scholarly journals Evaluating fast maximum likelihood-based phylogenetic programs using empirical phylogenomic data sets

2017 ◽  
Author(s):  
Xiaofan Zhou ◽  
Xingxing Shen ◽  
Chris Todd Hittinger ◽  
Antonis Rokas
Keyword(s):  
Maximum Likelihood ◽  
Phylogenetic Signal ◽  
Single Gene ◽  
Gene Tree ◽  
Species Tree ◽  
Data Matrix ◽  
Systematic Evaluation ◽  
Data Sets ◽  
Tree Inference ◽  
Data Matrices

AbstractPhylogenetics has witnessed dramatic increases in the sizes of data matrices assembled to resolve branches of the tree of life, motivating the development of programs for fast, yet accurate, inference. For example, several different fast programs have been developed in the very popular maximum likelihood framework, including RAxML/ExaML, PhyML, IQ-TREE, and FastTree. Although these four programs are widely used, a systematic evaluation and comparison of their performance using empirical genome-scale data matrices has so far been lacking. To address this question, we evaluated these four programs on 19 empirical phylogenomic data sets from diverse animal, plant, and fungal lineages with respect to likelihood maximization, tree topology, and computational speed. For single-gene tree inference, we found that the more exhaustive and slower strategies (ten searches per alignment) outperformed faster strategies (one tree search per alignment) using RAxML, PhyML, or IQ-TREE. Interestingly, single-gene trees inferred by the three programs yielded comparable coalescent-based species tree estimations. For concatenation–based species tree inference, IQ-TREE consistently achieved the best-observed likelihoods for all data sets, and RAxML/ExaML was a close second. In contrast, PhyML often failed to complete concatenation-based analyses, whereas FastTree was the fastest but generated lower likelihood values and more dissimilar tree topologies in both types of analyses. Finally, data matrix properties, such as the number of taxa and the strength of phylogenetic signal, sometimes substantially influenced the relative performance of the programs. Our results provide real-world gene and species tree phylogenetic inference benchmarks to inform the design and execution of large-scale phylogenomic data analyses.

scholarly journals Phylogenetic conflicts, combinability, and deep phylogenomics in plants

2018 ◽  
Author(s):  
Stephen A. Smith ◽  
Nathanael Walker-Hale ◽  
Joseph F. Walker ◽  
Joseph W. Brown
Keyword(s):  
Phylogenetic Relationships ◽  
Phylogenetic Signal ◽  
Gene Tree ◽  
Species Tree ◽  
Gene Trees ◽  
Data Filtering ◽  
Tree Inference ◽  
Tree Methods ◽  
Inference Methods ◽  
Species Tree Inference

AbstractStudies have demonstrated that pervasive gene tree conflict underlies several important phylogenetic relationships where different species tree methods produce conflicting results. Here, we present a means of dissecting the phylogenetic signal for alternative resolutions within a dataset in order to resolve recalcitrant relationships and, importantly, identify what the dataset is unable to resolve. These procedures extend upon methods for isolating conflict and concordance involving specific candidate relationships and can be used to identify systematic error and disambiguate sources of conflict among species tree inference methods. We demonstrate these on a large phylogenomic plant dataset. Our results support the placement of Amborella as sister to the remaining extant angiosperms, Gnetales as sister to pines, and the monophyly of extant gymnosperms. Several other contentious relationships, including the resolution of relationships within the bryophytes and the eudicots, remain uncertain given the low number of supporting gene trees. To address whether concatenation of filtered genes amplified phylogenetic signal for relationships, we implemented a combinatorial heuristic to test combinability of genes. We found that nested conflicts limited the ability of data filtering methods to fully ameliorate conflicting signal amongst gene trees. These analyses confirmed that the underlying conflicting signal does not support broad concatenation of genes. Our approach provides a means of dissecting a specific dataset to address deep phylogenetic relationships while also identifying the inferential boundaries of the dataset.

scholarly journals Consistency of SVDQuartets and Maximum Likelihood for Coalescent-Based Species Tree Estimation

2020 ◽  
Vol 70 (1) ◽  
pp. 33-48 ◽  
Author(s):  
Matthew Wascher ◽  
Laura Kubatko
Keyword(s):  
Maximum Likelihood ◽  
Gene Tree ◽  
Species Tree ◽  
Gene Trees ◽  
Data Types ◽  
Multispecies Coalescent ◽  
Consistency Results ◽  
True Tree ◽  
Tree Inference ◽  
Statistical Consistency

