Inferring the evolutionary history of gene clusters from phylogenetic and gene order data

Gene duplication is frequent within gene clusters and plays a fundamental role in evolution by providing a source of new genetic material upon which natural selection can act. Although classical phylogenetic inference methods provide some insight into the evolutionary history of a gene cluster, they are not sufficient alone to differentiate single- from multiple gene duplication events and to answer other questions regarding the nature and size of evolutionary events. In this paper, we present an algorithm allowing to infer a set of optimal evolutionary histories for a gene cluster in a single species, according to a general cost model involving variable length duplications (in tandem or inverted), deletions, and inversions. We applied our algorithm to the human olfactory receptor and protocadherin gene clusters, showing that the duplication size distribution differs significantly between the two gene families. The algorithm is available through a web interface at http://www-lbit.iro.umontreal.ca/DILTAG/.