Comparative Genomics of Non-Coding Regions to Facilitate Translational Research

项目摘要/摘要 越来越多的证据表明，调控基因表达的非编码序列的变异在 在人类疾病中起着重要作用。然而，非编码、调节性多态的鉴定 我们无法识别哪些变异存在于基因调控中，这限制了我们对疾病的贡献 序列。最近的多项研究表明，高度保守的非编码区由 比较序列分析通常具有基因调控活性。因此，仅靠序列守恒 可以优先考虑非编码序列的基因调控功能。虽然我们有理由期待 高度保守的非编码区的变异更有可能是有害的，几乎没有研究 目的是在临床人群中验证这一假说。因此，这项提案的目标是 研究比较基因组学在确定功能性非编码的优先顺序中的作用 几种疾病模型中的序列差异，并构建计算资源，使 临床研究人员使用这一策略。为了实现这一点，我们首先将非 根据一系列比较基因组标准编码序列变异，以估计它们的可能性 有害的。与i2b2临床研究人员的合作将使我们能够测试这一点的有效性。 哮喘临床研究中的分类。在Vista的成功基础上，我们的比较套件 基因组工具已经被生物医学界广泛使用，我们将开发一种用户友好的 “临床比较基因组门户”，使这一过程自动化。最后，门户网站整合到i2b2的S 蜂巢架构和临床研究图表将使临床研究人员能够利用 基于计算和临床序列的数据在分析i2b2丰富的临床数据库和 加快将临床基因数据转化为功能洞察力。为了方便 传播和采用比较门户，与i2b2协调，我们将在网上和 专门针对临床用户的线下培训活动。项目叙事 在不久的将来，对常见人类疾病的基因研究将变得越来越频繁，这要归功于 基因组科学和测序技术的进展。常见疾病，如糖尿病和 心血管疾病是人类发病和死亡的主要原因之一。小说 需要计算方法来帮助将在这类研究中获得的遗传信息转化为 可用于了解疾病机制和开发新的功能信息 诊断和治疗方法。在这份提案中，我们将利用我们的专业知识进行比较 序列分析开发计算平台，帮助整合计算数据和临床数据 基于人类基因组序列，并加速将遗传发现转化为 功能性和医学洞察力。这个平台将通过临床研究人员广泛使用 NIH支持的i2b2临床研究图表。

Project Summary/Abstract There is increasing evidence that variations in non-coding sequences that regulate gene expression play an important role in human disease. However, the identification of non-coding, regulatory polymorphisms contributing to disease is limited by our inability to identify which variants reside within gene regulatory sequences. Multiple recent studies indicate that highly conserved non-coding regions identified by comparative sequence analysis often possess gene regulatory activity. Thus, sequence conservation alone can prioritize noncoding sequences for gene regulatory function. While it is reasonable to expect that variations in highly conserved non-coding regions are more likely to be deleterious, very little research has been directed to validate this hypothesis in clinical populations. Accordingly, the goal of this proposal is to investigate the utility of comparative genomics for the prioritization of functional non-coding sequence variations in several disease models and to build computational resources enabling the employment of this strategy by clinical investigators. To accomplish this, we will first classify non- coding sequence variations based on a range of comparative genomic criteria to estimate their likelihood of deleteriousness. Collaboration with i2b2 clinical investigators will enable us to test the validity of this classification in a clinical study of asthma. Building on the success of VISTA, our suite of comparative genomic tools already widely used by the biomedical community, we will develop a user-friendly "clinical comparative genome portal" to automate this process. Finally, integration of the portal into i2b2's Hive architecture and clinical research chart will enable clinical investigators to exploit the synergies of computational and clinical sequence-based data in their analysis of i2b2 rich clinical databases and to accelerate the translation of clinical genetic data into functional insights. To facilitate the dissemination and adoption of the comparative portal, in coordination with i2b2 we will organize online and offline training activities specifically targeted at clinical users. Project Narrative Genetic studies of common human diseases will become increasingly frequent in the near future, thanks to advances in genomic science and sequencing technologies. Common diseases, such as diabetes and cardiovascular disease, are among the major causes of human morbidity and mortality. Novel computational approaches are needed to help translate the genetic information obtained in such studies into functional information that can be used to understand the mechanisms of disease and develop new diagnostic and therapeutic approaches. In this proposal, we will use our expertise with comparative sequence analysis to develop a computational platform to help integrate computational and clinical data based on the sequence of the human genome and accelerate the translation of genetic findings into functional and medical insights. This platform will be widely available to clinical investigators through the NIH-supported i2b2 clinical research chart.