Assessing the Impacts of Positive Selection on Coalescent-Based Species Tree Estimation and Species Delimitation

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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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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A Simulation Study to Examine the Information Content in Phylogenomic Data Sets under the Multispecies Coalescent Model

Molecular Biology and Evolution ◽

10.1093/molbev/msaa166 ◽

2020 ◽

Vol 37 (11) ◽

pp. 3211-3224

Author(s):

Jun Huang ◽

Tomáš Flouri ◽

Ziheng Yang

Keyword(s):

Information Content ◽

Mutation Rate ◽

Species Delimitation ◽

Species Tree ◽

Data Sets ◽

Site Mutation ◽

Coalescent Model ◽

Inference Problems ◽

Multispecies Coalescent ◽

Tree Estimation

Abstract We use computer simulation to examine the information content in multilocus data sets for inference under the multispecies coalescent model. Inference problems considered include estimation of evolutionary parameters (such as species divergence times, population sizes, and cross-species introgression probabilities), species tree estimation, and species delimitation based on Bayesian comparison of delimitation models. We found that the number of loci is the most influential factor for almost all inference problems examined. Although the number of sequences per species does not appear to be important to species tree estimation, it is very influential to species delimitation. Increasing the number of sites and the per-site mutation rate both increase the mutation rate for the whole locus and these have the same effect on estimation of parameters, but the sequence length has a greater effect than the per-site mutation rate for species tree estimation. We discuss the computational costs when the data size increases and provide guidelines concerning the subsampling of genomic data to enable the application of full-likelihood methods of inference.

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The Perfect Storm: Gene Tree Estimation Error, Incomplete Lineage Sorting, and Ancient Gene Flow Explain the Most Recalcitrant Ancient Angiosperm Clade, Malpighiales

Systematic Biology ◽

10.1093/sysbio/syaa083 ◽

2020 ◽

Author(s):

Liming Cai ◽

Zhenxiang Xi ◽

Emily Moriarty Lemmon ◽

Alan R Lemmon ◽

Austin Mast ◽

...

Keyword(s):

Gene Flow ◽

Incomplete Lineage Sorting ◽

Estimation Error ◽

Gene Tree ◽

Species Tree ◽

Flowering Plant ◽

Estimation Methods ◽

Lineage Sorting ◽

Tree Estimation ◽

Perfect Storm

Abstract The genomic revolution offers renewed hope of resolving rapid radiations in the Tree of Life. The development of the multispecies coalescent (MSC) model and improved gene tree estimation methods can better accommodate gene tree heterogeneity caused by incomplete lineage sorting (ILS) and gene tree estimation error stemming from the short internal branches. However, the relative influence of these factors in species tree inference is not well understood. Using anchored hybrid enrichment, we generated a data set including 423 single-copy loci from 64 taxa representing 39 families to infer the species tree of the flowering plant order Malpighiales. This order includes nine of the top ten most unstable nodes in angiosperms, which have been hypothesized to arise from the rapid radiation during the Cretaceous. Here, we show that coalescent-based methods do not resolve the backbone of Malpighiales and concatenation methods yield inconsistent estimations, providing evidence that gene tree heterogeneity is high in this clade. Despite high levels of ILS and gene tree estimation error, our simulations demonstrate that these two factors alone are insufficient to explain the lack of resolution in this order. To explore this further, we examined triplet frequencies among empirical gene trees and discovered some of them deviated significantly from those attributed to ILS and estimation error, suggesting gene flow as an additional and previously unappreciated phenomenon promoting gene tree variation in Malpighiales. Finally, we applied a novel method to quantify the relative contribution of these three primary sources of gene tree heterogeneity and demonstrated that ILS, gene tree estimation error, and gene flow contributed to 10.0%, 34.8%, and 21.4% of the variation, respectively. Together, our results suggest that a perfect storm of factors likely influence this lack of resolution, and further indicate that recalcitrant phylogenetic relationships like the backbone of Malpighiales may be better represented as phylogenetic networks. Thus, reducing such groups solely to existing models that adhere strictly to bifurcating trees greatly oversimplifies reality, and obscures our ability to more clearly discern the process of evolution.

