论文标题

在崎landscapes上变得更高:反转突变开放访问NK健身景观中的适合自适应峰

Getting higher on rugged landscapes: Inversion mutations open access to fitter adaptive peaks in NK fitness landscapes

论文作者

Trujillo, Leonardo, Banse, Paul, Beslon, Guillaume

论文摘要

分子进化通常被概念化为在坚固的健身景观上的自适应步行,受到突变驱动,并受到逐步适应性选择的约束。众所周知,上毒塑造了景观表面的坚固性,概述了它们的地形(高素质峰被低适应性基因型的山谷隔开)。但是,在强烈选择弱突变(SSWM)极限内,一旦自适应步行达到局部峰,自然选择就会限制穿过下游路径的通道,并阻碍任何可能达到更高适应性值的可能性。在这里,除了广泛使用的点突变外,我们还引入了序列反演的最小模型,以模拟自适应步行。我们使用众所周知的NK模型实例化崎landscapes。我们表明,自适应步行可以通过反演突变达到更高的适应性值,与点突变相比,该突变允许进化过程逃脱局部适应性峰。为了阐明这种染色体重排的效果,我们使用了可访问突变体的图理论表示,并显示了如何发现新的进化路径。本模型提出了一个简单的机理原理,可以分析由(内部)结构反演驱动的分子进化中局部适应性峰的逃逸,并揭示了分子进化模拟点突变的限制的某些后果。

Molecular evolution is often conceptualised as adaptive walks on rugged fitness landscapes, driven by mutations and constrained by incremental fitness selection. It is well known that epistasis shapes the ruggedness of the landscape's surface, outlining their topography (with high-fitness peaks separated by valleys of lower fitness genotypes). However, within the strong selection weak mutation (SSWM) limit, once an adaptive walk reaches a local peak, natural selection restricts passage through downstream paths and hampers any possibility of reaching higher fitness values. Here, in addition to the widely used point mutations, we introduce a minimal model of sequence inversions to simulate adaptive walks. We use the well known NK model to instantiate rugged landscapes. We show that adaptive walks can reach higher fitness values through inversion mutations, which, compared to point mutations, allows the evolutionary process to escape local fitness peaks. To elucidate the effects of this chromosomal rearrangement, we use a graph-theoretical representation of accessible mutants and show how new evolutionary paths are uncovered. The present model suggests a simple mechanistic rationale to analyse escapes from local fitness peaks in molecular evolution driven by (intragenic) structural inversions and reveals some consequences of the limits of point mutations for simulations of molecular evolution.

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