Mehra Priyanka, Hintze Arend
Department for MicroData Analytics, Dalarna University, 791 88 Falun, Sweden.
BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, MI 48824, USA.
Biology (Basel). 2024 Dec 2;13(12):1003. doi: 10.3390/biology13121003.
Understanding the balance between robustness and evolvability is crucial in evolutionary dynamics. This study aims to determine how varying mutation rates and valley depths affect this interplay during adaptation. Using a two-peak fitness landscape model requiring populations to cross a fitness valley to reach a higher peak, we investigate how mutation rates and valley depths influence both evolvability-the capacity to generate beneficial mutations-and mutational robustness, which stabilizes populations at the highest peak. Our experiments reveal that at low mutation rates, populations struggle to cross fitness valleys, reducing the occurrence of pioneers. As mutation rates increase, valley crossing becomes more frequent, but organisms forming a majority at the highest peak are less common and tend to arise at intermediate mutation rates. Although pioneers reach the highest peak, they are often replaced by more mutationally robust organisms that later form a majority. This suggests that while evolvability aids in valley crossing, long-term stability at the highest peak requires greater mutational robustness. Our findings highlight that adaptations in epistasis and pleiotropy facilitate the trade-off between evolvability and robustness, providing insights into how organisms navigate complex fitness landscapes. These results can also inform the design of genetic algorithms that balance evolvability with robustness to optimize outcomes.
理解稳健性与进化能力之间的平衡在进化动力学中至关重要。本研究旨在确定不同的突变率和适应度低谷深度如何在适应过程中影响这种相互作用。我们使用一个双峰适应度景观模型,该模型要求种群跨越一个适应度低谷以达到更高的峰值,在此基础上,我们研究突变率和适应度低谷深度如何影响进化能力(即产生有益突变的能力)和突变稳健性,后者能使种群在最高峰处保持稳定。我们的实验表明,在低突变率下,种群难以跨越适应度低谷,先驱者出现的频率降低。随着突变率增加,跨越低谷变得更加频繁,但在最高峰处占多数的生物体变得不那么常见,且往往在中等突变率时出现。尽管先驱者能到达最高峰,但它们常常被后来占多数的、具有更强突变稳健性的生物体所取代。这表明,虽然进化能力有助于跨越适应度低谷,但在最高峰处的长期稳定性需要更强的突变稳健性。我们的研究结果强调,上位性和多效性中的适应性有助于在进化能力和稳健性之间进行权衡,为生物体如何在复杂的适应度景观中导航提供了见解。这些结果还可为平衡进化能力与稳健性以优化结果的遗传算法设计提供参考。