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

Abstract Background 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 w...

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Main Authors: Ross Mawhorter, Nuo Liu, Ran Libeskind-Hadas, Yi-Chieh Wu
Format: Article
Language:English
Published: BMC 2019-12-01
Series:BMC Bioinformatics
Subjects:
Online Access:https://doi.org/10.1186/s12859-019-3206-6
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spelling doaj-6b7ef9cdaacb487eaa1a56b9ad1927fb2020-12-20T12:42:17ZengBMCBMC Bioinformatics1471-21052019-12-0120S2011310.1186/s12859-019-3206-6Inferring Pareto-optimal reconciliations across multiple event costs under the duplication-loss-coalescence modelRoss Mawhorter0Nuo Liu1Ran Libeskind-Hadas2Yi-Chieh Wu3Department of Computer Science, Harvey Mudd CollegeDepartment of Computer Science, Harvey Mudd CollegeDepartment of Computer Science, Harvey Mudd CollegeDepartment of Computer Science, Harvey Mudd CollegeAbstract Background 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. Results 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. Conclusion 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.https://doi.org/10.1186/s12859-019-3206-6PhylogeneticsReconciliationCoalescenceIncomplete lineage sortingGene duplication and lossPareto optimality
collection DOAJ
language English
format Article
sources DOAJ
author Ross Mawhorter
Nuo Liu
Ran Libeskind-Hadas
Yi-Chieh Wu
spellingShingle Ross Mawhorter
Nuo Liu
Ran Libeskind-Hadas
Yi-Chieh Wu
Inferring Pareto-optimal reconciliations across multiple event costs under the duplication-loss-coalescence model
BMC Bioinformatics
Phylogenetics
Reconciliation
Coalescence
Incomplete lineage sorting
Gene duplication and loss
Pareto optimality
author_facet Ross Mawhorter
Nuo Liu
Ran Libeskind-Hadas
Yi-Chieh Wu
author_sort Ross Mawhorter
title Inferring Pareto-optimal reconciliations across multiple event costs under the duplication-loss-coalescence model
title_short Inferring Pareto-optimal reconciliations across multiple event costs under the duplication-loss-coalescence model
title_full Inferring Pareto-optimal reconciliations across multiple event costs under the duplication-loss-coalescence model
title_fullStr Inferring Pareto-optimal reconciliations across multiple event costs under the duplication-loss-coalescence model
title_full_unstemmed Inferring Pareto-optimal reconciliations across multiple event costs under the duplication-loss-coalescence model
title_sort inferring pareto-optimal reconciliations across multiple event costs under the duplication-loss-coalescence model
publisher BMC
series BMC Bioinformatics
issn 1471-2105
publishDate 2019-12-01
description Abstract Background 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. Results 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. Conclusion 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.
topic Phylogenetics
Reconciliation
Coalescence
Incomplete lineage sorting
Gene duplication and loss
Pareto optimality
url https://doi.org/10.1186/s12859-019-3206-6
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