Maximum parsimony reconciliation in the DTLOR model.

BACKGROUND: Analyses of microbial evolution often use reconciliation methods. However, the standard duplication-transfer-loss (DTL) model does not account for the fact that species trees are often not fully sampled and thus, from the perspective of reconciliation, a gene family may enter the species tree from the outside. Moreover, within the genome, genes are often rearranged, causing them to move to new syntenic regions. RESULTS: We extend the DTL model to account for two events that commonly arise in the evolution of microbes: origin of a gene from outside the sampled species tree and rearrangement of gene syntenic regions. We describe an efficient algorithm for maximum parsimony reconciliation in this new DTLOR model and then show how it can be extended to account for non-binary gene trees to handle uncertainty in gene tree topologies. Finally, we describe preliminary experimental results from the integration of our algorithm into the existing xenoGI tool for reconstructing the histories of genomic islands in closely related bacteria. CONCLUSIONS: Reconciliation in the DTLOR model can offer new insights into the evolution of microbes that is not currently possible under the DTL model.

eMPRess: a systematic cophylogeny reconciliation tool.

SUMMARY: We describe eMPRess, a software program for phylogenetic tree reconciliation under the duplication-transfer-loss model that systematically addresses the problems of choosing event costs and selecting representative solutions, enabling users to make more robust inferences. AVAILABILITY AND IMPLEMENTATION: eMPRess is freely available at http://www.cs.hmc.edu/empress. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

An efficient exact algorithm for computing all pairwise distances between reconciliations in the duplication-transfer-loss model.

BACKGROUND: Maximum parsimony reconciliation in the duplication-transfer-loss model is widely used in studying the evolutionary histories of genes and species and in studying coevolution of parasites and their hosts and pairs of symbionts. While efficient algorithms are known for finding maximum parsimony reconciliations, the number of reconciliations can grow exponentially in the size of the trees. An understanding of the space of maximum parsimony reconciliations is necessary to determine whether a single reconciliation can adequately represent the space or whether multiple representative reconciliations are needed. RESULTS: We show that for any instance of the reconciliation problem, the distribution of pairwise distances can be computed exactly by an efficient polynomial-time algorithm with respect to several different distance metrics. We describe the algorithm, analyze its asymptotic worst-case running time, and demonstrate its utility and viability on a large biological dataset. CONCLUSIONS: This result provides new insights into the structure of the space of maximum parsimony reconciliations. These insights are likely to be useful in the wide range of applications that employ reconciliation methods.