Robustness, evolvability, and the logic of genetic regulation.
Robustness, evolvability, and the logic of genetic regulation.
复制标题
鲁棒性、进化性和遗传调控的逻辑。
DOI：
10.1162/artl_a_00099
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发表时间：
2014
期刊：
影响因子：
2.6
通讯作者：
Wagner,Andreas
中科院分区：
文献类型：
--
作者：
Payne,JoshuaL;Moore,JasonH;Wagner,Andreas
在基因调节回路中，单个基因的表达通常由一组调节基因产物调节，这些产物与基因的剪切调节区结合。该区域编码输入-输出功能，称为信号整合逻辑，其将调控信号（输入）的特定组合映射到基因的特定表达状态（输出）。所有可能的信号整合函数的空间是巨大的，从输入到输出的映射是多对一的：对于同一组输入，许多函数（基因型）产生相同的表达输出（表型）。在这里，我们详尽地列举了一组信号整合功能，产生相同的基因表达模式内的基因调控电路的计算模型。我们的目标是表征鲁棒性和可进化性之间的关系，在信号集成空间的监管电路，并了解这些属性之间的基因型和表型尺度的变化。在其他结果中，我们发现，基因型的鲁棒性的分布是偏斜的，所以大多数的信号集成功能是强大的扰动。我们表明，连接的一组基因型，使一个给定的表型被限制到空间的所有可能的信号整合功能的特定区域，但随着基因型之间的距离增加，所以他们的能力独特的创新。此外，我们发现，强大的表型是（i）进化，（ii）容易识别的随机突变，（iii）突变偏向于其他强大的表型。我们通过在随机选择的源表型和目标表型之间进行随机游走来探索这些后一种观察对基于突变的进化的影响。我们证明，所需的时间来确定目标表型是独立的源表型的属性。
In gene regulatory circuits, the expression of individual genes is commonly modulated by a set of regulating gene products, which bind to a gene'scis-regulatory region. This region encodes an input-output function, referred to as signal-integration logic, that maps a specific combination of regulatory signals (inputs) to a particular expression state (output) of a gene. The space of all possible signal-integration functions is vast and the mapping from input to output is many-to-one: For the same set of inputs, many functions (genotypes) yield the same expression output (phenotype). Here, we exhaustively enumerate the set of signal-integration functions that yield identical gene expression patterns within a computational model of gene regulatory circuits. Our goal is to characterize the relationship between robustness and evolvability in the signal-integration space of regulatory circuits, and to understand how these properties vary between the genotypic and phenotypic scales. Among other results, we find that the distributions of genotypic robustness are skewed, so that the majority of signal-integration functions are robust to perturbation. We show that the connected set of genotypes that make up a given phenotype are constrained to specific regions of the space of all possible signal-integration functions, but that as the distance between genotypes increases, so does their capacity for unique innovations. In addition, we find that robust phenotypes are (i) evolvable, (ii) easily identified by random mutation, and (iii) mutationally biased toward other robust phenotypes. We explore the implications of these latter observations for mutation-based evolution by conducting random walks between randomly chosen source and target phenotypes. We demonstrate that the time required to identify the target phenotype is independent of the properties of the source phenotype.