scholarly journals wQFM: Statistically Consistent Genome-scale Species Tree Estimation from Weighted Quartets

2020 ◽  
Author(s):  
Mahim Mahbub ◽  
Zahin Wahab ◽  
Rezwana Reaz ◽  
M. Saifur Rahman ◽  
Md. Shamsuzzoha Bayzid

AbstractMotivationSpecies tree estimation from genes sampled from throughout the whole genome is complicated due to the gene tree-species tree discordance. Incomplete lineage sorting (ILS) is one of the most frequent causes for this discordance, where alleles can coexist in populations for periods that may span several speciation events. Quartet-based summary methods for estimating species trees from a collection of gene trees are becoming popular due to their high accuracy and statistical guarantee under ILS. Generating quartets with appropriate weights, where weights correspond to the relative importance of quartets, and subsequently amalgamating the weighted quartets to infer a single coherent species tree allows for a statistically consistent way of estimating species trees. However, handling weighted quartets is challenging.ResultsWe propose wQFM, a highly accurate method for species tree estimation from multi-locus data, by extending the quartet FM (QFM) algorithm to a weighted setting. wQFM was assessed on a collection of simulated and real biological datasets, including the avian phylogenomic dataset which is one of the largest phylogenomic datasets to date. We compared wQFM with wQMC, which is the best alternate method for weighted quartet amalgamation, and with ASTRAL, which is one of the most accurate and widely used coalescent-based species tree estimation methods. Our results suggest that wQFM matches or improves upon the accuracy of wQMC and ASTRAL.AvailabilitywQFM is available in open source form at https://github.com/Mahim1997/wQFM-2020.

2015 ◽  
Author(s):  
Pranjal Vachaspati ◽  
Tandy Warnow

Background: Incomplete lineage sorting (ILS), modelled by the multi-species coalescent (MSC), is known to create discordance between gene trees and species trees, and lead to inaccurate species tree estimations unless appropriate methods are used to estimate the species tree. While many statistically consistent methods have been developed to estimate the species tree in the presence of ILS, only ASTRAL-2 and NJst have been shown to have good accuracy on large datasets. Yet, NJst is generally slower and less accurate than ASTRAL-2, and cannot run on some datasets. Results: We have redesigned NJst to enable it to run on all datasets, and we have expanded its design space so that it can be used with different distance-based tree estimation methods. The resultant method, ASTRID, is statistically consistent under the MSC model, and has accuracy that is competitive with ASTRAL-2. Furthermore, ASTRID is much faster than ASTRAL-2, completing in minutes on some datasets for which ASTRAL-2 used hours. Conclusions: ASTRID is a new coalescent-based method for species tree estimation that is competitive with the best current method in terms of accuracy, while being much faster. ASTRID is available in open source form on github.


2020 ◽  
Author(s):  
Ishrat Tanzila Farah ◽  
Md Muktadirul Islam ◽  
Kazi Tasnim Zinat ◽  
Atif Hasan Rahman ◽  
Md Shamsuzzoha Bayzid

AbstractSpecies tree estimation from multi-locus dataset is extremely challenging, especially in the presence of gene tree heterogeneity across the genome due to incomplete lineage sorting (ILS). Summary methods have been developed which estimate gene trees and then combine the gene trees to estimate a species tree by optimizing various optimization scores. In this study, we have formalized the concept of “phylogenomic terraces” in the species tree space, where multiple species trees with distinct topologies may have exactly the same optimization score (quartet score, extra lineage score, etc.) with respect to a collection of gene trees. We investigated the presence and implication of terraces in species tree estimation from multi-locus data by taking ILS into account. We analyzed two of the most popular ILS-aware optimization criteria: maximize quartet consistency (MQC) and minimize deep coalescence (MDC). Methods based on MQC are provably statistically consistent, whereas MDC is not a consistent criterion for species tree estimation. Our experiments, on a collection of dataset simulated under ILS, indicate that MDC-based methods may achieve competitive or identical quartet consistency score as MQC but could be significantly worse than MQC in terms of tree accuracy – demonstrating the presence and affect of phylogenomic terraces. This is the first known study that formalizes the concept of phylogenomic terraces in the context of species tree estimation from multi-locus data, and reports the presence and implications of terraces in species tree estimation under ILS.


