Inference of Genome Duplications from Age Distributions Revisited

Abstract

Whole-genome duplications (WGDs), thought to facilitate evolutionary innovations and adaptations, have been uncovered in many phylogenetic lineages. WGDs are frequently inferred from duplicate age distributions, where they manifest themselves as peaks against a small-scale duplication background. However, the interpretation of duplicate age distributions is complicated by the use of K(S), the number of synonymous substitutions per synonymous site, as a proxy for the age of paralogs. Two particular concerns are the stochastic nature of synonymous substitutions leading to increasing uncertainty in K(S) with increasing age since duplication and K(S) saturation caused by the inability of evolutionary models to fully correct for the occurrence of multiple substitutions at the same site. K(S) stochasticity is expected to erode the signal of older WGDs, whereas K(S) saturation may lead to artificial peaks in the distribution. Here, we investigate the consequences of these effects on K(S)-based age distributions and WGD inference by simulating the evolution of duplicated sequences according to predefined real age distributions and re-estimating the corresponding K(S) distributions. We show that, although K(S) estimates can be used for WGD inference far beyond the commonly accepted K(S) threshold of 1, K(S) saturation effects can cause artificial peaks at higher ages. Moreover, K(S) stochasticity and saturation may lead to confounded peaks encompassing multiple WGD events and/or saturation artifacts. We argue that K(S) effects need to be properly accounted for when inferring WGDs from age distributions and that the failure to do so could lead to false inferences.