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Fluctuating environments select for short-term phenotypic variation leading to long-term exploration

机译:波动的环境选择了短期表型变异从而导致了长期探索

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摘要

Genetic spaces are often described in terms of fitness landscapes or genotype-to-phenotype maps, where each genetic sequence is associated with phenotypic properties and linked to other genotypes that are a single mutational step away. The positions close to a genotype make up its “mutational landscape” and, in aggregate, determine the short-term evolutionary potential of a population. Populations with wider ranges of phenotypes in their mutational neighborhood are known to be more evolvable. Likewise, those with fewer phenotypic changes available in their local neighborhoods are more mutationally robust. Here, we examine whether forces that change the distribution of phenotypes available by mutation profoundly alter subsequent evolutionary dynamics. We compare evolved populations of digital organisms that were subject to either static or cyclically-changing environments. For each of these, we examine diversity of the phenotypes that are produced through mutations in order to characterize the local genotype-phenotype map. We demonstrate that environmental change can push populations toward more evolvable mutational landscapes where many alternate phenotypes are available, though purely deleterious mutations remain suppressed. Further, we show that populations in environments with harsh changes switch phenotypes more readily than those in environments with more benign changes. We trace this effect to repeated population bottlenecks in the harsh environments, which result in shorter coalescence times and keep populations in regions of the mutational landscape where the phenotypic shifts in question are more likely to occur. Typically, static environments select solely for immediate optimization, at the expensive of long-term evolvability. In contrast, we show that with changing environments, short-term pressures to deal with immediate challenges can align with long-term pressures to explore a more productive portion of the mutational landscape.
机译:遗传空间通常用适应度图或基因型到表型的图来描述,其中每个遗传序列都与表型特性相关,并与单个突变步骤相距的其他基因型相关。接近基因型的位置构成其“变异景观”,总的来说,决定了种群的短期进化潜力。已知在其突变邻域中具有较宽表型范围的种群具有更高的进化性。同样,那些在其本地邻域中可利用的表型变化较少的突变体在突变上也更强大。在这里,我们研究了通过突变改变表型分布的力量是否会深刻改变随后的进化动力学。我们比较了处于静态或周期性变化环境下的数字生物进化种群。对于每种方法,我们研究通过突变产生的表型多样性,以表征局部基因型-表型图。我们证明了环境变化可以将种群推向更易进化的突变景观,尽管许多有害的突变仍然被抑制,但在这些突变景观中存在许多其他的表型。此外,我们表明,在环境发生剧烈变化的情况下,种群的表型切换要比在环境发生良性变化的情况下更容易切换表型。我们将此效应追溯到恶劣环境中反复出现的种群瓶颈,这导致合并时间缩短,并使种群保持在突变景观的区域中,在该区域中,有关表型发生转移的可能性更大。通常,静态环境只选择立即进行优化,而代价是长期的可扩展性。相比之下,我们表明,随着环境的变化,应对紧迫挑战的短期压力可以与探索突变景观中更具生产力的部分的长期压力相吻合。

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