Inferring Pareto-optimal reconciliations across multiple event costs under the duplication-loss-coalescence model

Reconciliation methods are widely used to explain incongruence between a gene tree and species tree. However, the common approach of inferring maximum parsimony reconciliations (MPRs) relies on user-defined costs for each type of event, which can be difficult to estimate. Prior work has explored the...

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Bibliographic Details
Published in:BMC bioinformatics 2019-12, Vol.20 (Suppl 20), p.639-13, Article 639
Main Authors: Mawhorter, Ross, Liu, Nuo, Libeskind-Hadas, Ran, Wu, Yi-Chieh
Format: Article
Language:English
Subjects:
Algorithms
Coalescence
Coalescing
Costs
Evolution
Fungi
Fungi - genetics
Gene Duplication
Gene duplication and loss
Genes
Incomplete lineage sorting
Leaves
Methodology
Models, Genetic
Pareto optimality
Pareto optimum
Phylogenetics
Phylogeny
Reconciliation
Reproduction (copying)
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Summary:Reconciliation methods are widely used to explain incongruence between a gene tree and species tree. However, the common approach of inferring maximum parsimony reconciliations (MPRs) relies on user-defined costs for each type of event, which can be difficult to estimate. Prior work has explored the relationship between event costs and maximum parsimony reconciliations in the duplication-loss and duplication-transfer-loss models, but no studies have addressed this relationship in the more complicated duplication-loss-coalescence model. We provide a fixed-parameter tractable algorithm for computing Pareto-optimal reconciliations and recording all events that arise in those reconciliations, along with their frequencies. We apply this method to a case study of 16 fungi to systematically characterize the complexity of MPR space across event costs and identify events supported across this space. This work provides a new framework for studying the relationship between event costs and reconciliations that incorporates both macro-evolutionary events and population effects and is thus broadly applicable across eukaryotic species.
ISSN:1471-2105
1471-2105
DOI:10.1186/s12859-019-3206-6