Abstract Numerous methods for inferring species-level phylogenies under the coalescent model have been proposed within the last 20 years, and debates continue about the relative strengths and weaknesses of these methods. One desirable property of a phylogenetic estimator is that of statistical consistency, which means intuitively that as more data are collected, the probability that the estimated tree has the same topology as the true tree goes to 1. To date, consistency results for species tree inference under the multispecies coalescent (MSC) have been derived only for summary statistics methods, such as ASTRAL and MP-EST. These methods have been found to be consistent given true gene trees but may be inconsistent when gene trees are estimated from data for loci of finite length. Here, we consider the question of statistical consistency for four taxa for SVDQuartets for general data types, as well as for the maximum likelihood (ML) method in the case in which the data are a collection of sites generated under the MSC model such that the sites are conditionally independent given the species tree (we call these data coalescent independent sites [CIS] data). We show that SVDQuartets is statistically consistent for all data types (i.e., for both CIS data and for multilocus data), and we derive its rate of convergence. We additionally show that ML is consistent for CIS data under the JC69 model and discuss why a proof for the more general multilocus case is difficult. Finally, we compare the performance of ML and SDVQuartets using simulation for both data types. [Consistency; gene tree; maximum likelihood; multilocus data; hylogenetic inference; species tree; SVDQuartets.]

scholarly journals Gene tree discord, simplex plots, and statistical tests under the coalescent

2020 ◽  
Author(s):  
Elizabeth S. Allman ◽  
Jonathan D. Mitchell ◽  
John A. Rhodes
Keyword(s):  
Incomplete Lineage Sorting ◽  
Statistical Tests ◽  
Gene Tree ◽  
Complex Model ◽  
Species Tree ◽  
Data Sets ◽  
Gene Trees ◽  
Lineage Sorting ◽  
Multispecies Coalescent ◽  
Tree Inference

AbstractA simple graphical device, the simplex plot of quartet concordance factors, is introduced to aid in the exploration of a collection of gene trees on a common set of taxa. A single plot summarizes all gene tree discord, and allows for visual comparison to the expected discord from the multispecies coalescent model (MSC) of incomplete lineage sorting on a species tree. A formal statistical procedure is described that can quantify the deviation from expectation for each subset of four taxa, suggesting when the data is not in accord with the MSC, and thus either gene tree inference error is substantial or a more complex model such as that on a network may be required. If the collection of gene trees appears to be in accord with the MSC, the plots may reveal when substantial incomplete lineage sorting is present and coalescent based species tree inference is preferred over concatenation approaches. Applications to both simulated and empirical multilocus data sets illustrate the insights provided.

scholarly journals Non-parametric correction of estimated gene trees using TRACTION

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Sarah Christensen ◽  
Erin K. Molloy ◽  
Pranjal Vachaspati ◽  
Ananya Yammanuru ◽  
Tandy Warnow
Keyword(s):  
Incomplete Lineage Sorting ◽  
Phylogenetic Signal ◽  
Estimation Error ◽  
Single Gene ◽  
Gene Tree ◽  
Species Tree ◽  
Computational Techniques ◽  
Gene Trees ◽  
Species Trees ◽  
Sequencing Data

Abstract Motivation Estimated gene trees are often inaccurate, due to insufficient phylogenetic signal in the single gene alignment, among other causes. Gene tree correction aims to improve the accuracy of an estimated gene tree by using computational techniques along with auxiliary information, such as a reference species tree or sequencing data. However, gene trees and species trees can differ as a result of gene duplication and loss (GDL), incomplete lineage sorting (ILS), and other biological processes. Thus gene tree correction methods need to take estimation error as well as gene tree heterogeneity into account. Many prior gene tree correction methods have been developed for the case where GDL is present. Results Here, we study the problem of gene tree correction where gene tree heterogeneity is instead due to ILS and/or HGT. We introduce TRACTION, a simple polynomial time method that provably finds an optimal solution to the RF-optimal tree refinement and completion (RF-OTRC) Problem, which seeks a refinement and completion of a singly-labeled gene tree with respect to a given singly-labeled species tree so as to minimize the Robinson−Foulds (RF) distance. Our extensive simulation study on 68,000 estimated gene trees shows that TRACTION matches or improves on the accuracy of well-established methods from the GDL literature when HGT and ILS are both present, and ties for best under the ILS-only conditions. Furthermore, TRACTION ties for fastest on these datasets. We also show that a naive generalization of the RF-OTRC problem to multi-labeled trees is possible, but can produce misleading results where gene tree heterogeneity is due to GDL.

