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Resolution and reconciliation of non-binary gene trees with transfers, duplications and losses

Authors: Jacox, Edwin; Weller, Mathias; Tannier, Eric; Scornavacca, Celine;

Resolution and reconciliation of non-binary gene trees with transfers, duplications and losses

Abstract

Abstract Summary Gene trees reconstructed from sequence alignments contain poorly supported branches when the phylogenetic signal in the sequences is insufficient to determine them all. When a species tree is available, the signal of gains and losses of genes can be used to correctly resolve the unsupported parts of the gene history. However finding a most parsimonious binary resolution of a non-binary tree obtained by contracting the unsupported branches is NP-hard if transfer events are considered as possible gene scale events, in addition to gene origination, duplication and loss. We propose an exact, parameterized algorithm to solve this problem in single-exponential time, where the parameter is the number of connected branches of the gene tree that show low support from the sequence alignment or, equivalently, the maximum number of children of any node of the gene tree once the low-support branches have been collapsed. This improves on the best known algorithm by an exponential factor. We propose a way to choose among optimal solutions based on the available information. We show the usability of this principle on several simulated and biological datasets. The results are comparable in quality to several other tested methods having similar goals, but our approach provides a lower running time and a guarantee that the produced solution is optimal. Availability and Implementation Our algorithm has been integrated into the ecceTERA phylogeny package, available at http://mbb.univ-montp2.fr/MBB/download_sources/16__ecceTERA and which can be run online at http://mbb.univ-montp2.fr/MBB/subsection/softExec.php?soft=eccetera. Supplementary information Supplementary data are available at Bioinformatics online.

Country
France
Keywords

Genetic Variation, Cyanobacteria, Extinction, Biological, 004, Evolution, Molecular, Genes, Gene Duplication, Databases, Genetic, Proteobacteria, Computer Simulation, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], Algorithms, Phylogeny, [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM]

  • BIP!
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    selected citations
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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    13
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
13
Top 10%
Average
Average
Green
gold