PDF(Pubmed)
Abstract：
Evolutionary models of quantitative traits often assume trade-offs between beneficial and detrimental traits, requiring modelers to specify a function linking costs to benefits. The choice of trade-off function is often consequential; functions that assume diminishing returns (accelerating costs) typically lead to single equilibrium genotypes, while decelerating costs often lead to evolutionary branching. Despite their importance, we still lack a strong theoretical foundation to base the choice of trade-off function. To address this gap, we explore how trade-off functions can emerge from the genetic architecture of a quantitative trait. We developed a multi-locus model of disease resistance, assuming each locus had random antagonistic pleiotropic effects on resistance and fecundity. We used this model to generate genotype landscapes and explored how additive versus epistatic genetic architectures influenced the shape of the trade-off function. Regardless of epistasis, our model consistently led to accelerating costs. We then used our genotype landscapes to build an evolutionary model of disease resistance. Unlike other models with accelerating costs, our approach often led to genetic polymorphisms at equilibrium. Our results suggest that accelerating costs are a strong null model for evolutionary trade-offs and that the eco-evolutionary conditions required for polymorphism may be more nuanced than previously believed.
摘要：
数量性状的进化模型通常在有益和有害性状之间进行权衡，要求建模者指定一个将成本与收益联系起来的函数。权衡函数的选择通常是重要的；假设收益递减（加速成本）的函数通常会导致单一的平衡基因型，而减速成本往往会导致进化分支。尽管它们很重要,我们仍然缺乏强有力的理论基础来选择权衡函数。为了解决这个差距，我们探索权衡函数如何从数量性状的遗传结构中出现。我们建立了多位点抗病性模型,假设每个基因座对抗性和繁殖力具有随机拮抗多效性作用。我们使用此模型来生成基因型景观，并探索了加性与上位性遗传体系结构如何影响权衡函数的形状。不管认识论，我们的模式一直导致成本加速。然后，我们使用我们的基因型景观来建立抗病性的进化模型。与其他加速成本的模型不同，我们的方法经常导致处于平衡状态的遗传多态性。我们的结果表明，加速成本是进化权衡的强大零模型，并且多态性所需的生态进化条件可能比以前认为的更为细微。
