DART: Detection of Additive and Replacing Transfers

DART (short for “Detection of Additive and Replacing Transfers”) is a software package for classifying inferred horizontal gene transfers (HGTs) as either additive or replacing. An additive HGT occurs when the transferred gene adds itself as a new gene in the recipient genome. When a transferred gene replaces an existing homologous gene in the recipient genome, it is called a replacing HGT. The current version of DART only classifies those HGTs where the donor and recipient are both terminal (leaf) edges on the species tree. Note that this version of DART is designed to classify only putative “single-gene” HGTs, where only a small number of genes, ideally only one but perhaps, say, no more than two or three, were simultaneously transferred in the horizontal transfer event.

DART takes as input a rooted species tree, a rooted gene tree for each gene family consisting of least 4 genes present in the species/genomes under consideration, and gene ordering information for the species/genomes (leaves) represented in the species tree. The software uses phylogenetic reconciliation to infer high-confidence leaf-to-leaf single-gene HGTs and classifies them as “additive”, “replacing”, or “ambiguous”. DART’s classification is based on comparing the gene neighborhood conservation around the transferred gene in the recipient genome as well as in the recipient’s closest phylogenetic neighbors. Further algorithmic and technical details appear in the manual and in the paper cited below.

DART is written in Python and requires version 3.0 or greater. The implementation also assumes that ETE 3 toolkit is already installed. ETE toolkit is available freely from etetoolkit.org.

DART was implemented by Lina Kloub and is available open source under GNU GPL. Python Code, along with pre-compiled auxiliary C/C++ code (for Linux and macOS), and a user manual are available below.

The Aeromonas dataset used in this research as well as final classification results inferred on this dataset are also available below.

This software can be cited as follows:

Funding: Development of the software resource(s) available from this webpage was funded in part by U.S. National Science Foundation award MCB 1616514.

Contact: Please feel free to contact Mukul Bansal (mukul.bansal@uconn.edu) if you have any questions, concerns, or suggestions.