Matsumoto Tomotaka, Mineta Katsuhiko, Osada Naoki, Araki Hitoshi
Graduate School of Systems Life Sciences, Kyushu University Fukuoka, Japan ; Department of Population Genetics, National Institute of Genetics Mishima, Japan.
Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST) Thuwal, Saudi Arabia.
Front Genet. 2015 Nov 24;6:336. doi: 10.3389/fgene.2015.00336. eCollection 2015.
Recent studies suggest the existence of a stochasticity in gene expression (SGE) in many organisms, and its non-negligible effect on their phenotype and fitness. To date, however, how SGE affects the key parameters of population genetics are not well understood. SGE can increase the phenotypic variation and act as a load for individuals, if they are at the adaptive optimum in a stable environment. On the other hand, part of the phenotypic variation caused by SGE might become advantageous if individuals at the adaptive optimum become genetically less-adaptive, for example due to an environmental change. Furthermore, SGE of unimportant genes might have little or no fitness consequences. Thus, SGE can be advantageous, disadvantageous, or selectively neutral depending on its context. In addition, there might be a genetic basis that regulates magnitude of SGE, which is often referred to as "modifier genes," but little is known about the conditions under which such an SGE-modifier gene evolves. In the present study, we conducted individual-based computer simulations to examine these conditions in a diploid model. In the simulations, we considered a single locus that determines organismal fitness for simplicity, and that SGE on the locus creates fitness variation in a stochastic manner. We also considered another locus that modifies the magnitude of SGE. Our results suggested that SGE was always deleterious in stable environments and increased the fixation probability of deleterious mutations in this model. Even under frequently changing environmental conditions, only very strong natural selection made SGE adaptive. These results suggest that the evolution of SGE-modifier genes requires strict balance among the strength of natural selection, magnitude of SGE, and frequency of environmental changes. However, the degree of dominance affected the condition under which SGE becomes advantageous, indicating a better opportunity for the evolution of SGE in different genetic models.
近期研究表明，许多生物体中存在基因表达随机性（SGE），且其对生物体的表型和适应性有着不可忽视的影响。然而，迄今为止，SGE如何影响群体遗传学的关键参数仍未得到充分理解。如果生物体处于稳定环境中的适应性最优状态，SGE会增加表型变异并对个体构成负担。另一方面，如果处于适应性最优状态的个体因环境变化等原因在遗传上变得适应性降低，那么由SGE引起的部分表型变异可能会变得有利。此外，不重要基因的SGE可能对适应性影响很小或没有影响。因此，SGE根据其所处环境可能是有利的、不利的或选择性中性的。此外，可能存在调控SGE大小的遗传基础，通常称为“修饰基因”，但对于这种SGE修饰基因进化的条件知之甚少。在本研究中，我们进行了基于个体的计算机模拟，以在二倍体模型中研究这些条件。在模拟中，为简化起见，我们考虑了一个决定生物体适应性的单一位点，该位点上的SGE以随机方式产生适应性变异。我们还考虑了另一个修饰SGE大小的位点。我们的结果表明，在稳定环境中SGE总是有害的，并增加了该模型中有害突变的固定概率。即使在频繁变化的环境条件下，只有非常强烈的自然选择才能使SGE具有适应性。这些结果表明，SGE修饰基因的进化需要自然选择强度、SGE大小和环境变化频率之间的严格平衡。然而，显性程度影响SGE变得有利的条件，这表明在不同的遗传模型中SGE进化的机会更好。
