Polymorphism-aware estimation of species trees and evolutionary forces from genomic sequences with RevBayes

The availability of population genomic data through new sequencing technologies gives unprecedented opportunities for estimating important evolutionary forces such as genetic drift, selection, and mutation biases across organisms. Yet, analytical methods that can handle polymorphisms jointly with sequence divergence across species are rare and not easily accessible to empiricists. We implemented polymorphism-aware phylogenetic models (PoMos), an alternative approach for species tree estimation, in the Bayesian phylogenetic software RevBayes. PoMos naturally account for incomplete lineage sorting, which is known to cause difficulties for phylogenetic inference in species radiations, and scale well with genome-wide data. Simultaneously, PoMos can estimate mutation and selection biases. We have applied our methods to resolve the complex phylogenetic relationships of a young radiation of Chorthippus grasshoppers, based on coding sequences. In addition to establishing a well-supported species tree, we found a mutation bias favoring AT alleles and selection bias promoting the fixation of GC alleles, the latter consistent with GC-biased gene conversion. The selection bias is two orders of magnitude lower than genetic drift, validating the critical role of nearly neutral evolutionary processes in species radiation. PoMos offer a wide range of models to reconstruct phylogenies and can be easily combined with existing models in RevBayes - e.g., relaxed clock and divergence time estimation - offering new insights into the evolutionary processes underlying molecular evolution and, ultimately, species diversification.

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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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How to Tackle Phylogenetic Discordance in Recent and Rapidly Radiating Groups? Developing a Workflow Using Loricaria (Asteraceae) as an Example

Frontiers in Plant Science ◽

10.3389/fpls.2021.765719 ◽

2022 ◽

Vol 12 ◽

Author(s):

Martha Kandziora ◽

Petr Sklenář ◽

Filip Kolář ◽

Roswitha Schmickl

Keyword(s):

Incomplete Lineage Sorting ◽

Gene Tree ◽

Species Tree ◽

Secondary Contact ◽

Gene Trees ◽

Species Trees ◽

Lineage Sorting ◽

Phylogenetic Discordance ◽

Gene Tree Discordance ◽

High Degree

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.

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MSCquartets 1.0: Quartet methods for species trees and networks under the multispecies coalescent model in R

Bioinformatics ◽

10.1093/bioinformatics/btaa868 ◽

2020 ◽

Author(s):

John A Rhodes ◽

Hector Baños ◽

Jonathan D Mitchell ◽

Elizabeth S Allman

Keyword(s):

Network Inference ◽

Incomplete Lineage Sorting ◽

R Package ◽

Species Tree ◽

Supplementary Information ◽

Species Trees ◽

Lineage Sorting ◽

Coalescent Model ◽

Multispecies Coalescent ◽

Tree Inference

Abstract Summary MSCquartets is an R package for species tree hypothesis testing, inference of species trees, and inference of species networks under the Multispecies Coalescent model of incomplete lineage sorting and its network analog. Input for these analyses are collections of metric or topological locus trees which are then summarized by the quartets displayed on them. Results of hypothesis tests at user-supplied levels are displayed in a simplex plot by color-coded points. The package implements the QDC and WQDC algorithms for topological and metric species tree inference, and the NANUQ algorithm for level-1 topological species network inference, all of which give statistically consistent estimators under the model. Availability MSCquartets is available through the Comprehensive R Archive Network: https://CRAN.R-project.org/package=MSCquartets. Supplementary information Supplementary materials, including example data and analyses, are incorporated into the package.

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Disentangling Sources of Gene Tree Discordance in Phylogenomic Data Sets: Testing Ancient Hybridizations in Amaranthaceae s.l

Systematic Biology ◽

10.1093/sysbio/syaa066 ◽

2020 ◽

Cited By ~ 1

Author(s):

Diego F Morales-Briones ◽

Gudrun Kadereit ◽

Delphine T Tefarikis ◽

Michael J Moore ◽

Stephen A Smith ◽

...

