Modeling gene expression evolution with EvoGeneX uncovers differences in evolution of species, organs and sexes

Abstract

While DNA sequence evolution has been well studied, the expression of genes is also subject to evolution, yet the evolution of gene expression is currently not well understood. Recently, new tissue/organ-specific gene expression datasets spanning several organisms across the tree of life, have become available, providing the opportunity to study gene expression evolution in more detail. While a theoretical model to study the evolution of continuous traits exists, in practice computational methods often cannot confidently distinguish between alternative evolutionary scenarios. This lack of power has been attributed to modest numbers of species considered in these studies. We hypothesised that biological replicates can be used to increase predictive power of these models. With this in mind, we introduce EvoGeneX, a computationally efficient method to uncover the mode of gene expression evolution based on the Ornstein-Uhlenbeck process. Importantly, in addition to modelling expression variations between species, EvoGeneX models within-species variation. Furthermore, to facilitate comparative analysis of gene expression evolution, we introduce a formal approach, based on Michaelis-Menten equation, to measure the dynamics of evolutionary divergence of a group of genes in terms of groups asymptotic divergence level and rate. Finally, we used these tools to preform the first analysis the evolution of gene expression across different body parts, species, and sexes of the Drosophila genus. Our analysis revealed that neutral expression evolution can be confidently rejected in favor of purifying selection in nearly half of the genes. In addition, we quantified differences in the evolutionary dynamics of male and female gonads and uncovered interesting examples of adaptive gene expression evolution.