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Xenolog Classification

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  • Daniel Barker
  • Charlotte Darby
  • Maureen Stolzer
  • Patrick Ropp
  • Dannie Durand

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    Rights statement: © The Author 2016. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

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Original languageEnglish
Pages (from-to)640-649
Number of pages10
JournalBioinformatics
Volume33
Issue number5
Early online date29 Dec 2016
DOIs
Publication statusPublished - 1 Mar 2017

Abstract

Motivation: Orthology analysis is a fundamental tool in comparative genomics. Sophisticated methods have been developed to distinguish between orthologs and paralogs and to classify paralogs into subtypes depending on the duplication mechanism and timing, relative to speciation. However, no comparable framework exists for xenologs: gene pairs whose history, since their divergence, includes a horizontal transfer. Further, the diversity of gene pairs that meet this broad definition calls for classification of xenologs with similar properties into subtypes.
Results: We present a xenolog classification that uses phylogenetic reconciliation to assign each pair of genes to a class based on the event responsible for their divergence and the historical association between genes and species. Our classes distinguish between genes related through transfer alone and genes related through duplication and transfer. Further, they separate closely-related genes in distantly-related species from distantly-related genes in closely-related species. We present formal rules that assign gene pairs to specific xenolog classes, given a reconciled gene tree with an arbitrary number of duplications and transfers. The xenology classification rules have been implemented in software and tested on a collection of ∼13,000 prokaryotic gene families. In addition, we present a case study demonstrating the connection between xenolog classification and gene function prediction.

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