Integrative analysis of transcript and metabolite profiling data sets to evaluate the regulation of biochemical pathways during photomorphogenesis
Integrative analysis of transcript and metabolite profiling data sets to evaluate the regulation of biochemical pathways during photomorphogenesis
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DOI：
10.1016/j.abb.2005.11.020
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发表时间：
2006-04-15
影响因子：
3.9
通讯作者：
Lange, B. Markus
中科院分区：
文献类型：
--
作者：
Ghassemian, Majid;Lutes, Jason;Lange, B. Markus
光形态发生过程中的关键发育过程之一是前质体原层体分化为含有叶绿体光合色素-蛋白质复合物的类囊体膜。为了研究控制色素-蛋白质复合物组装的调控事件，包括代谢前体和色素终产物的生物合成，黄化的拟南芥幼苗用连续红光（Rc）照射，导致快速绿化，或连续远红光（FRc）照射，不会导致可见绿化，并通过寡核苷酸微阵列和靶向分析进行分析。 代谢物分析。使用 BioPathAt（一种生物信息学工具，可以直接在生化途径图上可视化后基因组数据集）进行的分析表明，在 Rc 处理的幼苗中，mRNA 表达和代谢模式紧密相关（例如，卡尔文循环、叶绿素、类胡萝卜素、类异戊二烯醌、类囊体脂质、 甾醇和氨基酸）。 K 均值聚类显示，Rc 和 FRc 处理的幼苗中各种生化途径的基因表达模式非常相似（尽管存在可见的表型差异），而代谢物池的主成分分析允许两种处理之间的明显区别（根据可见的表型）。我们的结果说明了将后基因组数据集与表型结果相关联的综合方法的普遍重要性。 (c) 2005 Elsevier Inc. 保留所有权利。
One of the key developmental processes during photomorphogenesis is the differentiation of prolamellar bodies of proplastids into thylakoid membranes containing the photosynthetic pigment-protein complexes of chloroplasts. To study the regulatory events controlling pigment-protein complex assembly, including the biosynthesis of metabolic precursors and pigment end products, etiolated Arabidopsis thaliana seedlings were irradiated with continuous red light (Rc), which led to rapid greening, or continuous far-red light (FRc), which did not result in visible greening, and subjected to analysis by oligonucleotide microarrays and targeted metabolite profiling. An analysis using BioPathAt, a bioinformatic tool that allows the Visualization of post-genomic data sets directly on biochemical pathway maps, indicated that in Rc-treated seedlings mRNA expression and metabolite patterns were tightly correlated (e.g., Calvin cycle, biosynthesis of chlorophylls, carotenoids, isoprenoid quinones, thylakoid lipids, sterols, and amino acids). K-means clustering revealed that gene expression patterns across various biochemical pathways were very similar in Rc- and FRc-treated seedlings (despite the visible phenotypic differences), whereas a principal component analysis of metabolite pools allowed a clear distinction between both treatments (in accordance with the visible phenotype). Our results illustrate the general importance of integrative approaches to correlate post-genomic data sets with phenotypic outcomes. (c) 2005 Elsevier Inc. All rights reserved.