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SEGN:推断介导表型可塑性的实时基因网络。

SEGN: Inferring real-time gene networks mediating phenotypic plasticity.

作者信息

Jiang Libo, Griffin Christopher H, Wu Rongling

机构信息

Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing 100083, China.

Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China.

出版信息

Comput Struct Biotechnol J. 2020 Sep 5;18:2510-2521. doi: 10.1016/j.csbj.2020.08.029. eCollection 2020.

DOI:10.1016/j.csbj.2020.08.029
PMID:33005313
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7516210/
Abstract

The capacity of an organism to alter its phenotype in response to environmental perturbations changes over developmental time and is a process determined by multiple genes that are co-expressed in intricate but organized networks. Characterizing the spatiotemporal change of such gene networks can offer insight into the genomic signatures underlying organismic adaptation, but it represents a major methodological challenge. Here, we integrate the holistic view of systems biology and the interactive notion of evolutionary game theory to reconstruct so-called systems evolutionary game networks (SEGN) that can autonomously detect, track, and visualize environment-induced gene networks along the time axis. The SEGN overcomes the limitations of traditional approaches by inferring context-specific networks, encapsulating bidirectional, signed, and weighted gene-gene interactions into fully informative networks, and monitoring the process of how networks topologically alter across environmental and developmental cues. Based on the design principle of SEGN, we perform a transcriptional plasticity study by culturing Euphrates poplar, a tree that can grow in the saline desert, in saline-free and saline-stress conditions. SEGN characterize previously unknown gene co-regulation that modulates the time trajectories of the trees' response to salt stress. As a marriage of multiple disciplines, SEGN shows its potential to interpret gene interdependence, predict how transcriptional co-regulation responds to various regimes, and provides a hint for exploring the mass, energetic, or signal basis that drives various types of gene interactions.

摘要

生物体响应环境扰动改变其表型的能力会随发育时间而变化,且是一个由多个基因决定的过程,这些基因在复杂但有序的网络中共同表达。表征此类基因网络的时空变化有助于深入了解生物体适应背后的基因组特征,但这是一项重大的方法学挑战。在此,我们整合系统生物学的整体观点和进化博弈论的交互概念,以重建所谓的系统进化博弈网络(SEGN),该网络能够沿着时间轴自主检测、追踪并可视化环境诱导的基因网络。SEGN通过推断特定背景网络、将双向、有符号和加权的基因 - 基因相互作用封装到信息丰富的网络中以及监测网络如何在环境和发育线索下进行拓扑改变的过程,克服了传统方法的局限性。基于SEGN的设计原则,我们通过在无盐和盐胁迫条件下培养能够在盐碱沙漠中生长的胡杨,进行了转录可塑性研究。SEGN表征了以前未知的基因共调控,该共调控调节树木对盐胁迫响应的时间轨迹。作为多学科的结合,SEGN显示出解释基因相互依赖性、预测转录共调控如何响应各种情况的潜力,并为探索驱动各种类型基因相互作用的质量、能量或信号基础提供了线索。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3501/7516210/9f97405d3ce0/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3501/7516210/b19308039fe6/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3501/7516210/ba707f112aa9/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3501/7516210/170f3a242aae/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3501/7516210/5934b8d6109c/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3501/7516210/90f6ca1800be/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3501/7516210/9f97405d3ce0/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3501/7516210/b19308039fe6/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3501/7516210/ba707f112aa9/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3501/7516210/170f3a242aae/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3501/7516210/5934b8d6109c/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3501/7516210/90f6ca1800be/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3501/7516210/9f97405d3ce0/gr6.jpg

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