Keyword(s):

Network Inference ◽

Incomplete Lineage Sorting ◽

Gene Tree ◽

Phylogenetic Network ◽

Species Tree ◽

Data Sets ◽

Species Trees ◽

Lineage Sorting ◽

Data Set ◽

Gene Tree Discordance

Abstract Gene tree discordance in large genomic data sets can be caused by evolutionary processes such as incomplete lineage sorting and hybridization, as well as model violation, and errors in data processing, orthology inference, and gene tree estimation. Species tree methods that identify and accommodate all sources of conflict are not available, but a combination of multiple approaches can help tease apart alternative sources of conflict. Here, using a phylotranscriptomic analysis in combination with reference genomes, we test a hypothesis of ancient hybridization events within the plant family Amaranthaceae s.l. that was previously supported by morphological, ecological, and Sanger-based molecular data. The data set included seven genomes and 88 transcriptomes, 17 generated for this study. We examined gene-tree discordance using coalescent-based species trees and network inference, gene tree discordance analyses, site pattern tests of introgression, topology tests, synteny analyses, and simulations. We found that a combination of processes might have generated the high levels of gene tree discordance in the backbone of Amaranthaceae s.l. Furthermore, we found evidence that three consecutive short internal branches produce anomalous trees contributing to the discordance. Overall, our results suggest that Amaranthaceae s.l. might be a product of an ancient and rapid lineage diversification, and remains, and probably will remain, unresolved. This work highlights the potential problems of identifiability associated with the sources of gene tree discordance including, in particular, phylogenetic network methods. Our results also demonstrate the importance of thoroughly testing for multiple sources of conflict in phylogenomic analyses, especially in the context of ancient, rapid radiations. We provide several recommendations for exploring conflicting signals in such situations. [Amaranthaceae; gene tree discordance; hybridization; incomplete lineage sorting; phylogenomics; species network; species tree; transcriptomics.]

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Terraces in Gene Tree Reconciliation-Based Species Tree Inference

10.1101/2020.04.17.047092 ◽

2020 ◽

Author(s):

Michael J. Sanderson ◽

Michelle M. McMahon ◽

Mike Steel

Keyword(s):

Incomplete Lineage Sorting ◽

Gene Tree ◽

Solution Space ◽

Species Tree ◽

Gene Trees ◽

Species Trees ◽

Lineage Sorting ◽

Data Set ◽

Tree Reconciliation ◽

The Impact

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.

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Phylogenomic terraces: presence and implication in species tree estimation from gene trees

10.1101/2020.04.19.048843 ◽

2020 ◽

Author(s):

Ishrat Tanzila Farah ◽

Md Muktadirul Islam ◽

Kazi Tasnim Zinat ◽

Atif Hasan Rahman ◽

Md Shamsuzzoha Bayzid

Keyword(s):

Incomplete Lineage Sorting ◽

Gene Tree ◽

Species Tree ◽

Gene Trees ◽

Species Trees ◽

Lineage Sorting ◽

Deep Coalescence ◽

Tree Estimation ◽

Tree Space ◽

Multiple Species

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.

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A phylogenomic study of Steganinae fruit flies (Diptera: Drosophilidae): strong gene tree heterogeneity and evidence for monophyly

BMC Evolutionary Biology ◽

10.1186/s12862-020-01703-7 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Guilherme Rezende Dias ◽

Eduardo Guimarães Dupim ◽

Thyago Vanderlinde ◽

Beatriz Mello ◽

Antonio Bernardo Carvalho

Keyword(s):

Gene Annotation ◽

Incomplete Lineage Sorting ◽

Branching Processes ◽

Gene Tree ◽

Morphological Characters ◽

Species Tree ◽

Small Sample ◽

Gene Trees ◽

Species Trees ◽

Lineage Sorting

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.

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To include or not to include: The impact of gene filtering on species tree estimation methods

10.1101/149120 ◽

2017 ◽

Cited By ~ 1

Author(s):

Erin K. Molloy ◽

Tandy Warnow

Keyword(s):

Missing Data ◽

Incomplete Lineage Sorting ◽

Estimation Error ◽

Gene Tree ◽

Species Tree ◽

Species Trees ◽

Lineage Sorting ◽

Gene Filtering ◽

Tree Estimation ◽

The Impact

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

10.1101/2020.11.30.403352 ◽

2020 ◽

Author(s):

Mahim Mahbub ◽

Zahin Wahab ◽

Rezwana Reaz ◽

M. Saifur Rahman ◽

Md. Shamsuzzoha Bayzid

Keyword(s):

Incomplete Lineage Sorting ◽

Gene Tree ◽

Accurate Method ◽

Species Tree ◽

Estimation Methods ◽

Gene Trees ◽

Species Trees ◽

Lineage Sorting ◽

Tree Estimation ◽

Source Form

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.

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