Generation of an In Vivo Human Genome Transcriptional Enhancer Dataset

描述(由申请人提供)：大量实验数据(EST、cDNA和蛋白质序列)的可获得性大大促进了我们识别人类基因组中大多数外显子的能力，从而为开发这些元件的CFE novo预测的有效算法提供了训练集。与之形成鲜明对比的是，人类基因组中基因调控区域的词汇仍然定义不清，这在很大程度上是因为这些序列缺乏平行的实验训练集。最近在我们预测哪些非编码序列具有更高的可能性作为转录增强子的能力方面取得的进展，基于深度进化保守，为解决这一问题提供了一些杠杆。在初步研究中，我们在转基因小鼠报告试验中检查了150个极其保守的非编码序列，并证明其中58个序列具有不同的组织特异性增强子活性。在此背景下，我们建议将我们在比较基因组学和高通量小鼠转基因方面的专业知识结合起来，以确定位于整个人类基因组中的1500个深度保守的非编码元件的增强子活性。我们将通过一个具有广泛搜索功能的在线数据库公开我们的活体研究结果，允许用户结合产生相似表达模式的序列来识别共同的序列特征。这些数据集将为计算、发育和临床生物学领域的一大批研究人员提供必要的资源，这些研究人员专注于破译控制人类基因表达的规则。因此，这项资助旨在通过以下方式对人类基因组中非编码DNA的基因调控特性进行分类：(1)鉴定1,500个高度保守的人类DNA片段，用于转基因小鼠的空间增强活性；(2)开发一个公开可用的体内增强子数据库，以显示这些结果。此外，为了向生物信息学社区提供一种基于他们对我们在AIM 1中生成的数据的分析来测试增强剂从头计算预测的方法，我们进一步建议(3)在我们的转基因小鼠系统中测试外部研究人员每年测试15-20个预测的增强剂。外行人员概述：整个人类基因组序列的产生是一个庞大的研究人员基础的常规起点，并有助于确定我们基因组中的大多数基因。然而，我们对调控这些基因的序列的了解很少，尽管它们在人类疾病中可能发生了变化。在这里，我们建议利用人和鱼的基因组比较来识别高度保守的非基因序列，并测试它们在转基因小鼠中作为基因调控序列的能力。这样的社区资源有望显著填补我们在人类基因组基因调控注释方面的空白，并破译它们的突变是人类疾病的原因。。

DESCRIPTION (provided by applicant): Our ability to identify the majority of exons in the human genome has been dramatically facilitated by the availability of extensive experimental data (EST, cDNA, and protein sequences) thereby providing training sets for the development of effective algorithms for the cfe novo prediction of such elements. In stark contrast, the vocabulary of gene regulatory regions in the human genome remains poorly defined, in large part, due to the lack of parallel experimental training sets for these sequences. Recent advances in our ability to predict which non-coding sequences have a higher likelihood of acting as transcriptional enhancers based on deep evolutionary conservation have provided some leverage for addressing this problem. In preliminary studies, we have examined 150 extremely conserved non-coding sequences in a transgenic mouse reporter assay and demonstrate that 58 of these sequences have distinct tissue specific enhancer activity. With this background, we propose here to couple our expertise in comparative genomics and high throughput mouse transgenesis to define the enhancer activity of 1,500 deeply conserved non-coding elements located throughout the human genome. We will make the results of our in vivo studies publicly available through an online database with extensive search capabilities, allowing users to bin sequences producing similar expression patterns to identify shared sequence features. These datasets will provide an essential resource for a broad group of investigators in computational, developmental, and clinical biology focused on deciphering the rules that govern human gene expression. Accordingly, this grant aims to classify the gene regulatory properties of non-coding DNA in the human genome through: (1) the characterization of 1,500 extremely conserved human DNA fragments for spatial enhancer activity in transgenic mice and (2) the development of a publicly available in vivo enhancer database to display these results. In addition, to provide the bioinformatic community with a means to test ab initio predictions of enhancers based on their analyses of our data generated in Aim 1, we further propose to (3) test 15-20 predicted enhancers by outside investigators per year in our transgenic mouse system. Lay Person Summary: The generation of the entire human genome sequence serves as a routine starting point for a huge investigator base and has aided in defining the majority of genes in our genome. However, our understanding of the sequences that regulate these genes is meager, despite their presumed alterations in human disease. Here, we propose to leverage human-fish genome comparisons to identify deeply conserved non-gene sequences and to test their ability to act as gene regulatory sequences in transgenic mice. Such a community resource is expected to significantly fill our void in gene regulatory annotation of the human genome and to decipher their mutation as a cause of human disease. .