Inferring species trees from incongruent multi-copy gene trees using the Robinson-Foulds distance

Abstract

BackgroundConstructing species trees from multi-copy gene trees remains a challenging problem in phylogenetics. One difficulty is that the underlying genes can be incongruent due to evolutionary processes such as gene duplication and loss, deep coalescence, or lateral gene transfer. Gene tree estimation errors may further exacerbate the difficulties of species tree estimation.ResultsWe present a new approach for inferring species trees from incongruent multi-copy gene trees that is based on a generalization of the Robinson-Foulds (RF) distance measure to multi-labeled trees (mul-trees). We prove that it is NP-hard to compute the RF distance between two mul-trees; however, it is easy to calculate this distance between a mul-tree and a singly-labeled species tree. Motivated by this, we formulate the RF problem for mul-trees (MulRF) as follows: Given a collection of multi-copy gene trees, find a singly-labeled species tree that minimizes the total RF distance from the input mul-trees. We develop and implement a fast SPR-based heuristic algorithm for the NP-hard MulRF problem.We compare the performance of the MulRF method (available at http://genome.cs.iastate.edu/CBL/MulRF/) with several gene tree parsimony approaches using gene tree simulations that incorporate gene tree error, gene duplications and losses, and/or lateral transfer. The MulRF method produces more accurate species trees than gene tree parsimony approaches. We also demonstrate that the MulRF method infers in minutes a credible plant species tree from a collection of nearly 2,000 gene trees.ConclusionsOur new phylogenetic inference method, based on a generalized RF distance, makes it possible to quickly estimate species trees from large genomic data sets. Since the MulRF method, unlike gene tree parsimony, is based on a generic tree distance measure, it is appealing for analyses of genomic data sets, in which many processes such as deep coalescence, recombination, gene duplication and losses as well as phylogenetic error may contribute to gene tree discord. In experiments, the MulRF method estimated species trees accurately and quickly, demonstrating MulRF as an efficient alternative approach for phylogenetic inference from large-scale genomic data sets.

Gut transcriptome analysis on females of Ornithodoros mimon (Acari: Argasidae) and phylogenetic inference of ticks

“…The tick species tree was inferred using the MulRF software package, which is a tree that minimizes the modified RobinsonFoulds (RF) distance for all input gene trees (CHAUDHARY et al, 2013(CHAUDHARY et al, , 2015. MulRF infers species trees from multi-copy gene trees using a generalization of RF topological distance, and it works by minimizing the total RF distance from the input multi-labeled trees, being relatively accurate in spite of evolutionary processes affecting single gene trees such as gene duplication and loss, deep coalescence, or lateral gene transfer (given our dataset, the most pervasive are gene duplication and loss).…”

“…Its power lies in not assuming any specific evolutionary process during the analysis (i.e. incomplete lineage sorting, gene duplication and/or gene loss).The MulRF method produces more accurate species trees than other gene tree parsimony approaches (CHAUDHARY et al, 2013). Nevertheless, because it works like a consensus tree, no nodal supports are available, so this issue must be overcome beforehand; we did this by collapsing branches with less than 70% support in each gene tree using TreeCollapseCL4 (HODCROFT et al, 2014), as mentioned above.…”

Are the Duplication Cost and Robinson-Foulds Distance Equivalent?

“…However, recently, Chaudhary et al (2013) demonstrated by simulation that the RF-based parsimony approach often outperforms the reconciliation methods that use the gene duplication or mutation costs. A recent study of Yang and Warnow (2011) also suggests that the duplication-cost-based approach has poorer performance at large.…”

“…The scoring models used in these methods include the duplication cost (that is, the number of duplications), the mutation cost (that is, the number of gene duplication and loss events), the deep coalescence cost (that is, the number of incomplete lineage sorting events), and the Robinson-Foulds (RF) distance (Bansal et al, 2010;Bayzid et al, 2012;Chang et al, 2013;Chaudhary et al, 2013;Than and Nakhleh, 2009;Wehe et al, 2008;Yu et al, 2011). Since finding the parsimony tree from gene trees is NP-hard for the reconciliation scoring models (Bryant, 1997;Ma et al, 2000;Zhang, 2011), existing methods all compute a species tree by navigating through the part of the species tree space guided by the reconciliation score.…”

“…Since finding the parsimony tree from gene trees is NP-hard for the reconciliation scoring models (Bryant, 1997;Ma et al, 2000;Zhang, 2011), existing methods all compute a species tree by navigating through the part of the species tree space guided by the reconciliation score. The performances of these heuristic methods are usually evaluated using the RF distances between true species trees and their estimate output on simulation datasets (Chaudhary et al, 2013;Than and Nakhleh, 2009;Yang and Warnow, 2011). Hence, uncovering the relationships between the RF distance and the reconciliation costs is important to design good gene tree reconciliation methods.…”