Cédric Chauve, Akbar Rafiey, Adrian A. Davin, Celine Scornavacca, Philippe Veber, Bastien Boussau, Gergely J Szöllosi, Vincent Daubin, and Eric TannierPlease use the format "First name initials family name" as in "Marie S. Curie, Niels H. D. Bohr, Albert Einstein, John R. R. Tolkien, Donna T. Strickland"
Lateral gene transfers (LGTs) between ancient species contain information about the relative timing of species diversification. Specifically, the ancestors of a donor species must have existed before the descendants of the recipient species. Hence, the detection of a LGT event can be translated into a time constraint between nodes of a phylogeny if donors and recipients can be identified. When a set of LGTs are detected by interpreting the phylogenetic discordance between gene trees and a species tree, the set of all deduced time constraints can be used to order totally the internal nodes and thus produce a ranked tree. Unfortunately LGT detection is still very challenging and current methods produce a significant proportion of false positives. As a result the set of time constraints is not always compatible with a ranked species tree. We propose an optimization method, which we call MaxTiC (Maximum Time Consistency), for obtaining a ranked species tree compatible with a maximum number of time constraints. The problem in general inherits NP-completeness from feedback arc sets. However we give an exact polynomial time method based on dynamic programming to compute an optimal ranked binary tree supposing that its two children are ranked. We turn this principle into a heuristic to solve the general problem and test it on simulated datasets. Under a wide range of conditions, which we compare to biological datasets, the obtained ranked tree is very close to the real one, confirming the theoretical possibility of dating in the history of life with transfers by maximizing time consistency. MaxTiC is available within the ALE package: https://github.com/ssolo/ALE/tree/master/misc.
Bioinformatics & Computational Biology, Evolutionary Dynamics, Genome Evolution, Life History, Molecular Evolution, Phylogenetics / Phylogenomics