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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：
8249062
负责人：
INNA DUBCHAK
金额：
$ 82.75万
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 2014-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8249062
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 abstracting 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

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.

项目总结/文摘