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Generation of an In Vivo Human Genome Transcriptional Enhancer Dataset

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:
7088631
负责人:
Len Alexander Pennacchio
金额:
$68.81万
依托单位国家:
美国
项目类别:
财政年份:
2006
资助国家:
美国
项目状态:
已结题
起止时间:
2006-09-26 至 2010-08-31

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项目成果

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中文摘要
翻译
描述(由申请人提供):我们鉴定人类基因组中大多数外显子的能力已经通过大量实验数据(EST、cDNA和蛋白质序列)的可用性而得到极大的促进,从而为开发用于这些元件的从头预测的有效算法提供了训练集。与此形成鲜明对比的是,人类基因组中基因调控区的词汇仍然定义不清,这在很大程度上是由于缺乏这些序列的平行实验训练集。最近的进展,我们的能力来预测哪些非编码序列有更高的可能性作为转录增强子的基础上深进化保守提供了一些杠杆来解决这个问题。在初步研究中,我们已经检查了150个非常保守的非编码序列在转基因小鼠报告基因检测,并证明这些序列中的58个具有不同的组织特异性增强子活性。在此背景下,我们在此提出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1,500个高度保守的非编码元件的增强子活性。我们将通过具有广泛搜索能力的在线数据库公开我们的体内研究结果,允许用户将产生相似表达模式的序列合并,以识别共享的序列特征。这些数据集将为计算、发育和临床生物学领域的广泛研究人员提供重要资源,这些研究人员专注于破译人类基因表达的规则。因此,该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)对转基因小鼠中1,500个极其保守的人类DNA片段进行空间增强子活性的表征,以及(2)开发公开可用的体内增强子数据库以显示这些结果。此外,为了给生物信息学界提供一种方法来测试基于他们对我们在目标1中产生的数据的分析的增强子的从头预测,我们进一步提议(3)在我们的转基因小鼠系统中由外部研究者每年测试15-20个预测的增强子。非专业人员总结:整个人类基因组序列的产生是一个庞大的研究基础的常规起点,并有助于确定我们基因组中的大多数基因。然而,我们对调节这些基因的序列的理解是贫乏的,尽管它们在人类疾病中被假定为改变。在这里,我们建议利用人类-鱼类基因组比较,以确定高度保守的非基因序列,并测试其作为基因调控序列在转基因小鼠的能力。这样的社区资源有望大大填补我们在人类基因组基因调控注释方面的空白,并将其突变解释为人类疾病的原因。.
英文摘要
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. .
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