System-level insights into the cellular interactome of a non-model organism: inferring, modelling and analysing functional gene network of soybean (Glycine max).
System-level insights into the cellular interactome of a non-model organism: inferring, modelling and analysing functional gene network of soybean (Glycine max).
复制标题
对非模型生物细胞相互作用组的系统级洞察：大豆 (Glycine max) 功能基因网络的推断、建模和分析
DOI：
10.1371/journal.pone.0113907
复制
发表时间：
2014
期刊：
影响因子：
3.7
通讯作者：
Liu Y
中科院分区：
文献类型：
--
作者：
Xu Y;Guo M;Zou Q;Liu X;Wang C;Liu Y
细胞相互作用组，其中基因和/或其产物在几个水平上相互作用，形成转录调节网络、蛋白质相互作用网络、代谢网络、信号转导网络等，吸引了几十年的研究热点。然而，这种特定类型的网络本身很难解释基因之间的各种互动活动。这些网络表征了不同的相互作用关系，暗示了它们独特的内在属性和缺陷，并涵盖了不同的生物信息切片。功能基因网络（FGN）是一种整合的相互作用网络，它模拟了基因-基因关系的模糊和更广义的概念，已被提出用于联合收割机异构网络，其目标是识别由多种相互作用类型支持的功能模块。由于缺乏足够的异质性相互作用数据，目前还没有FGN在稀疏研究的非模式生物（如大豆）上成功的先例。我们提出了一个替代的解决方案，推断FGNs的大豆（FGNs），在大豆相互作用组的开创性研究，这也适用于其他生物。生物网络具有典型的生物网络特征：无标度、小世界结构和模块化。通过共表达和KEGG途径的验证，与来自拟南芥的同源网络相比，ERFGNs更广泛和准确。作为一个案例研究，网络引导的抗病基因发现表明，CRFGNs可以提供系统水平的基因功能和相互作用的研究。这项工作表明，推断和建模的非模型植物的相互作用组是可行的。它将加速发现和定义控制重要功能的其他基因的功能和相互作用，如固氮和蛋白质或脂质合成。本研究为我们进一步在基因组和microRNome水平上对大豆功能互作组进行全面研究奠定了基础。此外，还可在以下网址查阅一个网络工具，用于检索和分析可持续发展网络的信息：http://nclab.hit.edu.cn/SoyFN。
Cellular interactome, in which genes and/or their products interact on several levels, forming transcriptional regulatory-, protein interaction-, metabolic-, signal transduction networks, etc., has attracted decades of research focuses. However, such a specific type of network alone can hardly explain the various interactive activities among genes. These networks characterize different interaction relationships, implying their unique intrinsic properties and defects, and covering different slices of biological information. Functional gene network (FGN), a consolidated interaction network that models fuzzy and more generalized notion of gene-gene relations, have been proposed to combine heterogeneous networks with the goal of identifying functional modules supported by multiple interaction types. There are yet no successful precedents of FGNs on sparsely studied non-model organisms, such as soybean (Glycine max), due to the absence of sufficient heterogeneous interaction data. We present an alternative solution for inferring the FGNs of soybean (SoyFGNs), in a pioneering study on the soybean interactome, which is also applicable to other organisms. SoyFGNs exhibit the typical characteristics of biological networks: scale-free, small-world architecture and modularization. Verified by co-expression and KEGG pathways, SoyFGNs are more extensive and accurate than an orthology network derived from Arabidopsis. As a case study, network-guided disease-resistance gene discovery indicates that SoyFGNs can provide system-level studies on gene functions and interactions. This work suggests that inferring and modelling the interactome of a non-model plant are feasible. It will speed up the discovery and definition of the functions and interactions of other genes that control important functions, such as nitrogen fixation and protein or lipid synthesis. The efforts of the study are the basis of our further comprehensive studies on the soybean functional interactome at the genome and microRNome levels. Additionally, a web tool for information retrieval and analysis of SoyFGNs can be accessed at SoyFN: http://nclab.hit.edu.cn/SoyFN.
登录
查看更多内容
影响因子：
4.3
作者：
Guan Y;Myers CL;Lu R;Lemischka IR;Bult CJ;Troyanskaya OG
通讯作者：
Troyanskaya OG
影响因子：
12.3
作者：
Peña-Castillo L;Tasan M;Myers CL;Lee H;Joshi T;Zhang C;Guan Y;Leone M;Pagnani A;Kim WK;Krumpelman C;Tian W;Obozinski G;Qi Y;Mostafavi S;Lin GN;Berriz GF;Gibbons FD;Lanckriet G;Qiu J;Grant C;Barutcuoglu Z;Hill DP;Warde-Farley D;Grouios C;Ray D;Blake JA;Deng M;Jordan MI;Noble WS;Morris Q;Klein-Seetharaman J;Bar-Joseph Z;Chen T;Sun F;Troyanskaya OG;Marcotte EM;Xu D;Hughes TR;Roth FP
通讯作者：
Roth FP
影响因子：
12.3
作者：
Kim WK;Krumpelman C;Marcotte EM
通讯作者：
Marcotte EM
影响因子：
64.8
作者：
Marcotte, EM;Pellegrini, M;Eisenberg, D
通讯作者：
Eisenberg, D
影响因子：
14.9
作者：
Barrett T;Troup DB;Wilhite SE;Ledoux P;Rudnev D;Evangelista C;Kim IF;Soboleva A;Tomashevsky M;Marshall KA;Phillippy KH;Sherman PM;Muertter RN;Edgar R
通讯作者：
Edgar R