high degree of gene tree discordance, which we found implausible at first sight, because the genus did not show evidence of hybridization in previous studies. We used various phylogenomic analyses (trees and networks) as well as the D-statistics to test for ILS and hybridization, which we developed into a workflow on how to tackle phylogenetic discordance in recent radiations. We found strong evidence for ILS and hybridization within the genus Loricaria. Low genetic differentiation was evident between species located in different Andean cordilleras, which could be indicative of substantial introgression between populations, promoted during Pleistocene glaciations, when alpine habitats shifted creating opportunities for secondary contact and hybridization.

scholarly journals MSCquartets 1.0: Quartet methods for species trees and networks under the multispecies coalescent model in R

2020 ◽  
Author(s):  
John A Rhodes ◽  
Hector Baños ◽  
Jonathan D Mitchell ◽  
Elizabeth S Allman
Keyword(s):  
Network Inference ◽  
Incomplete Lineage Sorting ◽  
R Package ◽  
Species Tree ◽  
Supplementary Information ◽  
Species Trees ◽  
Lineage Sorting ◽  
Coalescent Model ◽  
Multispecies Coalescent ◽  
Tree Inference

Abstract Summary MSCquartets is an R package for species tree hypothesis testing, inference of species trees, and inference of species networks under the Multispecies Coalescent model of incomplete lineage sorting and its network analog. Input for these analyses are collections of metric or topological locus trees which are then summarized by the quartets displayed on them. Results of hypothesis tests at user-supplied levels are displayed in a simplex plot by color-coded points. The package implements the QDC and WQDC algorithms for topological and metric species tree inference, and the NANUQ algorithm for level-1 topological species network inference, all of which give statistically consistent estimators under the model. Availability MSCquartets is available through the Comprehensive R Archive Network: https://CRAN.R-project.org/package=MSCquartets. Supplementary information Supplementary materials, including example data and analyses, are incorporated into the package.

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