Literature DB >> 30094772

Identifying Species Network Features from Gene Tree Quartets Under the Coalescent Model.

Hector Baños1.   

Abstract

We show that many topological features of level-1 species networks are identifiable from the distribution of the gene tree quartets under the network multi-species coalescent model. In particular, every cycle of size at least 4 and every hybrid node in a cycle of size at least 5 are identifiable. This is a step toward justifying the inference of such networks which was recently implemented by Solís-Lemus and Ané. We show additionally how to compute quartet concordance factors for a network in terms of simpler networks, and explore some circumstances in which cycles of size 3 and hybrid nodes in 4-cycles can be detected.

Entities:  

Keywords:  Coalescent theory; Concordance factors; Networks; Phylogenetics

Mesh:

Year:  2018        PMID: 30094772      PMCID: PMC6344282          DOI: 10.1007/s11538-018-0485-4

Source DB:  PubMed          Journal:  Bull Math Biol        ISSN: 0092-8240            Impact factor:   1.758


  24 in total

Review 1.  Hybridization, introgression, and linkage evolution.

Authors:  L H Rieseberg; S J Baird; K A Gardner
Journal:  Plant Mol Biol       Date:  2000-01       Impact factor: 4.076

2.  Hybridization as an invasion of the genome.

Authors:  James Mallet
Journal:  Trends Ecol Evol       Date:  2005-05       Impact factor: 17.712

Review 3.  Speciation genetics: evolving approaches.

Authors:  Mohamed A F Noor; Jeffrey L Feder
Journal:  Nat Rev Genet       Date:  2006-10-03       Impact factor: 53.242

4.  Estimating species phylogeny from gene-tree probabilities despite incomplete lineage sorting: an example from Melanoplus grasshoppers.

Authors:  Bryan C Carstens; L Lacey Knowles
Journal:  Syst Biol       Date:  2007-06       Impact factor: 15.683

5.  Displayed Trees Do Not Determine Distinguishability Under the Network Multispecies Coalescent.

Authors:  Sha Zhu; James H Degnan
Journal:  Syst Biol       Date:  2017-03-01       Impact factor: 15.683

6.  Reconstructing a phylogenetic level-1 network from quartets.

Authors:  J C M Keijsper; R A Pendavingh
Journal:  Bull Math Biol       Date:  2014-09-19       Impact factor: 1.758

7.  A maximum pseudo-likelihood approach for estimating species trees under the coalescent model.

Authors:  Liang Liu; Lili Yu; Scott V Edwards
Journal:  BMC Evol Biol       Date:  2010-10-11       Impact factor: 3.260

8.  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

9.  Inferring Phylogenetic Networks with Maximum Pseudolikelihood under Incomplete Lineage Sorting.

Authors:  Claudia Solís-Lemus; Cécile Ané
Journal:  PLoS Genet       Date:  2016-03-07       Impact factor: 5.917

10.  Quarnet Inference Rules for Level-1 Networks.

Authors:  Katharina T Huber; Vincent Moulton; Charles Semple; Taoyang Wu
Journal:  Bull Math Biol       Date:  2018-06-04       Impact factor: 1.758

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  5 in total

1.  Modeling Hybridization Under the Network Multispecies Coalescent.

Authors:  James H Degnan
Journal:  Syst Biol       Date:  2018-09-01       Impact factor: 15.683

2.  Distinguishing level-1 phylogenetic networks on the basis of data generated by Markov processes.

Authors:  Elizabeth Gross; Leo van Iersel; Remie Janssen; Mark Jones; Colby Long; Yukihiro Murakami
Journal:  J Math Biol       Date:  2021-09-04       Impact factor: 2.259

3.  Identifiability of species network topologies from genomic sequences using the logDet distance.

Authors:  Elizabeth S Allman; Hector Baños; John A Rhodes
Journal:  J Math Biol       Date:  2022-04-07       Impact factor: 2.164

4.  Gene Tree Discord, Simplex Plots, and Statistical Tests under the Coalescent.

Authors:  Elizabeth S Allman; Jonathan D Mitchell; John A Rhodes
Journal:  Syst Biol       Date:  2022-06-16       Impact factor: 9.160

5.  NANUQ: a method for inferring species networks from gene trees under the coalescent model.

Authors:  Elizabeth S Allman; Hector Baños; John A Rhodes
Journal:  Algorithms Mol Biol       Date:  2019-12-06       Impact factor: 1.405

  5 in total

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