title: Probabilistic inference of lateral gene transfer events.
abstract: BACKGROUND
  Lateral gene transfer (LGT) is an evolutionary process that has an important role in biology. It challenges the traditional binary tree-like evolution of species and is attracting increasing attention of the molecular biologists due to its involvement in antibiotic resistance. A number of attempts have been made to model LGT in the presence of gene duplication and loss, but reliably placing LGT events in the species tree has remained a challenge.
  
  
  RESULTS
  In this paper, we propose probabilistic methods that samples reconciliations of the gene tree with a dated species tree and computes maximum a posteriori probabilities. The MCMC-based method uses the probabilistic model DLTRS, that integrates LGT, gene duplication, gene loss, and sequence evolution under a relaxed molecular clock for substitution rates. We can estimate posterior distributions on gene trees and, in contrast to previous work, the actual placement of potential LGT, which can be used to, e.g., identify "highways" of LGT.
  
  
  CONCLUSIONS
  Based on a simulation study, we conclude that the method is able to infer the true LGT events on gene tree and reconcile it to the correct edges on the species tree in most cases. Applied to two biological datasets, containing gene families from Cyanobacteria and Molicutes, we find potential LGTs highways that corroborate other studies as well as previously undetected examples.
authors.affiliation: KTH Royal Institute of Technology, School of Computer Science and Communication, Box 1031, Solna, 171 21, Sweden.|Science for Life Laboratory, Box 1031, Solna, 171 21, Sweden.
authors.forename: Mehmood Alam
authors.initials: MA
authors.lastname: Khan
authors.affiliation: KTH Royal Institute of Technology, School of Computer Science and Communication, Box 1031, Solna, 171 21, Sweden.|Science for Life Laboratory, Box 1031, Solna, 171 21, Sweden.
authors.forename: Owais
authors.initials: O
authors.lastname: Mahmudi
authors.affiliation: KTH Royal Institute of Technology, School of Computer Science and Communication, Box 1031, Solna, 171 21, Sweden.|Science for Life Laboratory, Box 1031, Solna, 171 21, Sweden.
authors.forename: Ikram
authors.initials: I
authors.lastname: Ullah
authors.affiliation: Science for Life Laboratory, Box 1031, Solna, 171 21, Sweden.|Stockholm University, Dept. of Numerical Analysis and Computer Science, Box 1031, Solna, 171 21, Sweden.|Swedish e-Science Research Centre, Solna, Sweden.
authors.forename: Lars
authors.initials: L
authors.lastname: Arvestad
authors.affiliation: KTH Royal Institute of Technology, School of Computer Science and Communication, Box 1031, Solna, 171 21, Sweden. jensl@kth.se.|Science for Life Laboratory, Box 1031, Solna, 171 21, Sweden. jensl@kth.se.
authors.forename: Jens
authors.initials: J
authors.lastname: Lagergren
mesh_terms: D005075:Biological Evolution; D045622:Entomoplasmataceae / Q000145:classification / Q000235:genetics; D022761:Gene Transfer, Horizontal / Q000235:genetics*; D008957:Models, Genetic; D010802:Phylogeny
keywords: Bayesian inference; Evolution; Lateral gene transfer; Phylogeny