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Discovering Transcriptional Regulation by Integrating Protein-Protein Interaction, Gene Expression and Transcriptional Interaction Data

机译：通过整合蛋白质-蛋白质相互作用，基因表达和转录相互作用数据发现转录调控

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摘要

Understanding transcriptional regulation (TR) principles and mechanisms is a hot topic in the genomics and transcriptome research. Many experimental and computational methods have been proposed to investigate this problem. However, perhaps partially because the high complexity in the transcriptional regulation mechanism, or partially because the noise in the high-throughput detection experiments, integrative approaches are demanded to discover underlying TRs which could be missed when only single source of information is considered. In this paper, we explore the biological ideas behind co-regulated protein complexes to study this problem. Co-regulated protein complex has three remarkable characteristics: coding genes of member proteins share the same transcription factor, coding genes usually express coordinately and member proteins intensively interact and form a complex to implement a common biological function. It implies close relationships among co-regulation, co-expression and intensive interaction at the levels of transcriptional regulation, gene expression and protein-protein interaction. Based on these ideas, we integrate protein-protein interaction (PPI), gene expression (GE) and transcriptional interaction (TI) data and use them to form a framework to discover new Tr relationships. Experiments on the yeast in three conditions of cell cycle, diauxic shift and DNA damaging were conducted, and 20 novel TRs were predicted and explained.
机译：在基因组学和转录组研究中，了解转录调控（TR）的原理和机制是一个热门话题。已经提出了许多实验和计算方法来研究这个问题。但是，可能部分是由于转录调控机制的高度复杂性，或者部分是由于高通量检测实验中的噪声，因此需要采用集成方法来发现仅考虑单一信息源时可能会漏掉的潜在TR。在本文中，我们探索了共调控蛋白复合物背后的生物学思想来研究这一问题。共同调控的蛋白质复合物具有三个显着特征：成员蛋白质的编码基因共享相同的转录因子，编码基因通常协同表达，成员蛋白质强烈相互作用并形成复合物以实现共同的生物学功能。它暗示着在转录调节，基因表达和蛋白-蛋白相互作用水平上的共调节，共表达和强烈相互作用之间的密切关系。基于这些想法，我们整合了蛋白质-蛋白质相互作用（PPI），基因表达（GE）和转录相互作用（TI）数据，并利用它们形成了发现新的Tr关系的框架。进行了酵母在细胞周期，双峰迁移和DNA损伤三种条件下的实验，并预测和解释了20种新型TR。

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