Gong Huiying, Zhu Sheng, Zhu Xuli, Fang Qing, Zhang Xiao-Yu, Wu Rongling
College of Science, Beijing Forestry University, Beijing, China.
College of Biology and the Environment, Nanjing Forestry University, Nanjing, China.
Front Genet. 2021 Nov 12;12:769688. doi: 10.3389/fgene.2021.769688. eCollection 2021.
The effects of genes on physiological and biochemical processes are interrelated and interdependent; it is common for genes to express pleiotropic control of complex traits. However, the study of gene expression and participating pathways at the whole-genome level is challenging. Here, we develop a coupled regulatory interaction differential equation to assess overall and independent genetic effects on trait growth. Based on evolutionary game theory and developmental modularity theory, we constructed multilayer, omnigenic networks of bidirectional, weighted, and positive or negative epistatic interactions using a forest poplar tree mapping population, which were organized into metagalactic, intergalactic, and local interstellar networks that describe layers of structure between modules, submodules, and individual single nucleotide polymorphisms, respectively. These multilayer interactomes enable the exploration of complex interactions between genes, and the analysis of not only differential expression of quantitative trait loci but also previously uncharacterized determinant SNPs, which are negatively regulated by other SNPs, based on the deconstruction of genetic effects to their component parts. Our research framework provides a tool to comprehend the pleiotropic control of complex traits and explores the inherent directional connections between genes in the structure of omnigenic networks.
基因对生理和生化过程的影响是相互关联和相互依存的；基因对复杂性状进行多效性控制是很常见的。然而，在全基因组水平上研究基因表达和参与的途径具有挑战性。在这里，我们开发了一个耦合调控相互作用微分方程，以评估对性状生长的整体和独立遗传效应。基于进化博弈论和发育模块理论，我们利用一个杨树映射群体构建了多层、全基因组的双向、加权和正负上位性相互作用网络，这些网络分别被组织成描述模块、子模块和单个单核苷酸多态性之间结构层次的星系际、星系间和局部星际网络。这些多层相互作用组能够探索基因之间的复杂相互作用，不仅可以分析数量性状位点的差异表达，还可以基于将遗传效应解构为其组成部分，分析以前未表征的决定性单核苷酸多态性，这些单核苷酸多态性受到其他单核苷酸多态性的负调控。我们的研究框架提供了一个工具，以理解复杂性状的多效性控制，并探索全基因组网络结构中基因之间固有的定向联系。
