New approaches for unravelling reassortment pathways

BMC Evolutionary Biology

Research Article

James O McInerney¹  Victoria Svinti²  James A Cotton³ 

[1] Department of Biology, National University of Ireland at Maynooth, Maynooth, Co Kildare, Ireland;Department of Biology, National University of Ireland at Maynooth, Maynooth, Co Kildare, Ireland;Department of Microbiology & Immunology, Life Sciences Centre, University of British Columbia, V6T 1Z3, Vancouver, BC, Canada;Department of Biology, National University of Ireland at Maynooth, Maynooth, Co Kildare, Ireland;Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, CB10 1SA, Hinxton, Cambridge, UK;

关键词: Influenza;    Tree Topology;    Test Tree;    Reference Tree;    Approximately Unbiased;   

DOI  :  10.1186/1471-2148-13-1

 received in 2012-04-05, accepted in 2012-11-21,  发布年份 2013

来源: Springer

【 摘 要 】

BackgroundEvery year the human population encounters epidemic outbreaks of influenza, and history reveals recurring pandemics that have had devastating consequences. The current work focuses on the development of a robust algorithm for detecting influenza strains that have a composite genomic architecture. These influenza subtypes can be generated through a reassortment process, whereby a virus can inherit gene segments from two different types of influenza particles during replication. Reassortant strains are often not immediately recognised by the adaptive immune system of the hosts and hence may be the source of pandemic outbreaks. Owing to their importance in public health and their infectious ability, it is essential to identify reassortant influenza strains in order to understand the evolution of this virus and describe reassortment pathways that may be biased towards particular viral segments. Phylogenetic methods have been used traditionally to identify reassortant viruses. In many studies up to now, the assumption has been that if two phylogenetic trees differ, it is because reassortment has caused them to be different. While phylogenetic incongruence may be caused by real differences in evolutionary history, it can also be the result of phylogenetic error. Therefore, we wish to develop a method for distinguishing between topological inconsistency that is due to confounding effects and topological inconsistency that is due to reassortment.ResultsThe current work describes the implementation of two approaches for robustly identifying reassortment events. The algorithms rest on the idea of significance of difference between phylogenetic trees or phylogenetic tree sets, and subtree pruning and regrafting operations, which mimic the effect of reassortment on tree topologies. The first method is based on a maximum likelihood (ML) framework (MLreassort) and the second implements a Bayesian approach (Breassort) for reassortment detection. We focus on reassortment events that are found by both methods. We test both methods on a simulated dataset and on a small collection of real viral data isolated in Hong Kong in 1999.ConclusionsThe nature of segmented viral genomes present many challenges with respect to disease. The algorithms developed here can effectively identify reassortment events in small viral datasets and can be applied not only to influenza but also to other segmented viruses. Owing to computational demands of comparing tree topologies, further development in this area is necessary to allow their application to larger datasets.

【 授权许可】

Unknown   
© Svinti et al.; licensee BioMed Central Ltd. 2013. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.