Predicting the Evolution of Syntenies—An Algorithmic Review

Abstract

Syntenies are genomic segments of consecutive genes identified by a certain conservation in gene content and order. The notion of conservation may vary from one definition to another, the more constrained requiring identical gene contents and gene orders, while more relaxed definitions just require a certain similarity in gene content, and not necessarily in the same order. Regardless of the way they are identified, the goal is to characterize homologous genomic regions, i.e., regions deriving from a common ancestral region, reflecting a certain gene co-evolution that can enlighten important functional properties. In addition of being able to identify them, it is also necessary to infer the evolutionary history that has led from the ancestral segment to the extant ones. In this field, most algorithmic studies address the problem of inferring rearrangement scenarios explaining the disruption in gene order between segments with the same gene content, some of them extending the evolutionary model to gene insertion and deletion. However, syntenies also evolve through other events modifying their content in genes, such as duplications, losses or horizontal gene transfers, i.e., the movement of genes from one species to another. Although the reconciliation approach between a gene tree and a species tree addresses the problem of inferring such events for single-gene families, little effort has been dedicated to the generalization to segmental events and to syntenies. This paper reviews some of the main algorithmic methods for inferring ancestral syntenies and focus on those integrating both gene orders and gene trees.