Developing integrated crop knowledge networks to advance candidate gene discovery.
Developing integrated crop knowledge networks to advance candidate gene discovery.
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DOI：
10.1016/j.atg.2016.10.003
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发表时间：
2016-12
期刊：
影响因子：
--
通讯作者：
Rawlings, Christopher
中科院分区：
文献类型：
--
作者：
Hassani-Pak, Keywan;Castellote, Martin;Esch, Maria;Hindle, Matthew;Lysenko, Artem;Taubert, Jan;Rawlings, Christopher
如果我们能够全面了解支撑作物产量、抗病性或养分和水分利用效率等性状的所有生物机制，提高作物生产力以加强全球粮食安全的机会将大大增加。随着越来越多的作物基因组不断涌现，我们更接近于在基因水平上获得基本信息，从而开始组装作物基因目录，并利用其他植物物种的数据来了解基因如何发挥作用，以及它们之间的相互作用如何控制作物的发育和生理。不幸的是，创建这样一个完整的基因功能，相互作用网络和性状生物学知识库的任务在技术上是具有挑战性的，因为相关的数据分散在无数的数据库中的各种数据格式与可变的质量和覆盖范围。在本文中，我们提出了一个通用的方法来构建基因组规模的知识网络，提供了一个统一的表示异构，但相互关联的数据集，使有效的知识挖掘和基因发现。我们描述了数据集，并概述了我们为主要作物物种小麦和大麦创建和可视化这些网络而开发的方法，工作流程和工具。我们提出了这样的知识网络的全球性特点，并与一个例子连接的种子大小表型的大麦WRKY转录因子从拟南芥TTG2的orthopathic，我们说明了生物知识发现的综合数据的价值。我们开发的软件（www.ondex.org）和我们创建的知识资源（knetminer.rothamsted.ac.uk）都是开放源代码的，为系统和循证基因发现迈出了第一步，以促进作物改良。
The chances of raising crop productivity to enhance global food security would be greatly improved if we had a complete understanding of all the biological mechanisms that underpinned traits such as crop yield, disease resistance or nutrient and water use efficiency. With more crop genomes emerging all the time, we are nearer having the basic information, at the gene-level, to begin assembling crop gene catalogues and using data from other plant species to understand how the genes function and how their interactions govern crop development and physiology. Unfortunately, the task of creating such a complete knowledge base of gene functions, interaction networks and trait biology is technically challenging because the relevant data are dispersed in myriad databases in a variety of data formats with variable quality and coverage. In this paper we present a general approach for building genome-scale knowledge networks that provide a unified representation of heterogeneous but interconnected datasets to enable effective knowledge mining and gene discovery. We describe the datasets and outline the methods, workflows and tools that we have developed for creating and visualising these networks for the major crop species, wheat and barley. We present the global characteristics of such knowledge networks and with an example linking a seed size phenotype to a barley WRKY transcription factor orthologous to TTG2 from Arabidopsis, we illustrate the value of integrated data in biological knowledge discovery. The software we have developed (www.ondex.org) and the knowledge resources (http://knetminer.rothamsted.ac.uk) we have created are all open-source and provide a first step towards systematic and evidence-based gene discovery in order to facilitate crop improvement.
DOI：
10.1093/bioinformatics/btr134
发表时间：
2011-05-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Weile J;Pocock M;Cockell SJ;Lord P;Dewar JM;Holstein EM;Wilkinson D;Lydall D;Hallinan J;Wipat A
通讯作者：
Wipat A