ASTRAL-Pro: Quartet-Based Species-Tree Inference despite Paralogy

Abstract Phylogenetic inference from genome-wide data (phylogenomics) has revolutionized the study of evolution because it enables accounting for discordance among evolutionary histories across the genome. To this end, summary methods have been developed to allow accurate and scalable inference of species trees from gene trees. However, most of these methods, including the widely used ASTRAL, can only handle single-copy gene trees and do not attempt to model gene duplication and gene loss. As a result, most phylogenomic studies have focused on single-copy genes and have discarded large parts of the data. Here, we first propose a measure of quartet similarity between single-copy and multicopy trees that accounts for orthology and paralogy. We then introduce a method called ASTRAL-Pro (ASTRAL for PaRalogs and Orthologs) to find the species tree that optimizes our quartet similarity measure using dynamic programing. By studying its performance on an extensive collection of simulated data sets and on real data sets, we show that ASTRAL-Pro is more accurate than alternative methods.

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ASTRAL-Pro: quartet-based species tree inference despite paralogy

10.1101/2019.12.12.874727 ◽

2019 ◽

Cited By ~ 4

Author(s):

Chao Zhang ◽

Celine Scornavacca ◽

Erin K. Molloy ◽

Siavash Mirarab

Keyword(s):

Gene Duplication ◽

Gene Loss ◽

Incomplete Lineage Sorting ◽

Single Copy ◽

Species Tree ◽

Alternative Methods ◽

Gene Trees ◽

Species Trees ◽

Tree Inference ◽

Species Tree Inference

AbstractSpecies tree inference via summary methods that combine gene trees has become an increasingly common analysis in recent phylogenomic studies. This broad adoption has been partly due to the greater availability of genome-wide data and ample recognition that gene trees and species trees can differ due to biological processes such as gene duplication and gene loss. This increase has also been encouraged by the recent development of accurate and scalable summary methods, such as ASTRAL. However, most of these methods, including ASTRAL, can only handle single-copy gene trees and do not attempt to model gene duplication and gene loss. In this paper, we introduce a measure of quartet similarity between single-copy and multi-copy trees (accounting for orthology and paralogy relationships) that can be optimized via a scalable dynamic programming similar to the one used by ASTRAL. We then present a new quartet-based species tree inference method: ASTRAL-Pro (ASTRAL for PaRalogs and Orthologs). By studying its performance on an extensive collection of simulated datasets and on a real plant dataset, we show that ASTRAL-Pro is more accurate than alternative methods when gene trees differ from the species tree due to the simultaneous presence of gene duplication, gene loss, incomplete lineage sorting, and estimation errors.

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EXACT SOLUTIONS FOR SPECIES TREE INFERENCE FROM DISCORDANT GENE TREES

Journal of Bioinformatics and Computational Biology ◽

10.1142/s0219720013420055 ◽

2013 ◽

Vol 11 (05) ◽

pp. 1342005 ◽

Cited By ~ 16

Author(s):

WEN-CHIEH CHANG ◽

PAWEŁ GÓRECKI ◽

OLIVER EULENSTEIN

Keyword(s):

Exact Solutions ◽

Gene Tree ◽

Simulated Data ◽

Gene Families ◽

Species Tree ◽

Data Sets ◽

Gene Trees ◽

Species Trees ◽

Worst Case

Phylogenetic analysis has to overcome the grant challenge of inferring accurate species trees from evolutionary histories of gene families (gene trees) that are discordant with the species tree along whose branches they have evolved. Two well studied approaches to cope with this challenge are to solve either biologically informed gene tree parsimony (GTP) problems under gene duplication, gene loss, and deep coalescence, or the classic RF supertree problem that does not rely on any biological model. Despite the potential of these problems to infer credible species trees, they are NP-hard. Therefore, these problems are addressed by heuristics that typically lack any provable accuracy and precision. We describe fast dynamic programming algorithms that solve the GTP problems and the RF supertree problem exactly, and demonstrate that our algorithms can solve instances with data sets consisting of as many as 22 taxa. Extensions of our algorithms can also report the number of all optimal species trees, as well as the trees themselves. To better asses the quality of the resulting species trees that best fit the given gene trees, we also compute the worst case species trees, their numbers, and optimization score for each of the computational problems. Finally, we demonstrate the performance of our exact algorithms using empirical and simulated data sets, and analyze the quality of heuristic solutions for the studied problems by contrasting them with our exact solutions.

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

10.1101/2022.01.11.475787 ◽

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.

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Genomic Characterization and Curation of UCEs Improves Species Tree Reconstruction

Systematic Biology ◽

10.1093/sysbio/syaa063 ◽

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.]

