Genome-wide coexpression dynamics: Theory and application
Genome-wide coexpression dynamics: Theory and application
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DOI：
10.1073/pnas.252466999
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发表时间：
2002-12-24
影响因子：
11.1
通讯作者：
Li, KC
中科院分区：
文献类型：
--
作者：
Li, KC
高通量表达谱使基因活动的全球研究成为可能。表达谱呈正相关的基因很可能编码功能相关的蛋白质。然而，所有的生物过程都是相互关联的，每个蛋白质都可能扮演多种细胞角色。因此，任何两个功能相关的基因的共表达可能取决于不断变化的、但往往未知的细胞状态。为了启动对这一问题的系统研究，提出了共表达动力学理论。这一理论被用来合理化一种策略，即在全基因组范围内寻找可能影响任何两个基因的共表达模式的最关键的细胞因子。在一个例子中，使用酵母数据集，我们的方法揭示了与尿素循环相关的酶是如何表达的，以确保所涉及的代谢物的适当质量流动。随着CPA2表达水平的增加，ARG2与CAR2的相关性由正向负转变。这种微妙的相互作用意味着对鸟氨酸的流入和流出的显着控制，并很好地反映了细胞对精氨酸的内在需求。除了尿素循环，我们的例子还包括SCH9和CyR1(都与最近的长寿研究有关)，细胞色素CL(线粒体电子传递)，钙调蛋白(主要的钙结合蛋白)，PFK1和PFK2(糖酵解)，以及两个基因ECM1和YNL101W，它们的功能都是新发现的。数理统计的一项新结果减轻了计算的复杂性。
High-throughput expression profiling enables the global study of gene activities. Genes with positively correlated expression profiles are likely to encode functionally related proteins. However, all biological processes are interlocked, and each protein may play multiple cellular roles. Thus the coexpression of any two functionally related genes may depend on the constantly varying, yet often-unknown cellular state. To initiate a systematic study on this issue, a theory of coexpression dynamics is presented. This theory is used to rationalize a strategy of conducting a genome-wide search for the most critical cellular players that may affect the coexpression pattern of any two genes. In one example, using a yeast data set, our method reveals how the enzymes associated with the urea cycle are expressed to ensure proper mass flow of the involved metabolites. The correlation between ARG2 and CAR2 is found to change from positive to negative as the expression level of CPA2 increases. This delicate interplay in correlation signifies a remarkable control on the influx and efflux of ornithine and reflects well the intrinsic cellular demand for arginine. In addition to the urea cycle, our examples include SCH9 and CYR1 (both implicated in a recent longevity study), cytochrome cl (mitochondrial electron transport), calmodulin (main calcium-binding protein), PFK1 and PFK2 (glycolysis), and two genes, ECM1 and YNL101W, the functions of which are newly revealed. The complexity in computation is eased by a new result from mathematical statistics.