Harnessing GTEx to Create Transcriptome Knowledge and Inform Disease Biology

利用 GTEx 创建转录组知识并为疾病生物学提供信息

• 批准号: 8914801
• 负责人: Nancy J Cox
• 金额: $ 42.9万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-26 至 2016-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8914801
• 关键词: Accounting; Address; Advocate; Affect; Architecture; Biology; Collection; Communities; Complex; Computer software; Consensus Sequence; Data; Data Analyses; Data Collection; Data Set; Databases; Development; Dimensions; Disease; Elements; Environmental Exposure; Gender Role; Gene Expression; Gene Expression Profile; Gene Structure; Genes; Genetic; Genetic Transcription; Genetic Variation; Genome; Genotype; Health; Heritability; Human; Human Biology; Immersion Investigative Technique; Individual; Investigation; Knowledge; Lead; Measures; Methods; Modeling; Nature; Nonsense-Mediated Decay; Ontology; Pathway interactions; Phenotype; Quantitative Trait Loci; RNA Splicing; Regulatory Element; Research; Resources; Risk; Role; Single Nucleotide Polymorphism Map; Software Tools; Statistical Methods; Structure; System; Testing; Tissues; Transcript; Variant; Visual; base; design; exon skipping; flexibility; human disease; improved; insight; loss of function; member; novel; programs; protein function; sex; trait

DESCRIPTION (provided by applicant): We have long advocated the use of gene expression datasets for understanding the mechanisms underlying complex human disease, and we believe that the unique nature of data in the Genotype-Tissue Expression (GTEx) program will allow us to enhance our understanding of the functionality for a large class of variants, will lead to great insight into the genetic components of common diseases, and will permit the exploration of several novel scientific hypotheses on both transcriptome biology and the genetic architecture of human disease. The opportunity to analyze the GTEx datasets motivates the development of new statistical methods, software and knowledge databases that will facilitate the use of these results by the larger scientific community for additional investigations. All proposed research is informed by our near-complete immersion in studies relating genotype to phenotype (and in developing methods for relating genotype to phenotype) for many different complex traits. Thus, our specific aims are: 1) to discover cross-tissue and tissue-specific regulatory variation and to use the resulting information for discovery of novel risk pathways, and for partitioning of disease heritability into components corresponding to different classes of functional variants; 2) to test hypotheses that are finally feasible to investigate due to the uniqe design of the GTEx program, including the role of gender and other environmental exposures on regulatory variation, and the role of loss of function and missense variants in transcription; and 3) to use systems and network approaches for a better understanding of the organization of gene expression across tissues. All software and the databases developed through this project will be made publicly available immediately.

描述（由申请人提供）：我们长期以来主张使用基因表达数据集来了解复杂人类疾病的机制，我们相信基因型组织表达（GTEx）计划中数据的独特性质将使我们能够增强我们对一大类变体的功能的理解将导致 深入了解常见疾病的遗传成分，并将允许探索关于转录组生物学和人类疾病遗传结构的几种新颖的科学假设。分析 GTEx 数据集的机会推动了新统计方法、软件和知识数据库的开发，这将有助于更大的科学界利用这些结果进行更多调查。所有拟议的研究都是基于我们几乎完全沉浸在许多不同复杂性状的基因型与表型相关的研究（以及开发将基因型与表型相关的方法）中。因此，我们的具体目标是：1）发现跨组织和组织特异性的调控变异，并利用所得信息来发现新的风险途径，并将疾病遗传性划分为与不同类别的功能变异相对应的成分； 2）测试由于GTEx程序的独特设计而最终可行的假设，包括性别和其他环境暴露对调节变异的作用，以及转录中功能丧失和错义变异的作用； 3) 使用系统和网络方法更好地理解跨组织基因表达的组织。通过该项目开发的所有软件和数据库将立即公开。