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Genomic characterization and curation of UCEs improves species tree reconstruction

10.1101/828335 ◽

2019 ◽

Author(s):

Matthew H. Van Dam ◽

James B. Henderson ◽

Lauren Esposito ◽

Michelle Trautwein

Keyword(s):

Marine Invertebrates ◽

Phylogenetic Analyses ◽

Single Gene ◽

Single Copy ◽

Species Tree ◽

Bootstrap Support ◽

Gene Trees ◽

Species Trees ◽

Tree Reconstruction ◽

Phylogenomic Analyses

ABSTRACTUltraconserved genomic elements (UCEs), are generally treated as independent loci in phylogenetic analyses. The identification pipeline for UCE probes is agnostic to genetic identity, only selecting loci that are highly conserved, single copy, without repeats, and of a particular length. Here we characterized UCEs from 12 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 4 different sets of UCE markers by genomic category from 5 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 2 or more UCEs, corresponding to non-overlapping segments of a single gene. We considered these UCEs to be non-independent, merged all UCEs that belonged to a particular gene, constructed gene and species trees, and then evaluated the subsequent effect of merging co-genic UCEs on gene and species tree reconstruction. Average bootstrap support for merged UCE gene trees were significantly improved across all datasets. Increased loci length appears to drive this increase in bootstrap support. Additionally, we found that gene trees generated from merged UCEs were more accurate than those generated by unmerged and randomly merged UCEs, based on our simulation study. This modest degree of UCE characterization and curation impacts downstream analyses and demonstrates the advantages of incorporating basic genomic characterizations into phylogenomic analyses.

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

10.1101/770784 ◽

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

Molecular Biology and Evolution ◽

10.1093/molbev/msaa045 ◽

2020 ◽

Vol 37 (6) ◽

pp. 1809-1818

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

Abstract Species tree inference from multilocus data has emerged as a powerful paradigm in the postgenomic 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 not only 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 article, 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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Reversible Polymorphism-Aware Phylogenetic Models and their Application to Tree Inference

10.1101/048496 ◽

2016 ◽

Author(s):

Dominik Schrempf ◽

Bui Quang Minh ◽

Nicola De Maio ◽

Arndt von Haeseler ◽

Carolin Kosiol

Keyword(s):

Large Scale ◽

Incomplete Lineage Sorting ◽

Species Tree ◽

Species Trees ◽

Lineage Sorting ◽

Substitution Models ◽

Tree Inference ◽

Genome Wide Data ◽

Tree Estimation ◽

Dna Substitution

AbstractWe present a reversible Polymorphism-Aware Phylogenetic Model (revPoMo) for species tree estimation from genome-wide data. revPoMo enables the reconstruction of large scale species trees for many within-species samples. It expands the alphabet of DNA substitution models to include polymorphic states, thereby, naturally accounting for incomplete lineage sorting. We implemented revPoMo in the maximum likelihood software IQ-TREE. A simulation study and an application to great apes data show that the runtimes of our approach and standard substitution models are comparable but that revPoMo has much better accuracy in estimating trees, divergence times and mutation rates. The advantage of revPoMo is that an increase of sample size per species improves estimations but does not increase runtime. Therefore, revPoMo is a valuable tool with several applications, from speciation dating to species tree reconstruction.

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

10.1101/2020.02.13.948083 ◽

2020 ◽

Cited By ~ 1

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.

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SODA: Multi-locus species delimitation using quartet frequencies

10.1101/869396 ◽

2019 ◽

Cited By ~ 2

Author(s):

Maryam Rabiee ◽

Siavash Mirarab

Keyword(s):

Species Delimitation ◽

Branch Length ◽

Large Datasets ◽

Species Tree ◽

Gene Trees ◽

Species Trees ◽

Very Large Datasets ◽

Tree Inference ◽

Group A ◽

Tree Estimation

AbstractMotivationSpecies delimitation, the process of deciding how to group a set of organisms into units called species, is one of the most challenging problems in evolutionary computational biology. While many methods exist for species delimitation, most based on the coalescent theory, few are scalable to very large datasets and methods that scale tend to be not accurate. Species delimitation is closely related to species tree inference from discordant gene trees, a problem that has enjoyed rapid advances in recent years.ResultsIn this paper, we build on the accuracy and scalability of recent quartet-based methods for species tree estimation and propose a new method called SODA for species delimitation. SODA relies heavily on a recently developed method for testing zero branch length in species trees. In extensive simulations, we show that SODA can easily scale to very large datasets while maintaining high accuracy.AvailabilityThe code and data presented here are available on https://github.com/maryamrabiee/[email protected]

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