Genome Geography A tool for connecting genes and other genomic features

基因组地理学 连接基因和其他基因组特征的工具

• 批准号: 8355678
• 负责人: Laura Kelly Vaughan
• 金额: $ 7.33万
• 依托单位: UNIVERSITY OF ALABAMA AT BIRMINGHAM
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-15 至 2014-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8355678
• 关键词: Accounting; Area; Binding Sites; Bioinformatics; Biological; Caring; Chromosomes; Code; Communities; Complex; Computer software; DNA Sequence; DNA Transposable Elements; Databases; Disease; Elements; Enhancers; Evolution; Exons; Functional RNA; Genes; Genome; Genomics; Geography; Heredity; Junk DNA; K-Series Research Career Programs; Knowledge; Linkage Disequilibrium; Maps; Mentors; Methods; MicroRNAs; National Institute of Diabetes and Digestive and Kidney Diseases; Nucleic Acid Regulatory Sequences; Phenotype; Positioning Attribute; Process; Proteins; Reproducibility; Research; Research Personnel; Resources; Rest; Role; Single Nucleotide Polymorphism Map; Structural Genes; Variant; Work; computer based Semantic Analysis; genome wide association study; interest; meetings; promoter; repository; tool; transcription factor; user-friendly; web interface

DESCRIPTION (provided by applicant): As we accumulate knowledge, our understanding of the genome continues to evolve. We now realize that the 99% of the genome that does not code for proteins, what was once thought of as 'junk DNA', has important functional roles. This understanding has important implications in the analysis and interpretation of high dimensional genomics analysis. It is rare that a study is lucky enough to find significantly associated variant that lie within an exon of a protein coding gene that is biologically related to the phenotype. It s more common to identify a region of interest that is intergenic, or even in a gene desert. The implication of these associations is not directly obvious and often requires extensive bioinformatics analysis to even begin to understand the possible underlying biological mechanisms. To effectively capture our greater understanding of the relationship between coding and non-coding variants with complex disease, we must be able to accurately connect those variants with their biological annotations. This application proposes to build on my current K01 research of mapping SNPs to protein coding genes to capture these other features by accomplishing the following specific aims: Aim 1- Capturing non-protein coding 'genes'. In this aim we will identify non-protein coding genes and define their boundaries. Aim 2- Map variants in gene associated regions to the corresponding genes. Phenotypes are not controlled by genic sequences alone. In this aim we will identify and map the non-genic portions of the chromosome which can influence the expression of coding genes. Aim 3- Expanding beyond physical boundaries. Expanding feature boundaries to account for LD regions will allow for researchers to capture genomic features that would not be identified otherwise. It is vitaly important that any bioinformatics workflow follows the principles of reproducible research, particularly when utilizing database driven resources. These aims will be accomplished by exploiting various database repositories and presenting the compiled information in a user friendly interface. PUBLIC HEALTH RELEVANCE: Currently the interpretation of whole genome analysis tends to focus on protein coding genes. As our knowledge expands, we are beginning to understand that the rest of the genome has important functional roles. This proposal will provide a tool that will enable researchers to easily access, organize, and use information located in numerous ever expanding databases.

描述（由申请人提供）：随着知识的积累，我们对基因组的理解也在不断发展。我们现在意识到，99%的基因组不编码蛋白质，也就是曾经被认为是“垃圾DNA”的DNA，具有重要的功能作用。这种认识对高维基因组学分析的分析和解释具有重要意义。很少有研究能够幸运地发现与表型相关的蛋白质编码基因外显子内的显著相关变异。更常见的是确定基因间的兴趣区域，甚至在基因沙漠中。这些关联的含义不是直接明显的，往往需要广泛的生物信息学分析，甚至开始理解可能的潜在生物学机制。为了更有效地了解编码和非编码变异与复杂疾病之间的关系，我们必须能够准确地将这些变异与它们的生物学注释联系起来。该应用程序建议建立在我目前的K01研究，将snp映射到蛋白质编码基因，通过实现以下具体目标来捕获这些其他特征：目标1-捕获非蛋白质编码“基因”。在这个目标中，我们将识别非蛋白质编码基因并定义它们的边界。目标2-将基因相关区域的变异定位到相应的基因。表型不受基因序列的单独控制。在这个目标中，我们将识别和绘制染色体中可以影响编码基因表达的非基因部分。目标3-超越物理界限。扩展特征边界以解释LD区域将允许研究人员捕获否则无法识别的基因组特征。至关重要的是，任何