低影响突变对数字生物的影响。

Chase W Nelson, John C Sanford
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引用次数: 18

摘要

背景:Avida是一个用数字生物进行进化实验的计算机程序。以前的工作已经使用该程序来研究复杂特征的进化起源,即逻辑运算,但一直使用非常大的突变适应度效应。目前的研究使用了Avida来更好地理解低影响突变在进化中的作用。结果:当突变适应度效应约为0.075或更低时,没有新的逻辑运算进化,先前进化的逻辑运算丢失。当适应度效应约为0.2时,只有一半的操作进化,这反映了选择失败的阈值。相比之下,当使用Avida的默认适应度效应时,所有操作通常都会进化到高频率,而适应度仅在10,000代内平均增加了2000万。结论:阿维德生物只有在产生它们的突变被赋予高影响适应度效应时才会进化出新的逻辑运算。此外,净化选择不能保护具有低影响效益的操作免受突变恶化的影响。这些结果表明,低于一定适应度效应(即选择阈值)的低影响突变会导致选择中断。使用生物学相关参数设置的实验显示增加遗传负荷导致生物功能丧失的趋势。对这种遗传退化的了解与人类疾病有关,并且可能适用于通过使用致命诱变来控制病原体。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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The effects of low-impact mutations in digital organisms.

Background: Avida is a computer program that performs evolution experiments with digital organisms. Previous work has used the program to study the evolutionary origin of complex features, namely logic operations, but has consistently used extremely large mutational fitness effects. The present study uses Avida to better understand the role of low-impact mutations in evolution.

Results: When mutational fitness effects were approximately 0.075 or less, no new logic operations evolved, and those that had previously evolved were lost. When fitness effects were approximately 0.2, only half of the operations evolved, reflecting a threshold for selection breakdown. In contrast, when Avida's default fitness effects were used, all operations routinely evolved to high frequencies and fitness increased by an average of 20 million in only 10,000 generations.

Conclusions: Avidian organisms evolve new logic operations only when mutations producing them are assigned high-impact fitness effects. Furthermore, purifying selection cannot protect operations with low-impact benefits from mutational deterioration. These results suggest that selection breaks down for low-impact mutations below a certain fitness effect, the selection threshold. Experiments using biologically relevant parameter settings show the tendency for increasing genetic load to lead to loss of biological functionality. An understanding of such genetic deterioration is relevant to human disease, and may be applicable to the control of pathogens by use of lethal mutagenesis.

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来源期刊
Theoretical Biology and Medical Modelling
Theoretical Biology and Medical Modelling MATHEMATICAL & COMPUTATIONAL BIOLOGY-
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期刊介绍: Theoretical Biology and Medical Modelling is an open access peer-reviewed journal adopting a broad definition of "biology" and focusing on theoretical ideas and models associated with developments in biology and medicine. Mathematicians, biologists and clinicians of various specialisms, philosophers and historians of science are all contributing to the emergence of novel concepts in an age of systems biology, bioinformatics and computer modelling. This is the field in which Theoretical Biology and Medical Modelling operates. We welcome submissions that are technically sound and offering either improved understanding in biology and medicine or progress in theory or method.
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