REGULATORY PATHWAYS
REGULATORY PATHWAYS
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发表时间：
2007
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通讯作者：
Dcvmn Webinar;N. Dellepiane
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作者：
Dcvmn Webinar;N. Dellepiane
引言后基因组时代导致了高通量基因组学研究的巨大进步。基因组学方法，如微阵列表达分析和ChIP芯片转录因子结合测定产生了新的见解遗传途径。这些技术提供了有价值的观测数据，但不能确定网络内的功能连接或解释基因调控的机制。瞬时报告基因的实验，如功能启动子检测提供了一个重要的额外层的数据，了解遗传网络的调控机制。SwitchGear Genomics和Promega结合了他们的技术和专业知识，创建了一套新的工具，可以详细分析活细胞中的调控途径。通过克隆到Promega pGL4.11[luc2P] Vector（a）中，SwitchGear已经产生了包含数千个人类启动子、UTR和其他调控元件的文库，这些元件涵盖许多不同的疾病相关途径，可作为基于细胞的研究的即用型工具。图1显示了组合多种数据类型的强大功能的一个示例。图上有许多基因符合TFIID基础转录复合物的结合（在本实施例中通过TAF1测量）与基因表达（通过启动子活性和内源转录物水平测量）相关的流行模型。然而，这种模式也有一些非常有趣的例外。图1中标记为A的基因组具有高内源转录水平和启动子活性，但未显示基础转录因子结合的证据。这些基因可能通过TAF1非依赖性机制表达。同样地，具有显著转录因子结合和强启动子活性但具有低内源转录物水平的那些基因是被转录后调节并具有高转录物周转率的候选基因。这些观察结果突出了整合多个独立实验结果的价值，特别是高通量启动子检测在提供更完整的基因调控图片中的价值。我们之前在14种不同细胞系中研究人类基因组中1%启动子功能的一些工作是基因组功能注释的重要第一步（图2，来自库珀等人，2006）。这项全面的功能调查表明，广泛使用的替代启动子和强大的组成型活性的CpG丰富的启动子。我们发现启动子活性和相应的内源RNA转录水平之间有很强的相关性。有有趣的模式，细胞类型特异性启动子摘要在这里，我们描述了一套新的工具，使详细分析活细胞中的调控途径的发展。SwitchGear Genomics已经产生了一个包含数千个人类启动子、UTR和其他调控元件的文库，这些元件包含在最先进的荧光素酶报告基因载体pGL4.11[luc2P] Vector中。该文库结合了在广泛的动态范围内收集高度可重复数据的能力，以及在单个实验中扩展到数百或数千个启动子的能力。
INTRODUCTION The post-genome era has led to great advances in high-throughput genomics studies. Genomic approaches such as microarray expression analysis and ChIP-chip transcription factor binding assays have yielded new insights into genetic pathways. These technologies provide valuable observational data but do not identify the functional connections within networks or explain the mechanism of gene regulation. Transient reporter gene experiments like functional promoter assays provide an important additional layer of data for understanding mechanisms of regulation in genetic networks. SwitchGear Genomics and Promega have combined their technologies and expertise to create a new set of tools that enable a detailed analysis of regulatory pathways in living cells. By cloning into the Promega pGL4.11[luc2P] Vector(a), SwitchGear has produced a library of thousands of human promoters, UTRs and other regulatory elements encompassing many different disease-related pathways that are available as ready-to-use tools for cell-based studies. An example of the power of combining multiple data types is shown in Figure 1. There are a number of genes on the plot that fit with the prevailing model that binding of the TFIID basal transcription complex (as measured by TAF1 in this example) correlates with gene expression (as measured by promoter activity and endogenous transcript levels). However, there are exceptions to this pattern that are very interesting. The group of genes labeled A in Figure 1 have high endogenous transcript levels and promoter activity but do not show evidence of basal transcription factor binding. These are genes that may be expressed by a TAF1-independent mechanism. Likewise, those genes with significant transcription factor binding and strong promoter activity but with low endogenous transcript levels are candidates for being post-transcriptionally regulated and having a high rate of transcript turnover. These observations highlight the value of integrating multiple independent experimental results and, specifically, the value of high-throughput promoter assays in providing a more complete picture of gene regulation. Some of our previous work in studying the function of 1% of the promoters in the human genome in 14 diverse cell lines was an important first step in the functional annotation of the genome (Figure 2, from Cooper et al. 2006). This comprehensive functional survey demonstrates the widespread use of alternative promoters and the strong constitutive activity of CpG-rich promoters. We showed a strong correlation between promoter activity and the corresponding endogenous RNA transcript levels. There are interesting patterns of cell type-specific promoter ABSTRACT Here we describe the development of a new set of tools that enable detailed analysis of regulatory pathways in living cells. SwitchGear Genomics has produced a library of thousands of human promoters, UTRs and other regulatory elements contained within a state-of-the-art luciferase reporter vector, the pGL4.11[luc2P] Vector. This library combines the ability to gather highly reproducible data over a broad dynamic range with the ability to scale to hundreds or thousands of promoters in a single experiment.