2019 ◽  
Author(s):  
Mazharul Islam ◽  
Kowshika Sarker ◽  
Trisha Das ◽  
Rezwana Reaz ◽  
Md. Shamsuzzoha Bayzid

AbstractBackgroundSpecies tree estimation is frequently based on phylogenomic approaches that use multiple genes from throughout the genome. However, estimating a species tree from a collection of gene trees can be complicated due to the presence of gene tree incongruence resulting from incomplete lineage sorting (ILS), which is modelled by the multi-species coalescent process. Maximum likelihood and Bayesian MCMC methods can potentially result in accurate trees, but they do not scale well to large datasets.ResultsWe present STELAR (Species Tree Estimation by maximizing tripLet AgReement), a new fast and highly accurate statistically consistent coalescent-based method for estimating species trees from a collection of gene trees. We formalized the constrained triplet consensus (CTC) problem and showed that the solution to the CTC problem is a statistically consistent estimate of the species tree under the multi-species coalescent (MSC) model. STELAR is an efficient dynamic programming based solution to the CTC problem which is highly accurate and scalable. We evaluated the accuracy of STELAR in comparison with SuperTriplets, which is an alternate fast and highly accurate triplet-based supertree method, and with MP-EST and ASTRAL – two of the most popular and accurate coalescent-based methods. Experimental results suggest that STELAR matches the accuracy of ASTRAL and improves on MP-EST and SuperTriplets.ConclusionsTheoretical and empirical results (on both simulated and real biological datasets) suggest that STELAR is a valuable technique for species tree estimation from gene tree distributions.


2015 ◽  
Author(s):  
Ruth Davidson ◽  
Pranjal Vachaspati ◽  
Siavash Mirarab ◽  
Tandy Warnow

Background: Species tree estimation is challenged by gene tree heterogeneity resulting from biological processes such as duplication and loss, hybridization, incomplete lineage sorting (ILS), and horizontal gene transfer (HGT). Mathematical theory about reconstructing species trees in the presence of HGT alone or ILS alone suggests that quartet-based species tree methods (known to be statistically consistent under ILS, or under bounded amounts of HGT) might be effective techniques for estimating species trees when both HGT and ILS are present. Results: We evaluated several publicly available coalescent-based methods and concatenation under maximum likelihood on simulated datasets with moderate ILS and varying levels of HGT. Our study shows that two quartet-based species tree estimation methods (ASTRAL-2 and weighted Quartets MaxCut) are both highly accurate, even on datasets with high rates of HGT. In contrast, although NJst and concatenation using maximum likelihood are highly accurate under low HGT, they are less robust to high HGT rates. Conclusion: Our study shows that quartet-based species-tree estimation methods can be highly accurate under the presence of both HGT and ILS. The study suggests the possibility that some quartet-based methods might be statistically consistent under phylogenomic models of gene tree heterogeneity with both HGT and ILS. Keywords: phylogenomics; HGT; ILS; summary methods; concatenation


