Impact of gene family evolutionary histories on phylogenetic species tree inference by gene tree parsimony

2016 ◽  
Vol 96 ◽  
pp. 9-16 ◽  
Author(s):  
Tao Shi
Keyword(s):  
Gene Family ◽  
Gene Tree ◽  
Species Tree ◽  
Phylogenetic Species ◽  
Tree Inference ◽  
Species Tree Inference

scholarly journals DISCO: Species Tree Inference using Multicopy Gene Family Tree Decomposition

2021 ◽  
Author(s):  
James Willson ◽  
Mrinmoy Saha Roddur ◽  
Baqiao Liu ◽  
Paul Zaharias ◽  
Tandy Warnow
Keyword(s):  
Gene Duplication ◽  
Gene Family ◽  
Gene Tree ◽  
Single Copy ◽  
Species Tree ◽  
Family Tree ◽  
Tree Inference ◽  
Gene Duplication And Loss ◽  
Species Tree Inference ◽  
Family Trees

Abstract Species tree inference from gene family trees is a significant problem in computational biology. However, gene tree heterogeneity, which can be caused by several factors including gene duplication and loss, makes the estimation of species trees very challenging. While there have been several species tree estimation methods introduced in recent years to specifically address gene tree heterogeneity due to gene duplication and loss (such as DupTree, FastMulRFS, ASTRAL-Pro, and SpeciesRax), many incur high cost in terms of both running time and memory. We introduce a new approach, DISCO, that decomposes the multi-copy gene family trees into many single copy trees, which allows for methods previously designed for species tree inference in a single copy gene tree context to be used. We prove that using DISCO with ASTRAL (i.e., ASTRAL-DISCO) is statistically consistent under the GDL model, provided that ASTRAL-Pro correctly roots and tags each gene family tree. We evaluate DISCO paired with different methods for estimating species trees from single copy genes (e.g., ASTRAL, ASTRID, and IQ-TREE) under a wide range of model conditions, and establish that high accuracy can be obtained even when ASTRAL-Pro is not able to correctly roots and tags the gene family trees. We also compare results using MI, an alternative decomposition strategy from Yang Y. and Smith S.A. (2014), and find that DISCO provides better accuracy, most likely as a result of covering more of the gene family tree leafset in the output decomposition. [Concatenation analysis; gene duplication and loss; species tree inference; summary method.]

scholarly journals SpeciesRax: A tool for maximum likelihood species tree inference from gene family trees under duplication, transfer, and loss.

2021 ◽  
Author(s):  
Benoit Morel ◽  
Paul Schade ◽  
Sarah Lutteropp ◽  
Tom A. Williams ◽  
Gergely J. Szöllösi ◽  
...  
Keyword(s):  
Maximum Likelihood ◽  
Gene Family ◽  
Gene Families ◽  
Species Tree ◽  
Likelihood Method ◽  
Gene Trees ◽  
Informative Signal ◽  
Tree Inference ◽  
Species Tree Inference ◽  
Family Trees

Species tree inference from gene family trees is becoming increasingly popular because it can account for discordance between the species tree and the corresponding gene family trees. In particular, methods that can account for multiple-copy gene families exhibit potential to leverage paralogy as informative signal. At present, there does not exist any widely adopted inference method for this purpose. Here, we present SpeciesRax, the first maximum likelihood method that can infer a rooted species tree from a set of gene family trees and can account for gene duplication, loss, and transfer events. By explicitly modelling events by which gene trees can depart from the species tree, SpeciesRax leverages the phylogenetic rooting signal in gene trees. SpeciesRax infers species tree branch lengths in units of expected substitutions per site and branch support values via paralogy-aware quartets extracted from the gene family trees. Using both empirical and simulated datasets we show that SpeciesRax is at least as accurate as the best competing methods while being one order of magnitude faster on large datasets at the same time. We used SpeciesRax to infer a biologically plausible rooted phylogeny of the vertebrates comprising $188$ species from $31612$ gene families in one hour using $40$ cores. SpeciesRax is available under GNU GPL at https://github.com/BenoitMorel/GeneRax and on BioConda.

scholarly journals Gene tree correction for reconciliation and species tree inference: Complexity and algorithms

2014 ◽  
Vol 25 ◽  
pp. 51-65 ◽  
Author(s):  
Riccardo Dondi ◽  
Nadia El-Mabrouk ◽  
Krister M. Swenson
Keyword(s):  
Gene Tree ◽  
Species Tree ◽  
Tree Inference ◽  
Species Tree Inference

scholarly journals Phylogenetic conflicts, combinability, and deep phylogenomics in plants

2018 ◽  
Author(s):  
Stephen A. Smith ◽  
Nathanael Walker-Hale ◽  
Joseph F. Walker ◽  
Joseph W. Brown
Keyword(s):  
Phylogenetic Relationships ◽  
Phylogenetic Signal ◽  
Gene Tree ◽  
Species Tree ◽  
Gene Trees ◽  
Data Filtering ◽  
Tree Inference ◽  
Tree Methods ◽  
Inference Methods ◽  
Species Tree Inference

