Inferring explicit weighted consensus networks to represent alternative evolutionary histories

BMC Evolutionary Biology

Vladimir Makarenkov²  Pedro R Peres-Neto¹  Mehdi Layeghifard² 

[1] Département des Sciences biologiques, Université du Québec à Montréal (UQÀM), CP 8888, Succ. Centre Ville, Montréal, QC H3C 3P8, Canada;Département d’Informatique, Université du Québec à Montréal (UQÀM), CP 8888, Succ. Centre Ville, Montréal, QC H3C 3P8, Canada

关键词: Reticulate evolution;    Phylogenetic tree;    Phylogenetic network;    Consensus tree;    Consensus network;   

Others  :  858172
DOI  :  10.1186/1471-2148-13-274

 received in 2013-08-23, accepted in 2013-12-16,  发布年份 2013

【 摘 要 】

Background

The advent of molecular biology techniques and constant increase in availability of genetic material have triggered the development of many phylogenetic tree inference methods. However, several reticulate evolution processes, such as horizontal gene transfer and hybridization, have been shown to blur the species evolutionary history by causing discordance among phylogenies inferred from different genes.

Methods

To tackle this problem, we hereby describe a new method for inferring and representing alternative (reticulate) evolutionary histories of species as an explicit weighted consensus network which can be constructed from a collection of gene trees with or without prior knowledge of the species phylogeny.

Results

We provide a way of building a weighted phylogenetic network for each of the following reticulation mechanisms: diploid hybridization, intragenic recombination and complete or partial horizontal gene transfer. We successfully tested our method on some synthetic and real datasets to infer the above-mentioned evolutionary events which may have influenced the evolution of many species.

Conclusions

Our weighted consensus network inference method allows one to infer, visualize and validate statistically major conflicting signals induced by the mechanisms of reticulate evolution. The results provided by the new method can be used to represent the inferred conflicting signals by means of explicit and easy-to-interpret phylogenetic networks.

【 授权许可】

   
2013 Layeghifard et al.; licensee BioMed Central Ltd.

【 图 表 】

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