Rünneburger Estelle, Le Rouzic Arnaud
Laboratoire Évolution, Génomes, Comportement, Écologie, CNRS-IRD-Univ. Paris-Sud-Université Paris-Saclay, Gif-sur-Yvette, 91198, France.
BMC Evol Biol. 2016 Nov 8;16(1):239. doi: 10.1186/s12862-016-0801-2.
Genetic canalization reflects the capacity of an organism's phenotype to remain unchanged in spite of mutations. As selection on genetic canalization is weak and indirect, whether or not genetic canalization can reasonably evolve in complex genetic architectures is still an open question. In this paper, we use a quantitative model of gene regulatory network to describe the conditions in which substantial canalization is expected to emerge in a stable environment.
Through an individual-based simulation framework, we confirmed that most parameters associated with the network topology (complexity and size of the network) have less influence than mutational parameters (rate and size of mutations) on the evolution of genetic canalization. We also established that selecting for extreme phenotypic optima (nil or full gene expression) leads to much higher canalization levels than selecting for intermediate expression levels. Overall, constrained networks evolve less canalization than networks in which some genes could evolve freely (i.e. without direct stabilizing selection pressure on gene expression).
Taken together, these results lead us to propose a two-fold mechanism involved in the evolution of genetic canalization in gene regulatory networks: the shrinkage of mutational target (useless genes are virtually removed from the network) and redundancy in gene regulation (so that some regulatory factors can be lost without affecting gene expression).
遗传稳态反映了生物体的表型在尽管发生突变的情况下仍保持不变的能力。由于对遗传稳态的选择是微弱且间接的,在复杂的遗传结构中遗传稳态是否能够合理地进化仍是一个悬而未决的问题。在本文中,我们使用基因调控网络的定量模型来描述在稳定环境中预期会出现显著稳态的条件。
通过基于个体的模拟框架,我们证实与网络拓扑结构相关的大多数参数(网络的复杂性和大小)对遗传稳态进化的影响小于突变参数(突变的速率和大小)。我们还确定,选择极端表型最优值(零或全基因表达)比选择中间表达水平导致更高的稳态水平。总体而言,受约束的网络比一些基因可以自由进化的网络(即对基因表达没有直接稳定选择压力的网络)进化出的稳态更少。
综上所述,这些结果使我们提出了一种涉及基因调控网络中遗传稳态进化的双重机制:突变靶点的收缩(无用基因实际上从网络中被去除)和基因调控中的冗余(以便一些调控因子可以丢失而不影响基因表达)。