scholarly journals StarBeast3: Adaptive Parallelised Bayesian Inference of the Multispecies Coalescent

2021 ◽  
Author(s):  
Jordan Douglas ◽  
Cinthy L. Jiménez-Silva ◽  
Remco Bouckaert
Keyword(s):  
Bayesian Inference ◽  
Genomic Sequence ◽  
Sequence Data ◽  
Gene Tree ◽  
Gene Trees ◽  
Multispecies Coalescent ◽  
Tree Inference ◽  
Synthetic Datasets ◽  
Set Up ◽  
The Cost

AbstractAs genomic sequence data becomes increasingly available, inferring the phylogeny of the species as that of concatenated genomic data can be enticing. However, this approach makes for a biased estimator of branch lengths and substitution rates and an inconsistent estimator of tree topology. Bayesian multispecies coalescent methods address these issues. This is achieved by embedding a set of gene trees within a species tree and jointly inferring both under a Bayesian framework. However, this approach comes at the cost of increased computational demand. Here, we introduce StarBeast3 – a software package for efficient Bayesian inference of the multispecies coalescent model via Markov chain Monte Carlo. We gain efficiency by introducing cutting-edge proposal kernels and adaptive operators, and StarBeast3 is particularly efficient when a relaxed clock model is applied. Furthermore, gene tree inference is parallelised, allowing the software to scale with the size of the problem. We validated our software and benchmarked its performance using three real and two synthetic datasets. Our results indicate that StarBeast3 is up to one-and-a-half orders of magnitude faster than StarBeast2, and therefore more than two orders faster than *BEAST, depending on the dataset and on the parameter, and is suitable for multispecies coalescent inference on large datasets (100+ genes). StarBeast3 is open-source and is easy to set up with a friendly graphical user interface.

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.

The Multispecies Coalescent in Space and Time

2020 ◽  
Author(s):  
Patrick F. McKenzie ◽  
Deren A. R. Eaton
Keyword(s):  
Gene Tree ◽  
Species Tree ◽  
Gene Trees ◽  
Effective Population ◽  
Sliding Windows ◽  
Multispecies Coalescent ◽  
A Genome ◽  
Tree Inference ◽  
Rate Of Decay ◽  
Coalescent Time

AbstractA key distinction between species tree inference under the multi-species coalescent model (MSC), and the inference of gene trees in sliding windows along a genome, is in the effect of genetic linkage. Whereas the MSC explicitly assumes genealogies to be unlinked, i.e., statistically independent, genealogies located close together on genomes are spatially auto-correlated. Here we use tree sequence simulations with recombination to explore the effects of species tree parameters on spatial patterns of linkage among genealogies. We decompose coalescent time units to demonstrate differential effects of generation time and effective population size on spatial coalescent patterns, and we define a new metric, “phylogenetic linkage,” for measuring the rate of decay of phylogenetic similarity by comparison to distances among unlinked genealogies. Finally, we provide a simple example where accounting for phylogenetic linkage in sliding window analyses improves local gene tree inference.

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

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.

scholarly journals Estimation of Cross-Species Introgression Rates using Genomic Data Despite Model Unidentifiability

2021 ◽  
Author(s):  
Ziheng Yang ◽  
Thomas Flouris
Keyword(s):  
Genomic Sequence ◽  
Sequence Data ◽  
Gene Tree ◽  
Synthetic Data ◽  
Genomic Data ◽  
Sister Species ◽  
Label Switching ◽  
Cross Model ◽  
Multispecies Coalescent ◽  
Full Likelihood

The multispecies coalescent with introgression (MSci) model accommodates both the coalescent process and cross-species introgression/ hybridization events, two major processes that create genealogical fluctuations across the genome and gene-tree-species-tree discordance. Full likelihood implementations of the MSci model take such fluctuations as a major source of information about the history of species divergence and gene flow, and provide a powerful tool for estimating the direction, timing and strength of cross-species introgression using multilocus sequence data. However, introgression models, in particular those that accommodate bidirectional introgression (BDI), are known to cause unidentifiability issues of the label-switching type, whereby different models or parameters make the same predictions about the genomic data and thus cannot be distinguished by the data. Nevertheless, there has been no systematic study of unidentifiability when full likelihood methods are applied. Here we characterize the unidentifiability of arbitrary BDI models and derive simple rules for its identification. In general, an MSci model with k BDI events has 2^k unidentifiable towers in the posterior, with each BDI event between sister species creating within-model unidentifiability and each BDI between non-sister species creating cross-model unidentifiability. We develop novel algorithms for processing Markov chain Monte Carlo (MCMC) samples to remove label switching and implement them in the BPP program. We analyze genomic sequence data from Heliconius butterflies as well as synthetic data to illustrate the utility of the BDI models and the new algorithms.

