Literature DB >> 31860090

Probabilities of Unranked and Ranked Anomaly Zones under Birth-Death Models.

Anastasiia Kim1, Noah A Rosenberg2, James H Degnan1.   

Abstract

A labeled gene tree topology that is more probable than the labeled gene tree topology matching a species tree is called "anomalous." Species trees that can generate such anomalous gene trees are said to be in the "anomaly zone." Here, probabilities of "unranked" and "ranked" gene tree topologies under the multispecies coalescent are considered. A ranked tree depicts not only the topological relationship among gene lineages, as an unranked tree does, but also the sequence in which the lineages coalesce. In this article, we study how the parameters of a species tree simulated under a constant-rate birth-death process can affect the probability that the species tree lies in the anomaly zone. We find that with more than five taxa, it is possible for species trees to have both anomalous unranked and ranked gene trees. The probability of being in either type of anomaly zone increases with more taxa. The probability of anomalous gene trees also increases with higher speciation rates. We observe that the probabilities of unranked anomaly zones are higher and grow much faster than those of ranked anomaly zones as the speciation rate increases. Our simulation shows that the most probable ranked gene tree is likely to have the same unranked topology as the species tree. We design the software PRANC, which computes probabilities of ranked gene tree topologies given a species tree under the coalescent model.
© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  anomalous gene tree; coalescent; gene tree; phylogeny; species tree

Mesh:

Year:  2020        PMID: 31860090      PMCID: PMC7182218          DOI: 10.1093/molbev/msz305

Source DB:  PubMed          Journal:  Mol Biol Evol        ISSN: 0737-4038            Impact factor:   16.240


  29 in total

1.  The probability of topological concordance of gene trees and species trees.

Authors:  Noah A Rosenberg
Journal:  Theor Popul Biol       Date:  2002-03       Impact factor: 1.570

2.  Distribution of branch lengths and phylogenetic diversity under homogeneous speciation models.

Authors:  Tanja Stadler; Mike Steel
Journal:  J Theor Biol       Date:  2011-12-01       Impact factor: 2.691

3.  Coalescent-based species tree inference from gene tree topologies under incomplete lineage sorting by maximum likelihood.

Authors:  Yufeng Wu
Journal:  Evolution       Date:  2011-11-02       Impact factor: 3.694

4.  There are no caterpillars in a wicked forest.

Authors:  James H Degnan; John A Rhodes
Journal:  Theor Popul Biol       Date:  2015-09-10       Impact factor: 1.570

5.  Gene tree distributions under the coalescent process.

Authors:  James H Degnan; Laura A Salter
Journal:  Evolution       Date:  2005-01       Impact factor: 3.694

6.  Simulating trees with a fixed number of extant species.

Authors:  Tanja Stadler
Journal:  Syst Biol       Date:  2011-04-11       Impact factor: 15.683

Review 7.  Challenges in Species Tree Estimation Under the Multispecies Coalescent Model.

Authors:  Bo Xu; Ziheng Yang
Journal:  Genetics       Date:  2016-12       Impact factor: 4.562

8.  Anomalous unrooted gene trees.

Authors:  James H Degnan
Journal:  Syst Biol       Date:  2013-04-10       Impact factor: 15.683

9.  A polynomial time algorithm for calculating the probability of a ranked gene tree given a species tree.

Authors:  Tanja Stadler; James H Degnan
Journal:  Algorithms Mol Biol       Date:  2012-04-30       Impact factor: 1.405

10.  In the light of deep coalescence: revisiting trees within networks.

Authors:  Jiafan Zhu; Yun Yu; Luay Nakhleh
Journal:  BMC Bioinformatics       Date:  2016-11-11       Impact factor: 3.169

View more
  1 in total

1.  PRANC: ML species tree estimation from the ranked gene trees under coalescence.

Authors:  Anastasiia Kim; James H Degnan
Journal:  Bioinformatics       Date:  2020-09-15       Impact factor: 6.937

  1 in total

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