IEEE/ACM Trans Comput Biol Bioinform. 2018 May-Jun;15(3):878-891. doi: 10.1109/TCBB.2017.2653110. Epub 2017 Jan 16.
Finding regulatory relationships between genes, including the direction and nature of influence between them, is a fundamental challenge in the field of molecular genetics. One classical approach to this problem is epistasis analysis. Broadly speaking, epistasis analysis infers the regulatory relationships between a pair of genes in a genetic pathway by considering the patterns of change in an observable trait resulting from single and double deletion of genes. While classical epistasis analysis has yielded deep insights on numerous genetic pathways, it is not without limitations. Here, we explore the possibility of dynamic epistasis analysis, in which, in addition to performing genetic perturbations of a pathway, we drive the pathway by a time-varying upstream signal. We explore the theoretical power of dynamical epistasis analysis by conducting an identifiability analysis of Boolean models of genetic pathways, comparing static and dynamic approaches. We find that even relatively simple input dynamics greatly increases the power of epistasis analysis to discriminate alternative network structures. Further, we explore the question of experiment design, and show that a subset of short time-varying signals, which we call dynamic primitives, allow maximum discriminative power with a reduced number of experiments.
发现基因之间的调控关系，包括它们之间的影响方向和性质，是分子遗传学领域的一个基本挑战。解决这个问题的一种经典方法是上位性分析。广义而言，通过考虑单个和双基因缺失导致可观察性状变化的模式，上位性分析可以推断遗传途径中一对基因之间的调控关系。虽然经典的上位性分析对许多遗传途径产生了深刻的见解，但它并非没有局限性。在这里，我们探讨了动态上位性分析的可能性，即在对途径进行遗传扰动的同时，我们还通过时变的上游信号来驱动途径。我们通过对遗传途径的布尔模型进行可识别性分析，比较静态和动态方法，来探索动态上位性分析的理论能力。我们发现，即使是相对简单的输入动态也大大增加了上位性分析区分替代网络结构的能力。此外，我们还探讨了实验设计的问题，并表明，我们称之为动态原语的一小部分短时间变化的信号，可以用较少的实验获得最大的区分能力。
