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在理查德·道金斯的生物形态中,变异的出现偏差可以超过自然选择。

Bias in the arrival of variation can dominate over natural selection in Richard Dawkins's biomorphs.

机构信息

Rudolf Peierls Centre for Theoretical Physics, University of Oxford, Oxford, United Kingdom.

College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, United Kingdom.

出版信息

PLoS Comput Biol. 2024 Mar 27;20(3):e1011893. doi: 10.1371/journal.pcbi.1011893. eCollection 2024 Mar.

DOI:10.1371/journal.pcbi.1011893
PMID:38536880
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10971585/
Abstract

Biomorphs, Richard Dawkins's iconic model of morphological evolution, are traditionally used to demonstrate the power of natural selection to generate biological order from random mutations. Here we show that biomorphs can also be used to illustrate how developmental bias shapes adaptive evolutionary outcomes. In particular, we find that biomorphs exhibit phenotype bias, a type of developmental bias where certain phenotypes can be many orders of magnitude more likely than others to appear through random mutations. Moreover, this bias exhibits a strong preference for simpler phenotypes with low descriptional complexity. Such bias towards simplicity is formalised by an information-theoretic principle that can be intuitively understood from a picture of evolution randomly searching in the space of algorithms. By using population genetics simulations, we demonstrate how moderately adaptive phenotypic variation that appears more frequently upon random mutations can fix at the expense of more highly adaptive biomorph phenotypes that are less frequent. This result, as well as many other patterns found in the structure of variation for the biomorphs, such as high mutational robustness and a positive correlation between phenotype evolvability and robustness, closely resemble findings in molecular genotype-phenotype maps. Many of these patterns can be explained with an analytic model based on constrained and unconstrained sections of the genome. We postulate that the phenotype bias towards simplicity and other patterns biomorphs share with molecular genotype-phenotype maps may hold more widely for developmental systems.

摘要

生物形态,理查德·道金斯标志性的形态进化模型,传统上用于展示自然选择从随机突变中产生生物秩序的力量。在这里,我们表明生物形态也可以用来说明发育偏向如何塑造适应性进化结果。特别是,我们发现生物形态表现出表型偏向,这是一种发育偏向,其中某些表型通过随机突变出现的可能性要高出许多数量级。此外,这种偏向强烈倾向于具有低描述复杂性的简单表型。这种对简单性的偏向由一个信息论原理来形式化,该原理可以从算法空间中随机搜索的进化图中直观地理解。通过使用群体遗传学模拟,我们展示了在随机突变中出现频率更高的适度适应性表型变异如何能够固定下来,而代价是更高度适应性的生物形态表型,它们的出现频率较低。这一结果以及在生物形态的变异结构中发现的许多其他模式,如高突变稳健性和表型可进化性与稳健性之间的正相关,与分子基因型-表型图谱中的发现非常相似。许多这些模式可以用基于基因组的约束和非约束部分的分析模型来解释。我们假设,生物形态的表型简单性偏向和与分子基因型-表型图谱共享的其他模式可能更广泛地适用于发育系统。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6087/10971585/13708d85c187/pcbi.1011893.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6087/10971585/1efbb9061063/pcbi.1011893.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6087/10971585/e39af4c6e074/pcbi.1011893.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6087/10971585/c3007accf59a/pcbi.1011893.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6087/10971585/86f84d996ee7/pcbi.1011893.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6087/10971585/329ffe545414/pcbi.1011893.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6087/10971585/327345963a7b/pcbi.1011893.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6087/10971585/3abaaf0d25e8/pcbi.1011893.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6087/10971585/66b49bb04145/pcbi.1011893.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6087/10971585/13708d85c187/pcbi.1011893.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6087/10971585/1efbb9061063/pcbi.1011893.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6087/10971585/e39af4c6e074/pcbi.1011893.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6087/10971585/c3007accf59a/pcbi.1011893.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6087/10971585/86f84d996ee7/pcbi.1011893.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6087/10971585/329ffe545414/pcbi.1011893.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6087/10971585/327345963a7b/pcbi.1011893.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6087/10971585/3abaaf0d25e8/pcbi.1011893.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6087/10971585/66b49bb04145/pcbi.1011893.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6087/10971585/13708d85c187/pcbi.1011893.g009.jpg

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The Boltzmann distributions of molecular structures predict likely changes through random mutations.分子结构的玻尔兹曼分布预测了通过随机突变可能发生的变化。
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Maximum mutational robustness in genotype-phenotype maps follows a self-similar blancmange-like curve.
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