Analyzing gene coexpression data by an evolutionary model.

Moritz Schütte, Marek Mutwil, Staffan Persson, Oliver Ebenhöh
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Abstract

Coexpressed genes are tentatively translated into proteins that are involved in similar biological functions. Here, we constructed gene coexpression networks from collected microarray data of the organisms Arabidopsis thaliana, Saccharomyces cerevisiae, and Escherichia coli. Their degree distributions show the common property of an overrepresentation of highly connected nodes followed by a sudden truncation. In order to analyze this behavior, we present an evolutionary model simulating the genetic evolution. This model assumes that new genes emerge by duplication from a small initial set of primordial genes. Our model does not include the removal of unused genes but selective pressure is indirectly taken into account by preferentially duplicating the old genes. Thus, gene duplication represents the emergence of a new gene and its successful establishment. After a duplication event, all genes are slightly but iteratively mutated, thus altering their expression patterns. Our model is capable of reproducing global properties of the investigated coexpression networks. We show that our model reflects the mean inter-node distances and especially the characteristic humps in the degree distribution that, in the biological examples, result from functionally related genes.

用进化模型分析基因共表达数据。
共表达基因被暂时翻译成参与类似生物功能的蛋白质。在这里,我们利用收集到的拟南芥、酿酒酵母和大肠杆菌的微阵列数据构建了基因共表达网络。它们的度分布显示了高度连接节点的过度表示和突然截断的共同特性。为了分析这种行为,我们提出了一个模拟遗传进化的进化模型。这个模型假定新的基因是由一小部分原始基因的复制而产生的。我们的模型不包括去除不使用的基因,但通过优先复制旧基因间接考虑了选择压力。因此,基因复制代表了新基因的出现和成功建立。在重复事件发生后,所有的基因都发生了轻微但反复的突变,从而改变了它们的表达模式。我们的模型能够再现所研究的共表达网络的全局属性。我们表明,我们的模型反映了平均节点间距离,特别是度分布中的特征峰,在生物学示例中,这是由功能相关基因引起的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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