AbstractStudies have demonstrated that pervasive gene tree conflict underlies several important phylogenetic relationships where different species tree methods produce conflicting results. Here, we present a means of dissecting the phylogenetic signal for alternative resolutions within a dataset in order to resolve recalcitrant relationships and, importantly, identify what the dataset is unable to resolve. These procedures extend upon methods for isolating conflict and concordance involving specific candidate relationships and can be used to identify systematic error and disambiguate sources of conflict among species tree inference methods. We demonstrate these on a large phylogenomic plant dataset. Our results support the placement of Amborella as sister to the remaining extant angiosperms, Gnetales as sister to pines, and the monophyly of extant gymnosperms. Several other contentious relationships, including the resolution of relationships within the bryophytes and the eudicots, remain uncertain given the low number of supporting gene trees. To address whether concatenation of filtered genes amplified phylogenetic signal for relationships, we implemented a combinatorial heuristic to test combinability of genes. We found that nested conflicts limited the ability of data filtering methods to fully ameliorate conflicting signal amongst gene trees. These analyses confirmed that the underlying conflicting signal does not support broad concatenation of genes. Our approach provides a means of dissecting a specific dataset to address deep phylogenetic relationships while also identifying the inferential boundaries of the dataset.

scholarly journals Gene tree correction for reconciliation and species tree inference

2012 ◽  
Vol 7 (1) ◽  
Author(s):  
Krister M Swenson ◽  
Andrea Doroftei ◽  
Nadia El-Mabrouk
Keyword(s):  
Gene Tree ◽  
Species Tree ◽  
Tree Inference ◽  
Species Tree Inference

scholarly journals Accounting for Uncertainty in Gene Tree Estimation: Summary-Coalescent Species Tree Inference in a Challenging Radiation of Australian Lizards

2016 ◽  
Author(s):  
Mozes P.K. Blom ◽  
Jason G. Bragg ◽  
Sally Potter ◽  
Craig Moritz
Keyword(s):  
Phylogenetic Signal ◽  
Gene Tree ◽  
Phylogenetic Inference ◽  
Species Tree ◽  
Gene Trees ◽  
Tree Inference ◽  
Tree Estimation ◽  
Tree Resolution ◽  
The Impact ◽  
Species Tree Inference

AbstractAccurate gene tree inference is an important aspect of species tree estimation in a summary-coalescent framework. Yet, in empirical studies, inferred gene trees differ in accuracy due to stochastic variation in phylogenetic signal between targeted loci. Empiricists should therefore examine the consistency of species tree inference, while accounting for the observed heterogeneity in gene tree resolution of phylogenomic datasets. Here, we assess the impact of gene tree estimation error on summary-coalescent species tree inference by screening ~2000 exonic loci based on gene tree resolution prior to phylogenetic inference. We focus on a phylogenetically challenging radiation of Australian lizards (genus Cryptoblepharus, Scincidae) and explore effects on topology and support. We identify a well-supported topology based on all loci and find that a relatively small number of high-resolution gene trees can be sufficient to converge on the same topology. Adding gene trees with decreasing resolution produced a generally consistent topology, and increased confidence for specific bipartitions that were poorly supported when using a small number of informative loci. This corroborates coalescent-based simulation studies that have highlighted the need for a large number of loci to confidently resolve challenging relationships and refutes the notion that low-resolution gene trees introduce phylogenetic noise. Further, our study also highlights the value of quantifying changes in nodal support across locus subsets of increasing size (but decreasing gene tree resolution). Such detailed analyses can reveal anomalous fluctuations in support at some nodes, suggesting the possibility of model violation. By characterizing the heterogeneity in phylogenetic signal among loci, we can account for uncertainty in gene tree estimation and assess its effect on the consistency of the species tree estimate. We suggest that the evaluation of gene tree resolution should be incorporated in the analysis of empirical phylogenomic datasets. This will ultimately increase our confidence in species tree estimation using summary-coalescent methods and enable us to exploit genomic data for phylogenetic inference.

scholarly journals Evolutionary patterns of 64 vertebrate genomes (species) revealed by phylogenomics analysis of protein-coding gene families

2020 ◽  
Author(s):  
Jia Song ◽  
Xia Han ◽  
Kui Lin
Keyword(s):  
Gene Family ◽  
Gene Families ◽  
Species Tree ◽  
Whole Genome ◽  
Species Trees ◽  
High Concentration ◽  
Evolutionary Mechanisms ◽  
Study Results ◽  
Tree Inference ◽  
Species Tree Inference

AbstractBackgroundRecent studies have demonstrated that phylogenomics is an important basis for answering many fundamental evolutionary questions. With more high-quality whole genome sequences published, more efficient phylogenomics analysis workflows are required urgently.ResultsTo this end and in order to capture putative differences among evolutionary histories of gene families and species, we developed a phylogenomics workflow for gene family classification, gene family tree inference, species tree inference and duplication/loss events dating. Our analysis framework is on the basis of two guiding ideas: 1) gene trees tend to be different from species trees but they influence each other in evolution; 2) different gene families have undergone different evolutionary mechanisms. It has been applied to the genomic data from 64 vertebrates and 5 out-group species. And the results showed high accuracy on species tree inference and few false-positives in duplication events dating.ConclusionsBased on the inferred gene duplication and loss event, only 9∼16% gene families have duplication retention after a whole genome duplication (WGD) event. A large part of these families have ohnologs from two or three WGDs. Consistent with the previous study results, the gene function of these families are mainly involved in nervous system and signal transduction related biological processes. Specifically, we found that the gene families with ohnologs from the teleost-specific (TS) WGD are enriched in fat metabolism, this result implyng that the retention of such ohnologs might be associated with the environmental status of high concentration of oxygen during that period.

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