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Horizontal gene transfer (HGT) is one of the main mechanisms driving the evolution of microorganisms. Its accurate identification is one of the major challenges posed by reticulate evolution. In this article, we describe a new polynomial-time algorithm for inferring HGT events and compare 3 existing and 1 new tree comparison indices in the context of HGT identification. The proposed algorithm can rely on different optimization criteria, including least squares (LS), Robinson and Foulds (RF) distance, quartet distance (QD), and bipartition dissimilarity (BD), when searching for an optimal scenario of subtree prune and regraft (SPR) moves needed to transform the given species tree into the given gene tree. As the simulation results suggest, the algorithmic strategy based on BD, introduced in this article, generally provides better results than those based on LS, RF, and QD. The BD-based algorithm also proved to be more accurate and faster than a well-known polynomial time heuristic RIATA-HGT. Moreover, the HGT recovery results yielded by BD were generally equivalent to those provided by the exponential-time algorithm LatTrans, but a clear gain in running time was obtained using the new algorithm. Finally, a statistical framework for assessing the reliability of obtained HGTs by bootstrap analysis is also presented.

Inferring and Validating Horizontal Gene Transfer Events Using Bipartition Dissimilarity