Monotonicity of fitness landscapes and mutation rate control.

Monotonicity of fitness landscapes and mutation rate control.
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DOI:
10.1007/s00285-016-0995-3
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发表时间:
2016-12
影响因子:
1.9
通讯作者:
Knight, Christopher G.
Knight, Christopher G.
中科院分区:
数学4区
文献类型:
--
作者:
Belavkin, Roman V.;Channon, Alastair;Aston, Elizabeth;Aston, John;Krasovec, Rok;Knight, Christopher G.

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进化生物学中的一个普遍观点是突变率被最小化。然而,在组合优化和搜索的研究已经显示出一个明显的优势,使用可变的突变率作为控制参数,以优化性能的进化算法。这一领域的许多生物学理论都是基于罗纳德·费舍尔的工作,他使用欧几里得几何来研究突变大小与无限表型空间中后代预期适应度之间的关系。在这里,我们重新考虑这一理论的基础上的替代几何的离散和有限空间的DNA序列。首先,我们考虑的几何情况下的健身同构的距离从一个最佳的,并显示如何最佳的突变率控制问题可以解决的精确或近似取决于额外的约束条件的问题。然后,我们考虑一般情况下的健身通信的距离只有部分信息。我们定义了适应度景观的弱单调性,并证明了该性质在所有连续且在最佳状态下开放的景观中成立。这一理论结果激发了我们的假设,在这样的景观最佳突变率函数将增加时,健身最佳的一些邻域减少,类似的控制功能在几何的情况下。我们通过分析DNA序列和转录因子之间的结合分数的115个完整景观中的近似最佳突变率控制函数来实验测试这一假设。我们的研究结果支持了这一假设,并发现突变率的增加是更迅速的景观,是不那么单调(更崎岖)。我们将讨论这些发现与生物体的相关性。本文的在线版本(doi:10.1007/s 00285 -016-0995-3)包含补充材料,可供授权用户使用。
A common view in evolutionary biology is that mutation rates are minimised. However, studies in combinatorial optimisation and search have shown a clear advantage of using variable mutation rates as a control parameter to optimise the performance of evolutionary algorithms. Much biological theory in this area is based on Ronald Fisher’s work, who used Euclidean geometry to study the relation between mutation size and expected fitness of the offspring in infinite phenotypic spaces. Here we reconsider this theory based on the alternative geometry of discrete and finite spaces of DNA sequences. First, we consider the geometric case of fitness being isomorphic to distance from an optimum, and show how problems of optimal mutation rate control can be solved exactly or approximately depending on additional constraints of the problem. Then we consider the general case of fitness communicating only partial information about the distance. We define weak monotonicity of fitness landscapes and prove that this property holds in all landscapes that are continuous and open at the optimum. This theoretical result motivates our hypothesis that optimal mutation rate functions in such landscapes will increase when fitness decreases in some neighbourhood of an optimum, resembling the control functions derived in the geometric case. We test this hypothesis experimentally by analysing approximately optimal mutation rate control functions in 115 complete landscapes of binding scores between DNA sequences and transcription factors. Our findings support the hypothesis and find that the increase of mutation rate is more rapid in landscapes that are less monotonic (more rugged). We discuss the relevance of these findings to living organisms. The online version of this article (doi:10.1007/s00285-016-0995-3) contains supplementary material, which is available to authorized users.
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