Comparative Genomics of Non-Coding Regions to Facilitate Translational Research

非编码区域的比较基因组学促进转化研究

基本信息

批准号：
8055442
负责人：
INNA DUBCHAK
金额：
$ 80.9万
依托单位：
UNIVERSITY OF CALIF-LAWRENC BERKELEY LAB
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-04-15 至 2013-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8055442
关键词：
Academic Medical Centers Address Adopted Adoption Affect Age Anatomy Animal Model Animals Architecture Asthma Automobile Driving Base Sequence Biological Biological Models Biology Biomedical Computing Biomedical Research Cardiovascular Diseases Classification Clinical Clinical Data Clinical Investigator Clinical Research Collaborations Communities Companions Computer software Computing Methodologies Consent DNA Binding DNA Sequence Data Data Set Databases Development Diabetes Mellitus Discipline Disease Disease Progression Disease model Doctor of Medicine Doctor of Philosophy Employment Engineering Ensure Epigenetic Process Frequencies Fruit Functional RNA Future Gene Expression Generations Genetic Genetic Polymorphism Genetic Translation Genome Genomics Goals Health Health Sciences Health Technology Healthcare Healthcare Systems Heterogeneity Hospitals Human Human Genome Human Genome Project Hypertension Informatics Information Technology Intellectual Property Knowledge Laboratories Leadership Licensing Major Depressive Disorder Maps Measurement Medical Methodology Methods Modeling Obesity Ontology Patients Pattern Recognition Phenotype Physiology Play Population Principal Investigator Process Program Description Property Proteomics Public Health Schools Quantitative Trait Loci Recording of previous events Regulator Genes Research Research Design Research Personnel Resources Rheumatoid Arthritis Role Sampling Science Sequence Analysis Solutions Structure System Technology Testing Text Therapeutic Time Time Series Analysis Training Activity Translating Translational Research Translations Underrepresented Minority United States National Institutes of Health Update Urticaria Variant Woman Work base biocomputing biological research biomedical informatics clinical care clinical practice clinically relevant comparative comparative genomics computer framework computerized data processing computing resources data integration database structure design genome-wide health care delivery human disease human morbidity human mortality image processing improved innovation insight interdisciplinary collaboration knowledge base medical schools models and simulation multidisciplinary nervous system disorder novel novel diagnostics novel therapeutic intervention patient population prognostic programs response structural biology success tool user-friendly virtual web site

项目摘要

DESCRIPTION (provided by applicant): 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. PUBLIC HEALTH REVELANCE: 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.

描述（由申请人提供）：越来越多的证据表明，调节基因表达的非编码序列的变异在人类疾病中发挥着重要作用。然而，由于我们无法识别基因调控序列中存在哪些变异，因此对导致疾病的非编码调控多态性的识别受到限制。最近的多项研究表明，通过比较序列分析鉴定出的高度保守的非编码区通常具有基因调控活性。因此，仅序列保守就可以优先考虑基因调控功能的非编码序列。虽然可以合理地预期高度保守的非编码区的变异更有可能是有害的，但很少有研究在临床人群中验证这一假设。因此，本提案的目标是研究比较基因组学在几种疾病模型中功能性非编码序列变异优先排序的效用，并建立计算资源，使临床研究人员能够采用该策略。为了实现这一目标，我们将首先根据一系列比较基因组标准对非编码序列变异进行分类，以估计其有害的可能性。与 i2b2 临床研究人员的合作将使我们能够在哮喘临床研究中测试该分类的有效性。基于 VISTA 的成功（我们的比较基因组工具套件已被生物医学界广泛使用），我们将开发一个用户友好的“临床比较基因组门户”来自动化此过程。最后，将该门户集成到 i2b2 的 Hive 架构和临床研究图表中，将使临床研究人员能够在分析 i2b2 丰富的临床数据库时利用计算数据和基于临床序列的数据的协同作用，并加速将临床遗传数据转化为功能见解。为了促进比较门户的传播和采用，我们将与 i2b2 合作组织专门针对临床用户的线上和线下培训活动。公共卫生启示：由于基因组科学和测序技术的进步，在不久的将来，对人类常见疾病的遗传学研究将变得越来越频繁。糖尿病和心血管疾病等常见疾病是人类发病和死亡的主要原因。需要新的计算方法来帮助将此类研究中获得的遗传信息转化为可用于理解疾病机制并开发新的诊断和治疗方法的功能信息。在本提案中，我们将利用我们在比较序列分析方面的专业知识来开发一个计算平台，以帮助整合基于人类基因组序列的计算和临床数据，并加速将遗传发现转化为功能和医学见解。该平台将通过 NIH 支持的 i2b2 临床研究图表广泛供临床研究人员使用。