Department of Biology and Duke Center for Systems Biology, Duke University, Durham, NC, USA.
Curr Opin Plant Biol. 2012 Apr;15(2):162-7. doi: 10.1016/j.pbi.2012.01.004. Epub 2012 Jan 23.
Genome-scale studies hold great promise for revealing novel plant biology. Because of the complexity of these techniques, numerous considerations need to be made before embarking on a study. Here we focus on the Arabidopsis model system because of the wealth of available genome-scale data. Many approaches are available that provide genome-scale information regarding the state of a given organism (e.g. genomics, epigenomics, transcriptomics, proteomics, metabolomics interactomics, ionomics, phenomics, etc.). Integration of all of these types of data will be necessary for a comprehensive description of Arabidopsis. In this review we propose that 'triangulation' among transcriptomics, proteomics and metabolomics is a meaningful approach for beginning this integrative analysis and uncovering a systems level perspective of Arabidopsis biology.
基因组规模的研究为揭示新的植物生物学提供了巨大的前景。由于这些技术的复杂性，在开始研究之前需要考虑许多因素。在这里，我们专注于拟南芥模型系统，因为有大量可用的基因组规模数据。有许多方法可以提供关于特定生物体状态的基因组规模信息（例如基因组学、表观基因组学、转录组学、蛋白质组学、代谢组学、相互作用组学、离子组学、表型组学等）。要全面描述拟南芥，需要整合所有这些类型的数据。在这篇综述中，我们提出转录组学、蛋白质组学和代谢组学之间的“三角测量”是开始这种综合分析并揭示拟南芥生物学系统水平观点的有意义的方法。