scholarly journals Accounting for Uncertainty in Gene Tree Estimation: Summary-Coalescent Species Tree Inference in a Challenging Radiation of Australian Lizards

2016 ◽  
Author(s):  
Mozes P.K. Blom ◽  
Jason G. Bragg ◽  
Sally Potter ◽  
Craig Moritz
Keyword(s):  
Phylogenetic Signal ◽  
Gene Tree ◽  
Phylogenetic Inference ◽  
Species Tree ◽  
Gene Trees ◽  
Tree Inference ◽  
Tree Estimation ◽  
Tree Resolution ◽  
The Impact ◽  
Species Tree Inference

AbstractAccurate gene tree inference is an important aspect of species tree estimation in a summary-coalescent framework. Yet, in empirical studies, inferred gene trees differ in accuracy due to stochastic variation in phylogenetic signal between targeted loci. Empiricists should therefore examine the consistency of species tree inference, while accounting for the observed heterogeneity in gene tree resolution of phylogenomic datasets. Here, we assess the impact of gene tree estimation error on summary-coalescent species tree inference by screening ~2000 exonic loci based on gene tree resolution prior to phylogenetic inference. We focus on a phylogenetically challenging radiation of Australian lizards (genus Cryptoblepharus, Scincidae) and explore effects on topology and support. We identify a well-supported topology based on all loci and find that a relatively small number of high-resolution gene trees can be sufficient to converge on the same topology. Adding gene trees with decreasing resolution produced a generally consistent topology, and increased confidence for specific bipartitions that were poorly supported when using a small number of informative loci. This corroborates coalescent-based simulation studies that have highlighted the need for a large number of loci to confidently resolve challenging relationships and refutes the notion that low-resolution gene trees introduce phylogenetic noise. Further, our study also highlights the value of quantifying changes in nodal support across locus subsets of increasing size (but decreasing gene tree resolution). Such detailed analyses can reveal anomalous fluctuations in support at some nodes, suggesting the possibility of model violation. By characterizing the heterogeneity in phylogenetic signal among loci, we can account for uncertainty in gene tree estimation and assess its effect on the consistency of the species tree estimate. We suggest that the evaluation of gene tree resolution should be incorporated in the analysis of empirical phylogenomic datasets. This will ultimately increase our confidence in species tree estimation using summary-coalescent methods and enable us to exploit genomic data for phylogenetic inference.

scholarly journals Phylogenetic Conflicts, Combinability, and Deep Phylogenomics in Plants

2019 ◽  
Vol 69 (3) ◽  
pp. 579-592 ◽  
Author(s):  
Stephen A Smith ◽  
Nathanael Walker-Hale ◽  
Joseph F Walker ◽  
Joseph W Brown
Keyword(s):  
Phylogenetic Relationships ◽  
Phylogenetic Signal ◽  
Gene Tree ◽  
Species Tree ◽  
Gene Trees ◽  
Data Set ◽  
Tree Inference ◽  
Tree Methods ◽  
Plant Data ◽  
Inference Methods

Abstract Studies have demonstrated that pervasive gene tree conflict underlies several important phylogenetic relationships where different species tree methods produce conflicting results. Here, we present a means of dissecting the phylogenetic signal for alternative resolutions within a data set in order to resolve recalcitrant relationships and, importantly, identify what the data set is unable to resolve. These procedures extend upon methods for isolating conflict and concordance involving specific candidate relationships and can be used to identify systematic error and disambiguate sources of conflict among species tree inference methods. We demonstrate these on a large phylogenomic plant data set. Our results support the placement of Amborella as sister to the remaining extant angiosperms, Gnetales as sister to pines, and the monophyly of extant gymnosperms. Several other contentious relationships, including the resolution of relationships within the bryophytes and the eudicots, remain uncertain given the low number of supporting gene trees. To address whether concatenation of filtered genes amplified phylogenetic signal for relationships, we implemented a combinatorial heuristic to test combinability of genes. We found that nested conflicts limited the ability of data filtering methods to fully ameliorate conflicting signal amongst gene trees. These analyses confirmed that the underlying conflicting signal does not support broad concatenation of genes. Our approach provides a means of dissecting a specific data set to address deep phylogenetic relationships while also identifying the inferential boundaries of the data set. [Angiosperms; coalescent; gene-tree conflict; genomics; phylogenetics; phylogenomics.]

scholarly journals SpeciesRax: A tool for maximum likelihood species tree inference from gene family trees under duplication, transfer, and loss.

