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

Ross Mawhorter, Nuo Liu, Ran Libeskind-Hadas, Yi-Chieh Wu
Author Information
  1. Ross Mawhorter: Department of Computer Science, Harvey Mudd College, Claremont, 91711, CA, USA.
  2. Nuo Liu: Department of Computer Science, Harvey Mudd College, Claremont, 91711, CA, USA.
  3. Ran Libeskind-Hadas: Department of Computer Science, Harvey Mudd College, Claremont, 91711, CA, USA.
  4. Yi-Chieh Wu: Department of Computer Science, Harvey Mudd College, Claremont, 91711, CA, USA. yjw@cs.hmc.edu.

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.

Keywords

References

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MeSH Term

Algorithms
Fungi
Gene Duplication
Models, Genetic
Phylogeny

Word Cloud

Created with Highcharts 10.0.0reconciliationscostseventacrossrelationshipeventsReconciliationtreespeciesmaximumparsimonyworkduplication-loss-coalescencemodelPareto-optimalspaceBACKGROUND:methodswidelyusedexplainincongruencegeneHowevercommonapproachinferringMPRsreliesuser-definedtypecandifficultestimatePriorexploredduplication-lossduplication-transfer-lossmodelsstudiesaddressedcomplicatedRESULTS:providefixed-parametertractablealgorithmcomputingrecordingarisealongfrequenciesapplymethodcasestudy16fungisystematicallycharacterizecomplexityMPRidentifysupportedCONCLUSION:providesnewframeworkstudyingincorporatesmacro-evolutionarypopulationeffectsthusbroadlyapplicableeukaryoticInferringmultipleCoalescenceGeneduplicationlossIncompletelineagesortingParetooptimalityPhylogenetics

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