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Inferring duplications, losses, transfers and incomplete lineage sorting with nonbinary species trees

Authors: Maureen Stolzer; Han Lai; Minli Xu; Deepa Sathaye; Benjamin Vernot; Dannie Durand;

Inferring duplications, losses, transfers and incomplete lineage sorting with nonbinary species trees

Abstract

Abstract Motivation: Gene duplication (D), transfer (T), loss (L) and incomplete lineage sorting (I) are crucial to the evolution of gene families and the emergence of novel functions. The history of these events can be inferred via comparison of gene and species trees, a process called reconciliation, yet current reconciliation algorithms model only a subset of these evolutionary processes. Results: We present an algorithm to reconcile a binary gene tree with a nonbinary species tree under a DTLI parsimony criterion. This is the first reconciliation algorithm to capture all four evolutionary processes driving tree incongruence and the first to reconcile non-binary species trees with a transfer model. Our algorithm infers all optimal solutions and reports complete, temporally feasible event histories, giving the gene and species lineages in which each event occurred. It is fixed-parameter tractable, with polytime complexity when the maximum species outdegree is fixed. Application of our algorithms to prokaryotic and eukaryotic data show that use of an incomplete event model has substantial impact on the events inferred and resulting biological conclusions. Availability: Our algorithms have been implemented in Notung, a freely available phylogenetic reconciliation software package, available at http://www.cs.cmu.edu/~durand/Notung. Contact: mstolzer@andrew.cmu.edu

Keywords

Gene Transfer, Horizontal, Models, Genetic, Original Papers, Evolution, Molecular, Gene Duplication, Multigene Family, FOS: Biological sciences, Algorithms, Phylogeny, Software, 69999 Biological Sciences not elsewhere classified

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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!
291
Top 1%
Top 1%
Top 1%
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gold