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A Multi-objective Metaheuristic Approach for Accurate Species Tree Estimation

2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE) ◽

10.1109/bibe50027.2020.00021 ◽

2020 ◽

Author(s):

Muhammad Ali Nayeem ◽

Md. Shamsuzzoha Bayzid ◽

Sakshar Chakravarty ◽

Mohammad Saifur Rahman ◽

M. Sohel Rahman

Keyword(s):

Species Tree ◽

Multi Objective ◽

Tree Estimation

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TreeMerge: a new method for improving the scalability of species tree estimation methods

Bioinformatics ◽

10.1093/bioinformatics/btz344 ◽

2019 ◽

Vol 35 (14) ◽

pp. i417-i426 ◽

Cited By ~ 7

Author(s):

Erin K Molloy ◽

Tandy Warnow

Keyword(s):

Large Scale ◽

Species Tree ◽

New Method ◽

Divide And Conquer ◽

Supplementary Information ◽

Estimation Methods ◽

Running Time ◽

Tree Estimation ◽

Computationally Intensive ◽

A Minor

Abstract Motivation At RECOMB-CG 2018, we presented NJMerge and showed that it could be used within a divide-and-conquer framework to scale computationally intensive methods for species tree estimation to larger datasets. However, NJMerge has two significant limitations: it can fail to return a tree and, when used within the proposed divide-and-conquer framework, has O(n5) running time for datasets with n species. Results Here we present a new method called ‘TreeMerge’ that improves on NJMerge in two ways: it is guaranteed to return a tree and it has dramatically faster running time within the same divide-and-conquer framework—only O(n2) time. We use a simulation study to evaluate TreeMerge in the context of multi-locus species tree estimation with two leading methods, ASTRAL-III and RAxML. We find that the divide-and-conquer framework using TreeMerge has a minor impact on species tree accuracy, dramatically reduces running time, and enables both ASTRAL-III and RAxML to complete on datasets (that they would otherwise fail on), when given 64 GB of memory and 48 h maximum running time. Thus, TreeMerge is a step toward a larger vision of enabling researchers with limited computational resources to perform large-scale species tree estimation, which we call Phylogenomics for All. Availability and implementation TreeMerge is publicly available on Github (http://github.com/ekmolloy/treemerge). Supplementary information Supplementary data are available at Bioinformatics online.

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Long-Branch Attraction in Species Tree Estimation: Inconsistency of Partitioned Likelihood and Topology-Based Summary Methods

Systematic Biology ◽

10.1093/sysbio/syy061 ◽

2018 ◽

Vol 68 (2) ◽

pp. 281-297 ◽

Cited By ~ 32

Author(s):

Sebastien Roch ◽

Michael Nute ◽

Tandy Warnow

Keyword(s):

Species Tree ◽

Long Branch Attraction ◽

And Topology ◽

Tree Estimation

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FastMulRFS: fast and accurate species tree estimation under generic gene duplication and loss models

Bioinformatics ◽

10.1093/bioinformatics/btaa444 ◽

2020 ◽

Vol 36 (Supplement_1) ◽

pp. i57-i65 ◽

Cited By ~ 3

Author(s):

Erin K Molloy ◽

Tandy Warnow

Keyword(s):

Gene Duplication ◽

Species Tree ◽

Supplementary Information ◽

Biological Research ◽

Generic Model ◽

Species Trees ◽

Basic Part ◽

Gene Duplication And Loss ◽

Tree Estimation ◽

Scalable Methods

Abstract Motivation Species tree estimation is a basic part of biological research but can be challenging because of gene duplication and loss (GDL), which results in genes that can appear more than once in a given genome. All common approaches in phylogenomic studies either reduce available data or are error-prone, and thus, scalable methods that do not discard data and have high accuracy on large heterogeneous datasets are needed. Results We present FastMulRFS, a polynomial-time method for estimating species trees without knowledge of orthology. We prove that FastMulRFS is statistically consistent under a generic model of GDL when adversarial GDL does not occur. Our extensive simulation study shows that FastMulRFS matches the accuracy of MulRF (which tries to solve the same optimization problem) and has better accuracy than prior methods, including ASTRAL-multi (the only method to date that has been proven statistically consistent under GDL), while being much faster than both methods. Availability and impementation FastMulRFS is available on Github (https://github.com/ekmolloy/fastmulrfs). Supplementary information Supplementary data are available at Bioinformatics online.

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