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Modeling Gene Expression Evolution with an Extended Ornstein-Uhlenbeck Process Accounting for Within-Species Variation

机译:使用扩展的Ornstein-Uhlenbeck过程解释物种内变异的基因表达进化模型

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摘要

Much of the phenotypic variation observed between even closely related species may be driven by differences in gene expression levels. The current availability of reliable techniques like RNA-Seq, which can quantify expression levels across species, has enabled comparative studies. Ornstein-Uhlenbeck (OU) processes have been proposed to model gene expression evolution as they model both random drift and stabilizing selection and can be extended to model changes in selection regimes. The OU models provide a statistical framework that allows comparisons of specific hypotheses of selective regimes, including random drift, constrained drift, and expression level shifts. In this way, inferences may be made about the mode of selection acting on the expression level of a gene. We augment this model to include within-species expression variance, allowing for modeling of nonevolutionary expression variance that could be caused by individual genetic, environmental, or technical variation. Through simulations, we explore the reliability of parameter estimates and the extent to which different selective regimes can be distinguished using phylogenies of varying size using both the typical OU model and our extended model. We find that if individual variation is not accounted for, nonevolutionary expression variation is often mistaken for strong stabilizing selection. The methods presented in this article are increasingly relevant as comparative expression data becomes more available and researchers turn to expression as a primary evolving phenotype.
机译:即使在密切相关的物种之间观察到的许多表型变异,也可能是由于基因表达水平的差异所驱动。 RNA-Seq等可靠技术的当前可用性,可以量化跨物种的表达水平,这使得进行比较研究成为可能。已经提出了Ornstein-Uhlenbeck(OU)过程来模拟基因表达进化,因为它们可以模拟随机漂移和稳定选择,并且可以扩展为模拟选择机制的变化。 OU模型提供了一个统计框架,该框架允许对选择性方案的特定假设进行比较,包括随机漂移,约束漂移和表达水平漂移。以这种方式,可以推断出作用于基因表达水平的选择模式。我们对该模型进行了扩展,使其包括物种内的表达差异,从而可以对由个体遗传,环境或技术差异引起的非进化表达差异进行建模。通过仿真,我们探索了参数估计的可靠性,以及使用典型的OU模型和扩展模型使用大小不同的系统发育树区分不同选择方案的程度。我们发现,如果不考虑个体变异,则非进化表达变异通常被误认为是强稳定选择。随着比较表达数据的获得和研究人员将表达作为主要的进化表型,本文中提出的方法越来越相关。

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