2021 ◽  
Author(s):  
Benoit Morel ◽  
Paul Schade ◽  
Sarah Lutteropp ◽  
Tom A. Williams ◽  
Gergely J. Szöllösi ◽  
...  
Keyword(s):  
Maximum Likelihood ◽  
Gene Family ◽  
Gene Families ◽  
Species Tree ◽  
Likelihood Method ◽  
Gene Trees ◽  
Informative Signal ◽  
Tree Inference ◽  
Species Tree Inference ◽  
Family Trees

Species tree inference from gene family trees is becoming increasingly popular because it can account for discordance between the species tree and the corresponding gene family trees. In particular, methods that can account for multiple-copy gene families exhibit potential to leverage paralogy as informative signal. At present, there does not exist any widely adopted inference method for this purpose. Here, we present SpeciesRax, the first maximum likelihood method that can infer a rooted species tree from a set of gene family trees and can account for gene duplication, loss, and transfer events. By explicitly modelling events by which gene trees can depart from the species tree, SpeciesRax leverages the phylogenetic rooting signal in gene trees. SpeciesRax infers species tree branch lengths in units of expected substitutions per site and branch support values via paralogy-aware quartets extracted from the gene family trees. Using both empirical and simulated datasets we show that SpeciesRax is at least as accurate as the best competing methods while being one order of magnitude faster on large datasets at the same time. We used SpeciesRax to infer a biologically plausible rooted phylogeny of the vertebrates comprising $188$ species from $31612$ gene families in one hour using $40$ cores. SpeciesRax is available under GNU GPL at https://github.com/BenoitMorel/GeneRax and on BioConda.

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 Genomic Characterization and Curation of UCEs Improves Species Tree Reconstruction

2020 ◽  
Author(s):  
Matthew H Van Dam ◽  
James B Henderson ◽  
Lauren Esposito ◽  
Michelle Trautwein
Keyword(s):  
Marine Invertebrates ◽  
Phylogenetic Analyses ◽  
Single Gene ◽  
Gene Tree ◽  
Single Copy ◽  
Species Tree ◽  
Bootstrap Support ◽  
Gene Trees ◽  
Species Trees ◽  
Tree Reconstruction

Abstract Ultraconserved genomic elements (UCEs) are generally treated as independent loci in phylogenetic analyses. The identification pipeline for UCE probes does not require prior knowledge of genetic identity, only selecting loci that are highly conserved, single copy, without repeats, and of a particular length. Here, we characterized UCEs from 11 phylogenomic studies across the animal tree of life, from birds to marine invertebrates. We found that within vertebrate lineages, UCEs are mostly intronic and intergenic, while in invertebrates, the majority are in exons. We then curated four different sets of UCE markers by genomic category from five different studies including: birds, mammals, fish, Hymenoptera (ants, wasps, and bees), and Coleoptera (beetles). Of genes captured by UCEs, we find that many are represented by two or more UCEs, corresponding to nonoverlapping segments of a single gene. We considered these UCEs to be nonindependent, merged all UCEs that belonged to a particular gene, constructed gene and species trees, and then evaluated the subsequent effect of merging cogenic UCEs on gene and species tree reconstruction. Average bootstrap support for merged UCE gene trees was significantly improved across all data sets apparently driven by the increase in loci length. Additionally, we conducted simulations and found that gene trees generated from merged UCEs were more accurate than those generated by unmerged UCEs. As loci length improves gene tree accuracy, this modest degree of UCE characterization and curation impacts downstream analyses and demonstrates the advantages of incorporating basic genomic characterizations into phylogenomic analyses. [Anchored hybrid enrichment; ants; ASTRAL; bait capture; carangimorph; Coleoptera; conserved nonexonic elements; exon capture; gene tree; Hymenoptera; mammal; phylogenomic markers; songbird; species tree; ultraconserved elements; weevils.]

Sign in / Sign up

Export Citation Format

Share Document