Generation of an In Vivo Human Genome Transcriptional Enhancer Dataset

体内人类基因组转录增强子数据集的生成

• 批准号: 7941543
• 负责人: Len Alexander Pennacchio
• 金额: $ 35.22万
• 依托单位: UNIVERSITY OF CALIF-LAWRENC BERKELEY LAB
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2011-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7941543
• 关键词: Address; Algorithms; Amino Acid Sequence; Area; Automobile Driving; Bioinformatics; Biological; Biological Assay; Biology; Chickens; Clinical; Communities; Complementary DNA; Computer Analysis; Coupled; DNA; Data; Data Set; Databases; Deposition; Development; Elements; Embryo; Enhancers; Exons; Expressed Sequence Tags; Fishes; Functional RNA; Gene Expression; Gene Transfer Techniques; Generations; Genes; Genetic Enhancer Element; Genome; Genomics; Genotype; Grant; Harvest; Human; Human Genome; Human Genome Project; Image; Informatics; Investigation; Knowledge; Morphologic artifacts; Mus; Mutation; Nucleic Acid Regulatory Sequences; Pattern; Peptide Sequence Determination; Persons; Pilot Projects; Property; Rana; Reading; Regulator Genes; Reporter; Reporting; Research Personnel; Resolution; Resources; Rodent; Scientist; Site; Specific qualifier value; Staining method; Stains; System; Takifugu; Testing; Time; Tissues; Training; Transgenic Mice; Transgenic Organisms; Vocabulary; base; beta-Galactosidase; comparative; design; digital; digital imaging; egg; genome sequencing; genome-wide; human DNA; human disease; in vivo; insight; interest; user-friendly; vector; web site

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. .

描述（由申请人提供）：我们鉴定人基因组中大多数外显子的能力已通过可用的广泛的实验数据（EST，cDNA和蛋白质序列）极大地促进，从而为这种元素的CFE Novo Novo notements提供了有效的算法，从而提供了训练集。与之形成鲜明对比的是，由于缺乏这些序列的平行实验训练集，人类基因组中基因调节区域的词汇在很大程度上仍然很差。我们预测哪些非编码序列的能力的最新进展具有较高的可能性，其作为基于深层进化保护的转录增强剂的可能性较高，为解决此问题提供了一定的杠杆作用。在初步研究中，我们在转基因小鼠记者测定中检查了150个极为保守的非编码序列，并证明了这些序列中的58个具有不同组织特异性增强剂活性。在这种背景下，我们在这里提议将我们在比较基因组学和高吞吐量小鼠转基因方面进行培养，以定义位于整个人类基因组的1,500个深处保守的非编码元素的增强剂活性。我们将通过具有广泛的搜索功能的在线数据库公开获得体内研究的结果，从而使用户可以键入产生相似的表达模式以识别共享序列功能。这些数据集将为一群针对破译人类基因表达的规则的计算，发育和临床生物学的研究者提供必不可少的资源。因此，该赠款旨在通过以下方式通过以下方式对非编码DNA的基因调节特性进行分类：（1）对转基因小鼠中1,500个极为保守的人DNA片段的表征，以及（2）在Vivo增强数据库中开发的空间增强活性，以显示这些结果。此外，为了根据AIM 1中生成的数据的分析，为增强剂提供了一种从头开始预测增强剂的方法，我们进一步建议（3）（3）测试15-20个通过转基因小鼠系统中的外部研究人员预测的增强器。外行人摘要：整个人类基因组序列的产生是一个庞大的研究者基础的常规起点，并有助于定义我们基因组中的大多数基因。但是，尽管人们认为它们在人类疾病中发生了改变，但我们对调节这些基因的序列的理解仍然很少。在这里，我们建议利用人类基因组比较来识别深层保守的非基因序列，并测试其在转基因小鼠中充当基因调节序列的能力。预计这种社区资源将在人类基因组的基因调节注释中显着填补我们的空白，并将其突变破译为人类疾病的原因。 。