Inferring species trees from gene duplication episodes

• Authors: J. Gordon Burleigh;Mukul S. Bansal;Oliver Eulenstein;Todd J. Vision
• Venue: Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology
• Year: 2010

Gene tree parsimony, which infers a species tree that implies the fewest gene duplications across a collection of gene trees, is a method for inferring phylogenetic trees from paralogous genes. However, it assumes that all duplications are independent, and therefore, it does not account for large-scale gene duplication events like whole genome duplications. We describe two methods to infer species trees based on gene duplication events that may involve multiple genes. First, gene episode parsimony seeks the species tree that implies the fewest possible gene duplication episodes. Second, adjusted gene tree parsimony corrects the number of gene duplications at each node in the species tree by treating the largest possible gene duplication episode as a single duplication. We test both new methods, as well as gene tree parsimony, using 7,091 gene trees representing 7 plant taxa. Gene tree parsimony and adjusted gene tree parsimony both perform well, returning the species tree after an exhaustive search of the tree space. By contrast, gene episode parsimony fails to rank the true species tree within the top third of all possible topologies. Furthermore, gene trees with randomly permuted leaf labels can imply fewer duplication episodes than gene trees with the correct leaf labels. Adjusted gene tree parsimony reflects a potentially more realistic and, at least for small data sets, computationally feasible model for counting gene duplication events than treating each duplication independently or minimizing the number of possible duplication episodes.