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 Retroposon Insertions within a Multispecies Coalescent Framework Suggest that Ratite Phylogeny is not in the ‘Anomaly Zone’

2019 ◽  
Author(s):  
Mark S. Springer ◽  
John Gatesy
Keyword(s):  
Phylogenetic Analysis ◽  
Sequence Data ◽  
Gene Tree ◽  
Reconstruction Error ◽  
Species Tree ◽  
Neutral Evolution ◽  
Gene Trees ◽  
Tree Reconstruction ◽  
Multispecies Coalescent ◽  
Branch Lengths

ABSTRACTSummary coalescence methods were developed to address the negative impacts of incomplete lineage sorting on species tree estimation with concatenation. Coalescence methods are statistically consistent if certain requirements are met including no intralocus recombination, neutral evolution, and no gene tree reconstruction error. However, the assumption of no intralocus recombination may not hold for many DNA sequence data sets, and neutral evolution is not the rule for genetic markers that are commonly employed in phylogenomic coalescence analyses. Most importantly, the assumption of no gene tree reconstruction error is routinely violated, especially for rapid radiations that are deep in the Tree of Life. With the sequencing of complete genomes and novel pipelines, phylogenetic analysis of retroposon insertions has emerged as a valuable alternative to sequence-based phylogenetic analysis. Retroposon insertions avoid or reduce several problems that beset analysis of sequence data with summary coalescence methods: 1) intralocus recombination is avoided because retroposon insertions are singular evolutionary events, 2) neutral evolution is approximated in many cases, and 3) gene tree reconstruction errors are rare because retroposons have low rates of homoplasy. However, the analysis of retroposons within a multispecies coalescent framework has not been realized. Here, we propose a simple workaround in which a retroposon insertion matrix is first transformed into a series of incompletely resolved gene trees. Next, the program ASTRAL is used to estimate a species tree in the statistically consistent framework of the multispecies coalescent. The inferred species tree includes support scores at all nodes and internal branch lengths in coalescent units. As a test case, we analyzed a retroposon dataset for palaeognath birds (ratites and tinamous) with ASTRAL and compared the resulting species tree to an MP-EST species tree for the same clade derived from thousands of sequence-based gene trees. The MP-EST species tree suggests an empirical case of the ‘anomaly zone’ with three very short internal branches at the base of Palaeognathae, and as predicted for anomaly zone conditions, the MP-EST species tree differs from the most common gene tree. Although identical in topology to the MP-EST tree, the ASTRAL species tree based on retroposons shows branch lengths that are much longer and incompatible with anomaly zone conditions. Simulation of gene trees from the retroposon-based species tree reveals that the most common gene tree matches the species tree. We contend that the wide discrepancies in branch lengths between sequence-based and retroposon-based species trees are explained by the greater accuracy of retroposon gene trees (bipartitions) relative to sequence-based gene trees. Coalescence analysis of retroposon data provides a promising alternative to the status quo by reducing gene tree reconstruction error that can have large impacts on both branch length estimates and evolutionary interpretations.

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 Detecting destabilizing species in the phylogenetic backbone of Potentilla (Rosaceae) using low-copy nuclear markers

AoB Plants ◽  
2020 ◽  
Vol 12 (3) ◽  
Author(s):  
Nannie L Persson ◽  
Ingrid Toresen ◽  
Heidi Lie Andersen ◽  
Jenny E E Smedmark ◽  
Torsten Eriksson
Keyword(s):  
Incomplete Lineage Sorting ◽  
Gene Tree ◽  
Data Sets ◽  
Gene Trees ◽  
Lineage Sorting ◽  
Nuclear Markers ◽  
Data Set ◽  
Multispecies Coalescent ◽  
Single Marker ◽  
Named Groups

Abstract The genus Potentilla (Rosaceae) has been subjected to several phylogenetic studies, but resolving its evolutionary history has proven challenging. Previous analyses recovered six, informally named, groups: the Argentea, Ivesioid, Fragarioides, Reptans, Alba and Anserina clades, but the relationships among some of these clades differ between data sets. The Reptans clade, which includes the type species of Potentilla, has been noticed to shift position between plastid and nuclear ribosomal data sets. We studied this incongruence by analysing four low-copy nuclear markers, in addition to chloroplast and nuclear ribosomal data, with a set of Bayesian phylogenetic and Multispecies Coalescent (MSC) analyses. A selective taxon removal strategy demonstrated that the included representatives from the Fragarioides clade, P. dickinsii and P. fragarioides, were the main sources of the instability seen in the trees. The Fragarioides species showed different relationships in each gene tree, and were only supported as a monophyletic group in a single marker when the Reptans clade was excluded from the analysis. The incongruences could not be explained by allopolyploidy, but rather by homoploid hybridization, incomplete lineage sorting or taxon sampling effects. When P. dickinsii and P. fragarioides were removed from the data set, a fully resolved, supported backbone phylogeny of Potentilla was obtained in the MSC analysis. Additionally, indications of autopolyploid origins of the Reptans and Ivesioid clades were discovered in the low-copy gene trees.

scholarly journals The BPP program for species tree estimation and species delimitation

2015 ◽  
Vol 61 (5) ◽  
pp. 854-865 ◽  
Author(s):  
Ziheng Yang
Keyword(s):  
Species Delimitation ◽  
Genomic Sequence ◽  
Sequence Data ◽  
Species Tree ◽  
Joint Analysis ◽  
Coalescent Model ◽  
Species Phylogeny ◽  
Multispecies Coalescent ◽  
Tree Estimation ◽  
Nuclear Loci

Abstract This paper provides an overview and a tutorial of the BPP program, which is a Bayesian MCMC program for analyzing multi-locus genomic sequence data under the multispecies coalescent model. An example dataset of five nuclear loci from the East Asian brown frogs is used to illustrate four different analyses, including estimation of species divergence times and population size parameters under the multispecies coalescent model on a fixed species phylogeny (A00), species tree estimation when the assignment and species delimitation are fixed (A01), species delimitation using a fixed guide tree (A10), and joint species delimitation and species-tree estimation or unguided species delimitation (A11). For the joint analysis (A11), two new priors are introduced, which assign uniform probabilities for the different numbers of delimited species, which may be useful when assignment, species delimitation, and species phylogeny are all inferred in one joint analysis. The paper ends with a discussion of the assumptions, the strengths and weaknesses of the BPP analysis.

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