Integrating Sequence and Topology for Efficient and Accurate Detection of Horizontal Gene Transfer (original) (raw)

An Empirical Comparison Between BPAnalysis and MPBE on the Campanulaceae Chloroplast Genome Dataset

The breakpoint phylogeny is an optimization problem proposed by Blanchette et al. for reconstructing evolutionary trees from gene order data. These same authors developed and implemented BPAnalysis [4], a heuristic method (based upon solving many instances of the Travelling Salesman Problem) for estimating the breakpoint phylogeny. We present a new heuristic for estimating the breakpoint phylogeny which, although not polynomial-time, is much faster in practice than BPAnalysis. We use this heuristic to conduct a phylogenetic analysis of the flowering plant family Campanulaceae. We also present and discuss the results of experimentation on this real dataset with three methods: our new method, BPAnalysis, and the neighbor-joining method [21], using breakpoint distances, inversion distances, and inversion plus transposition distances. Introduction Phylogenetic tree reconstruction is a major aspect of much biological research. This is a very difficult computational problem b...

Efficiency of the Neighbor-Joining Method in Reconstructing Deep and Shallow Evolutionary Relationships in Large Phylogenies

The neighbor-joining (NJ) method is widely used in reconstructing large phylogenies because of its computational speed and the high accuracy in phylogenetic inference as revealed in computer simulation studies. However, most computer simulation studies have quantified the overall performance of the NJ method in terms of the percentage of branches inferred correctly or the percentage of replications in which the correct tree is recovered. We have examined other aspects of its performance, such as the relative efficiency in correctly reconstructing shallow (close to the external branches of the tree) and deep branches in large phylogenies; the contribution of zero-length branches to topological errors in the inferred trees; and the influence of increasing the tree size (number of sequences), evolutionary rate, and sequence length on the efficiency of the NJ method. Results show that the correct reconstruction of deep branches is no more difficult than that of shallower branches. The presence of zero-length branches in realized trees contributes significantly to the overall error observed in the NJ tree, especially in large phylogenies or slowly evolving genes. Furthermore, the tree size does not influence the efficiency of NJ in reconstructing shallow and deep branches in our simulation study, in which the evolutionary process is assumed to be homogeneous in all lineages.