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Model-based detection of whole-genome duplications in a phylogeny

Arthur Zwaenepoel (UGent) and Yves Van de Peer (UGent)
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Abstract
Ancient whole-genome duplications (WGDs) leave signatures in comparative genomic data sets that can be harnessed to detect these events of presumed evolutionary importance. Current statistical approaches for the detection of ancient WGDs in a phylogenetic context have two main drawbacks. The first is that unwarranted restrictive assumptions on the ‘background’ gene duplication and loss rates make inferences unreliable in the face of model violations. The second is that most methods can only be used to examine a limited set of a priori selected WGD hypotheses; and cannot be used to discover WGDs in a phylogeny. In this study we develop an approach for WGD inference using gene count data that seeks to overcome both issues. We employ a phylogenetic birth-death model that includes WGD in a flexible hierarchical Bayesian approach, and use reversible-jump MCMC to perform Bayesian inference of branch-specific duplication, loss and WGD retention rates accross the space of WGD configurations. We evaluate the proposed method using simulations, apply it to data sets from flowering plants and discuss the statistical intricacies of model-based WGD inference.
Keywords
Genetics, Ecology, Evolution, Behavior and Systematics, Molecular Biology

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Please use this url to cite or link to this publication:

MLA
Zwaenepoel, Arthur, and Yves Van de Peer. “Model-Based Detection of Whole-Genome Duplications in a Phylogeny.” MOLECULAR BIOLOGY AND EVOLUTION, edited by Jianzhi Zhang, 2020.
APA
Zwaenepoel, A., & Van de Peer, Y. (2020). Model-based detection of whole-genome duplications in a phylogeny. MOLECULAR BIOLOGY AND EVOLUTION.
Chicago author-date
Zwaenepoel, Arthur, and Yves Van de Peer. 2020. “Model-Based Detection of Whole-Genome Duplications in a Phylogeny.” Edited by Jianzhi Zhang. MOLECULAR BIOLOGY AND EVOLUTION.
Chicago author-date (all authors)
Zwaenepoel, Arthur, and Yves Van de Peer. 2020. “Model-Based Detection of Whole-Genome Duplications in a Phylogeny.” Ed by. Jianzhi Zhang. MOLECULAR BIOLOGY AND EVOLUTION.
Vancouver
1.
Zwaenepoel A, Van de Peer Y. Model-based detection of whole-genome duplications in a phylogeny. Zhang J, editor. MOLECULAR BIOLOGY AND EVOLUTION. 2020;
IEEE
[1]
A. Zwaenepoel and Y. Van de Peer, “Model-based detection of whole-genome duplications in a phylogeny,” MOLECULAR BIOLOGY AND EVOLUTION, 2020.
@article{8660636,
  abstract     = {Ancient whole-genome duplications (WGDs) leave signatures in comparative genomic data sets that can be harnessed to detect these events of presumed evolutionary importance. Current statistical approaches for the detection of ancient WGDs in a phylogenetic context have two main drawbacks. The first is that unwarranted restrictive assumptions on the ‘background’ gene duplication and loss rates make inferences unreliable in the face of model violations. The second is that most methods can only be used to examine a limited set of a priori selected WGD hypotheses; and cannot be used to discover WGDs in a phylogeny. In this study we develop an approach for WGD inference using gene count data that seeks to overcome both issues. We employ a phylogenetic birth-death model that includes WGD in a flexible hierarchical Bayesian approach, and use reversible-jump MCMC to perform Bayesian inference of branch-specific duplication, loss and WGD retention rates accross the space of WGD configurations. We evaluate the proposed method using simulations, apply it to data sets from flowering plants and discuss the statistical intricacies of model-based WGD inference.},
  author       = {Zwaenepoel, Arthur and Van de Peer, Yves},
  editor       = {Zhang, Jianzhi},
  issn         = {0737-4038},
  journal      = {MOLECULAR BIOLOGY AND EVOLUTION},
  keywords     = {Genetics,Ecology,Evolution,Behavior and Systematics,Molecular Biology},
  language     = {eng},
  title        = {Model-based detection of whole-genome duplications in a phylogeny},
  url          = {http://dx.doi.org/10.1093/molbev/msaa111},
  year         = {2020},
}

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