2017 ◽  
Author(s):  
Fábio K. Mendes ◽  
Matthew W. Hahn

AbstrctGenome-scale sequencing has been of great benefit in recovering species trees, but has not provided final answers. Despite the rapid accumulation of molecular sequences, resolving short and deep branches of the tree of life has remained a challenge, and has prompted the development of new strategies that can make the best use of available data. One such strategy – the concatenation of gene alignments – can be successful when coupled with many tree estimation methods, but has also been shown to fail when there are high levels of incomplete lineage sorting. Here, we focus on the failure of likelihood-based methods in retrieving a rooted, asymmetric four-taxon species tree from concatenated data when the species tree is in or near the anomaly zone – a region of parameter space where the most common gene tree does not match the species tree because of incomplete lineage sorting. First, we use coalescent theory to prove that most informative sites will support the species tree in the anomaly zone, and that as a consequence maximum-parsimony succeeds in recovering the species tree from concatenated data. We further show that maximum-likelihood tree estimation from concatenated data fails both inside and outside the anomaly zone, and that this failure is unconnected to the frequency of the most common gene tree. We provide support for a hypothesis that likelihood-based methods fail in and near the anomaly zone because discordant sites on the species tree have a lower likelihood than those that are discordant on alternative topologies. Our results confirm and extend previous reports of the failure and success of likelihood- and parsimony-based methods, and highlight avenues for future work improving the performance of methods aimed at recovering species tree.


2020 ◽  
Author(s):  
Liming Cai ◽  
Zhenxiang Xi ◽  
Emily Moriarty Lemmon ◽  
Alan R Lemmon ◽  
Austin Mast ◽  
...  

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.


2022 ◽  
Vol 12 ◽  
Author(s):  
Martha Kandziora ◽  
Petr Sklenář ◽  
Filip Kolář ◽  
Roswitha Schmickl

A major challenge in phylogenetics and -genomics is to resolve young rapidly radiating groups. The fast succession of species increases the probability of incomplete lineage sorting (ILS), and different topologies of the gene trees are expected, leading to gene tree discordance, i.e., not all gene trees represent the species tree. Phylogenetic discordance is common in phylogenomic datasets, and apart from ILS, additional sources include hybridization, whole-genome duplication, and methodological artifacts. Despite a high degree of gene tree discordance, species trees are often well supported and the sources of discordance are not further addressed in phylogenomic studies, which can eventually lead to incorrect phylogenetic hypotheses, especially in rapidly radiating groups. We chose the high-Andean Asteraceae genus Loricaria to shed light on the potential sources of phylogenetic discordance and generated a phylogenetic hypothesis. By accounting for paralogy during gene tree inference, we generated a species tree based on hundreds of nuclear loci, using Hyb-Seq, and a plastome phylogeny obtained from off-target reads during target enrichment. We observed a high degree of gene tree discordance, which we found implausible at first sight, because the genus did not show evidence of hybridization in previous studies. We used various phylogenomic analyses (trees and networks) as well as the D-statistics to test for ILS and hybridization, which we developed into a workflow on how to tackle phylogenetic discordance in recent radiations. We found strong evidence for ILS and hybridization within the genus Loricaria. Low genetic differentiation was evident between species located in different Andean cordilleras, which could be indicative of substantial introgression between populations, promoted during Pleistocene glaciations, when alpine habitats shifted creating opportunities for secondary contact and hybridization.


2020 ◽  
Author(s):  
Michael J. Sanderson ◽  
Michelle M. McMahon ◽  
Mike Steel

AbstractTerraces in phylogenetic tree space are sets of trees with identical optimality scores for a given data set, arising from missing data. These were first described for multilocus phylogenetic data sets in the context of maximum parsimony inference and maximum likelihood inference under certain model assumptions. Here we show how the mathematical properties that lead to terraces extend to gene tree - species tree problems in which the gene trees are incomplete. Inference of species trees from either sets of gene family trees subject to duplication and loss, or allele trees subject to incomplete lineage sorting, can exhibit terraces in their solution space. First, we show conditions that lead to a new kind of terrace, which stems from subtree operations that appear in reconciliation problems for incomplete trees. Then we characterize when terraces of both types can occur when the optimality criterion for tree search is based on duplication, loss or deep coalescence scores. Finally, we examine the impact of assumptions about the causes of losses: whether they are due to imperfect sampling or true evolutionary deletion.


