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计算基因组中共调控基因物理簇的统计显著性:染色质在全结构域基因调控中的作用。

Calculating the statistical significance of physical clusters of co-regulated genes in the genome: the role of chromatin in domain-wide gene regulation.

作者信息

Chang Cheng-Fu, Wai Ka-Man, Patterton Hugh G

机构信息

Department of Molecular and Cell Biology and Institute for Infectious Diseases and Molecular Medicine, University of Cape Town, University Private Bag, Rondebosch 7701, South Africa.

出版信息

Nucleic Acids Res. 2004 Mar 19;32(5):1798-807. doi: 10.1093/nar/gkh507. Print 2004.

Abstract

Physical clusters of co-regulated, but apparently functionally unrelated, genes are present in many genomes. Despite the important implication that the genomic environment contributes appreciably to the regulation of gene expression, no simple statistical method has been described to identify physical clusters of co-regulated genes. Here we report the development of a model that allows the direct calculation of the significance of such clusters. We have implemented the derived statistical relation in a software program, Pyxis, and have analyzed a selection of Saccharomyces cerevisiae gene expression microarray data sets. We have identified many gene clusters where constituent genes exhibited a regulatory dependence on proteins previously implicated in chromatin structure. Specifically, we found that Tup1p-dependent gene domains were enriched close to telomeres, which suggested a new role for Tup1p in telomere silencing. In addition, we identified Sir2p-, Sir3p- and Sir4p-dependent clusters, which suggested the presence of Sir-mediated heterochromatin in previously unidentified regions of the yeast genome. We also showed the presence of Sir4p-dependent gene clusters bordering the HMRa heterothallic locus, which suggested leaky termination of the heterochromatin by the boundary elements. These results demonstrate the utility of Pyxis in identifying possible higher order genomic features that may contribute to gene regulation in extended domains.

摘要

在许多基因组中都存在共同调控但功能上明显无关的基因的物理簇。尽管基因组环境对基因表达调控有重要影响,但尚未有简单的统计方法可用于识别共同调控基因的物理簇。在此,我们报告了一个模型的开发,该模型可直接计算此类簇的显著性。我们已在软件程序Pyxis中实现了推导的统计关系,并分析了一系列酿酒酵母基因表达微阵列数据集。我们识别出了许多基因簇,其中组成基因对先前涉及染色质结构的蛋白质表现出调控依赖性。具体而言,我们发现Tup1p依赖性基因结构域在端粒附近富集,这表明Tup1p在端粒沉默中具有新作用。此外,我们识别出了Sir2p、Sir3p和Sir4p依赖性簇,这表明在酵母基因组先前未识别的区域存在Sir介导的异染色质。我们还展示了与HMRa异宗配合位点相邻的Sir4p依赖性基因簇的存在,这表明边界元件导致异染色质的渗漏终止。这些结果证明了Pyxis在识别可能有助于扩展区域基因调控的高阶基因组特征方面的实用性。

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