A computational investigation of cis-gene regulation in evolution.

IF 1.3 4区 生物学 Q3 BIOLOGY
Mohammed Mahmud, Mulugeta Bekele, Narayan Behera
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Abstract

In biological processes involving gene networks, genes regulate other genes that determine the phenotypic traits. Gene regulation plays an important role in evolutionary dynamics. In a genetic algorithm, a trans-gene regulatory mechanism was shown to speed up adaptation and evolution. Here, we examine the effect of cis-gene regulation on an adaptive system. The model is haploid. A chromosome is partitioned into regulatory loci and structural loci. The regulatory genes regulate the expression and functioning of structural genes via the cis-elements in a probabilistic manner. In the simulation, the change in the allele frequency, the mean population fitness and the efficiency of phenotypic selection are monitored. Cis-gene regulation increases adaption and accelerates the evolutionary process in comparison with the case involving absence of gene regulation. Some special features of the simulation results are as follows. A low ratio of regulatory loci and structural loci gives higher adaptation for fixed total number of loci. Plasticity is advantageous beyond a threshold value. Adaptation is better for large number of total loci when the ratio of regulatory loci to structural loci is one. However, it reaches a saturation beyond which the increase in the total loci is not advantageous. Efficiency of the phenotypic selection is higher for larger value of the initial plasticity.

Abstract Image

进化中顺式基因调控的计算研究。
在涉及基因网络的生物学过程中,基因调节决定表型性状的其他基因。基因调控在进化动力学中起着重要作用。在遗传算法中,一种转基因调控机制被证明可以加速适应和进化。在这里,我们研究顺式基因调控对适应性系统的影响。模型为单倍体。染色体分为调节位点和结构位点。调控基因通过顺式元件以概率方式调控结构基因的表达和功能。在模拟中,监测了等位基因频率、平均种群适应度和表型选择效率的变化。与缺乏基因调控的情况相比,顺式基因调控增加了适应性,加速了进化过程。仿真结果的一些特点如下:调节位点与结构位点的比例较低,对固定总数的位点具有较高的适应性。超过阈值后,可塑性是有利的。当调控位点与结构位点之比为1时,总位点数量较多,适应性较好。然而,它达到一个饱和,超过这个饱和,总位点的增加是不利的。初始可塑性值越大,表型选择效率越高。
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来源期刊
Theory in Biosciences
Theory in Biosciences 生物-生物学
CiteScore
2.70
自引率
9.10%
发文量
21
审稿时长
3 months
期刊介绍: Theory in Biosciences focuses on new concepts in theoretical biology. It also includes analytical and modelling approaches as well as philosophical and historical issues. Central topics are: Artificial Life; Bioinformatics with a focus on novel methods, phenomena, and interpretations; Bioinspired Modeling; Complexity, Robustness, and Resilience; Embodied Cognition; Evolutionary Biology; Evo-Devo; Game Theoretic Modeling; Genetics; History of Biology; Language Evolution; Mathematical Biology; Origin of Life; Philosophy of Biology; Population Biology; Systems Biology; Theoretical Ecology; Theoretical Molecular Biology; Theoretical Neuroscience & Cognition.
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