2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Guilherme Rezende Dias ◽  
Eduardo Guimarães Dupim ◽  
Thyago Vanderlinde ◽  
Beatriz Mello ◽  
Antonio Bernardo Carvalho

Abstract Background The Drosophilidae family is traditionally divided into two subfamilies: Drosophilinae and Steganinae. This division is based on morphological characters, and the two subfamilies have been treated as monophyletic in most of the literature, but some molecular phylogenies have suggested Steganinae to be paraphyletic. To test the paraphyletic-Steganinae hypothesis, here, we used genomic sequences of eight Drosophilidae (three Steganinae and five Drosophilinae) and two Ephydridae (outgroup) species and inferred the phylogeny for the group based on a dataset of 1,028 orthologous genes present in all species (> 1,000,000 bp). This dataset includes three genera that broke the monophyly of the subfamilies in previous works. To investigate possible biases introduced by small sample sizes and automatic gene annotation, we used the same methods to infer species trees from a set of 10 manually annotated genes that are commonly used in phylogenetics. Results Most of the 1,028 gene trees depicted Steganinae as paraphyletic with distinct topologies, but the most common topology depicted it as monophyletic (43.7% of the gene trees). Despite the high levels of gene tree heterogeneity observed, species tree inference in ASTRAL, in PhyloNet, and with the concatenation approach strongly supported the monophyly of both subfamilies for the 1,028-gene dataset. However, when using the concatenation approach to infer a species tree from the smaller set of 10 genes, we recovered Steganinae as a paraphyletic group. The pattern of gene tree heterogeneity was asymmetrical and thus could not be explained solely by incomplete lineage sorting (ILS). Conclusions Steganinae was clearly a monophyletic group in the dataset that we analyzed. In addition to ILS, gene tree discordance was possibly the result of introgression, suggesting complex branching processes during the early evolution of Drosophilidae with short speciation intervals and gene flow. Our study highlights the importance of genomic data in elucidating contentious phylogenetic relationships and suggests that phylogenetic inference for drosophilids based on small molecular datasets should be performed cautiously. Finally, we suggest an approach for the correction and cleaning of BUSCO-derived genomic datasets that will be useful to other researchers planning to use this tool for phylogenomic studies.


2017 ◽  
Author(s):  
Erin K. Molloy ◽  
Tandy Warnow

AbstractSpecies tree estimation from loci sampled from multiple genomes is now common, but is challenged by the heterogeneity across the genome due to multiple processes, such as gene duplication and loss, horizontal gene transfer, and incomplete lineage sorting. Although methods for estimating species trees have been developed that address gene tree heterogeneity due to incomplete lineage sorting, many of these methods operate by combining estimated gene trees and are hence vulnerable to gene tree quality. There is also the added concern that missing data, which is frequently encountered in genome-scale datasets, will impact species tree estimation.Our study addresses the impact of gene filtering on species trees inferred from multi-gene datasets. We address these questions using a large and heterogeneous collection of simulated datasets both with and without missing data. We compare several established coalescent-based methods (ASTRAL, ASTRID, MP-EST, and SVDquartets within PAUP*) as well as unpartitioned concatenation using maximum likelihood (RAxML).Our study shows that gene tree error and missing data impact all methods (and some methods degrade more than others), but the degree of incomplete lineage sorting and gene tree estimation error impacts the absolute and relative performance of methods as well as their response to gene filtering strategies. We find that filtering genes based on the degree of missing data is either neutral or else reduces the accuracy of all five methods examined, and so is not recommended. Filtering genes based on gene tree estimation error shows somewhat different trends. Under low levels of incomplete lineage sorting, removing genes with high gene tree estimation error can improve the accuracy of summary methods, but only if not too many genes are removed. Otherwise, filtering genes tends to increase error, especially under high levels of incomplete lineage sorting. Hence, while filtering genes based on missing data is not recommended, there are conditions under which removing high error gene trees can improve species tree estimation. This study provides insights into prior studies and suggests approaches for analyzing phylogenomic datasets.


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