Horizontal Gene Transfer (HGT), a process of acquisition and fixation of foreign genetic material, is an important biological phenomenon. Several approaches to HGT inference have been proposed. However, most of them either rely on approximate, non-phylogenetic methods or on the tree reconciliation, which is computationally intensive and sensitive to parameter values. In this work, we investigate the Locus Tree Inference problem as a possible alternative that combines the advantages of both

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... aches. We show several algorithms to solve the problem in the parsimony framework. We introduce a novel tree mapping, which allows us to obtain a heuristic solution to the problems of locus tree inference and duplication classification. Our approach allows not only for faster comparisons of gene and species trees but also to improve known algorithms for duplication inference in the presence of polytomies in the species trees.