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(进化)突变率与复合性状结构的演化。

(Epi)mutation Rates and the Evolution of Composite Trait Architectures.

出版信息

Am Nat. 2024 Sep;204(3):E42-E56. doi: 10.1086/731461. Epub 2024 Jul 22.

DOI:10.1086/731461
PMID:39179232
Abstract

AbstractMutation rates vary widely along genomes and across inheritance systems. This suggests that complex traits-resulting from the contributions of multiple determinants-might be composite in terms of the underlying mutation rates. Here we investigate through mathematical modeling whether such a heterogeneity may drive changes in a trait's architecture, especially in fluctuating environments, where phenotypic instability can be beneficial. We first identify a convexity principle related to the shape of the trait's fitness function, setting conditions under which composite architectures should be adaptive or, conversely and more commonly, should be selected against. Simulations reveal, however, that applying this principle to realistic evolving populations requires taking into account pervasive epistatic interactions that take place in the system. Indeed, the fate of a mutation affecting the architecture depends on the (epi)genetic background, which itself depends on the current architecture in the population. We tackle this problem by borrowing the adaptive dynamics framework from evolutionary ecology-where it is routinely used to deal with such resident/mutant dependencies-and find that the principle excluding composite architectures generally prevails. Yet the predicted evolutionary trajectories will typically depend on the initial architecture, possibly resulting in historical contingencies. Finally, by relaxing the large population size assumption, we unexpectedly find that not only the strength of selection on a trait's architecture but also its direction depend on population size, revealing a new occurrence of the recently identified phenomenon coined "sign inversion."

摘要

摘要 突变率在基因组和遗传系统中差异很大。这表明,复杂性状——由多个决定因素共同作用产生——在潜在的突变率方面可能是复合的。在这里,我们通过数学建模来研究这种异质性是否会导致性状结构的变化,特别是在环境波动的情况下,表型不稳定性可能是有益的。我们首先确定了一个与性状适应值函数形状有关的凸性原理,确定了复合结构应该是适应性的条件,或者相反,更常见的情况是应该被选择淘汰。然而,模拟结果表明,将这一原理应用于现实进化群体需要考虑系统中普遍存在的上位性相互作用。事实上,影响结构的突变的命运取决于(表)遗传背景,而遗传背景又取决于群体中的当前结构。我们通过借用进化生态学中的适应动力学框架来解决这个问题——在进化生态学中,它通常用于处理这种居民/突变体之间的相互依赖关系——并发现排除复合结构的原理通常占主导地位。然而,预测的进化轨迹通常取决于初始结构,可能导致历史偶然事件。最后,通过放宽对大群体规模的假设,我们意外地发现,不仅是对性状结构的选择强度,而且选择的方向都取决于群体规模,揭示了最近发现的被称为“符号反转”的现象的新出现。

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