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 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 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 Analyzing contentious relationships and outlier genes in phylogenomics

2017 ◽  
Author(s):  
Joseph F. Walker ◽  
Joseph W. Brown ◽  
Stephen A. Smith
Keyword(s):  
Incomplete Lineage Sorting ◽  
Species Tree ◽  
Gene Trees ◽  
Species Trees ◽  
Lineage Sorting ◽  
Tree Inference ◽  
Small Set ◽  
Tree Methods ◽  
Edge Based ◽  
Species Tree Inference

ABSTRACTRecent studies have demonstrated that conflict is common among gene trees in phylogenomic studies, and that less than one percent of genes may ultimately drive species tree inference in supermatrix analyses. Here, we examined two datasets where supermatrix and coalescent-based species trees conflict. We identified two highly influential “outlier” genes in each dataset. When removed from each dataset, the inferred supermatrix trees matched the topologies obtained from coalescent analyses. We also demonstrate that, while the outlier genes in the vertebrate dataset have been shown in a previous study to be the result of errors in orthology detection, the outlier genes from a plant dataset did not exhibit any obvious systematic error and therefore may be the result of some biological process yet to be determined. While topological comparisons among a small set of alternate topologies can be helpful in discovering outlier genes, they can be limited in several ways, such as assuming all genes share the same topology. Coalescent species tree methods relax this assumption but do not explicitly facilitate the examination of specific edges. Coalescent methods often also assume that conflict is the result of incomplete lineage sorting (ILS). Here we explored a framework that allows for quickly examining alternative edges and support for large phylogenomic datasets that does not assume a single topology for all genes. For both datasets, these analyses provided detailed results confirming the support for coalescent-based topologies. This framework suggests that we can improve our understanding of the underlying signal in phylogenomic datasets by asking more targeted edge-based questions.

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 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 Gene tree correction for reconciliation and species tree inference: Complexity and algorithms

2014 ◽  
Vol 25 ◽  
pp. 51-65 ◽  
Author(s):  
Riccardo Dondi ◽  
Nadia El-Mabrouk ◽  
Krister M. Swenson
Keyword(s):  
Gene Tree ◽  
Species Tree ◽  
Tree Inference ◽  
Species Tree Inference

scholarly journals Phylogeny of the cycads based on multiple single-copy nuclear genes: congruence of concatenated parsimony, likelihood and species tree inference methods

2013 ◽  
Vol 112 (7) ◽  
pp. 1263-1278 ◽  
Author(s):  
Dayana E. Salas-Leiva ◽  
Alan W. Meerow ◽  
Michael Calonje ◽  
M. Patrick Griffith ◽  
Javier Francisco-Ortega ◽  
...  
Keyword(s):  
Single Copy ◽  
Species Tree ◽  
Nuclear Genes ◽  
Tree Inference ◽  
Inference Methods ◽  
Species Tree Inference

scholarly journals Species Tree Inference under the Multispecies Coalescent on Data with Paralogs is Accurate

2018 ◽  
Author(s):  
Zhi Yan ◽  
Peng Du ◽  
Matthew W. Hahn ◽  
Luay Nakhleh
Keyword(s):  
Incomplete Lineage Sorting ◽  
Single Copy ◽  
Species Tree ◽  
Biological Data ◽  
Lineage Sorting ◽  
Multispecies Coalescent ◽  
Gene Copies ◽  
Tree Inference ◽  
Inference Methods ◽  
Species Tree Inference

AbstractThe multispecies coalescent (MSC) has emerged as a powerful and desirable framework for species tree inference in phylogenomic studies. Under this framework, the data for each locus is assumed to consist of orthologous, single-copy genes, and heterogeneity across loci is assumed to be due to incomplete lineage sorting (ILS). These assumptions have led biologists that use ILS-aware inference methods, whether based directly on the MSC or proven to be statistically consistent under it (collectively referred to here as MSC-based methods), to exclude all loci that are present in more than a single copy in any of the studied genomes. Furthermore, such analyses entail orthology assignment to avoid the potential of hidden paralogy in the data. 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 biological data sets, we show that running such methods on data with paralogs provide very accurate results, either by treating all gene copies within a family as alleles from multiple individuals or by randomly selecting one copy per species. Our results have significant implications for the use of MSC-based phylogenomic analyses, demonstrating that they do not have to be restricted to single-copy loci, thus greatly increasing the amount of data that can be used. [Multispecies coalescent; incomplete lineage sorting; gene duplication and loss; orthology; paralogy.]

scholarly journals Using all gene families vastly expands data available for phylogenomic inference in primates

2021 ◽  
Author(s):  
Megan L Smith ◽  
Dan Vanderpool ◽  
Matthew W. Hahn
Keyword(s):  
Branch Length ◽  
Gene Families ◽  
Phylogenetic Inference ◽  
Single Copy ◽  
Decomposition Methods ◽  
Species Tree ◽  
Primate Species ◽  
Tree Inference ◽  
Inference Methods ◽  
Species Tree Inference

Traditionally, single-copy orthologs have been the gold standard in phylogenomics. Most phylogenomic studies identify putative single-copy orthologs by using clustering approaches and retaining families with a single sequence from each species. However, this approach can severely limit the amount of data available by excluding larger families. Recent methodological 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 popular methods for species tree inference appear to be robust to the inclusion of paralogs, and hence could use all of the data from larger families. Here, we explore the effects of using all families for phylogenetic inference using genomes from 26 primate species. We compare single-copy families, orthologs extracted using tree-based decomposition approaches, and all families with all data (i.e., including orthologs and paralogs). We explore several species tree inference methods, finding that across all nodes of the tree except one, identical trees are returned across nearly all datasets and methods. As in previous studies, the relationships among Platyrrhini remain contentious; however, the tree inference methods matter more than the dataset used. We also assess the effects of each dataset on branch length estimates, measures of phylogenetic uncertainty and concordance, and in detecting introgression. Our results demonstrate that using data from larger gene families drastically increases the number of genes available for phylogenetic inference and leads to consistent estimates of branch lengths, nodal certainty and concordance, and inferences of introgression.

scholarly journals Practical Speedup of Bayesian Inference of Species Phylogenies by Restricting the Space of Gene Trees

2019 ◽  
Author(s):  
Yaxuan Wang ◽  
Huw A. Ogilvie ◽  
Luay Nakhleh
Keyword(s):  
Bayesian Inference ◽  
Species Tree ◽  
Biological Data ◽  
Small Data ◽  
Data Sets ◽  
Gene Trees ◽  
Multispecies Coalescent ◽  
Tree Inference ◽  
The Individual ◽  
Species Tree Inference

AbstractSpecies tree inference from multi-locus data has emerged as a powerful paradigm in the post-genomic era, both in terms of the accuracy of the species tree it produces as well as in terms of elucidating the processes that shaped the evolutionary history. Bayesian methods for species tree inference are desirable in this area as they have been shown to yield accurate estimates, but also to naturally provide measures of confidence in those estimates. However, the heavy computational requirements of Bayesian inference have limited the applicability of such methods to very small data sets.In this paper, we show that the computational efficiency of Bayesian inference under the multispecies coalescent can be improved in practice by restricting the space of the gene trees explored during the random walk, without sacrificing accuracy as measured by various metrics. The idea is to first infer constraints on the trees of the individual loci in the form of unresolved gene trees, and then to restrict the sampler to consider only resolutions of the constrained trees. We demonstrate the improvements gained by such an approach on both simulated and biological data.

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