Functional Characterization of the Genetic and Environmental Determinants of Comp

描述(申请人提供)：与复杂特征相关的功能变异往往落在非编码区，并影响尚未很好表征的调节机制。此外，通常很难确定它们在哪些组织和条件下可能会对功能产生影响。这是因为基因变异对分子途径的影响，以及最终对个体表型的影响，可能会受到“环境”因素的影响。我们将这些变异命名为“基因表达环境特异性数量性状核苷酸”GxE-QTns。更好地了解GxE-QTNS的机制是了解基因和复杂表型之间联系的关键一步。同样重要的是开发计算高效和统计合理的方法，能够整合特定组织/条件的功能基因组数据，以预测和验证序列变体何时具有功能。我们建议开发新的实验和计算方法来筛选、分析和功能表征受环境暴露调节的复杂性状的遗传变异。为了鉴定和表征GxE-QTN，我们将分析一组相关组织(例如心血管疾病的血管内皮细胞)在一系列受控环境条件下(例如糖皮质激素治疗，作为应激暴露的替代)中的等位基因特异性表达。拟议的计算工具将整合不同的证据来源，包括ENCODE、路线图Eigenome和GTEx项目收集的数据，以从功能上注释Gwas变体。该项目开发的实验和计算工具具有广泛的适用性；例如，可用于在其他环境背景(例如，其他类型的压力和荷尔蒙水平)和遗传背景下处理复杂性状的功能基础。与公众健康相关：我们的发现将代表第一个全面的基因变异目录，这些基因变异在确定人类复杂特征时与环境暴露相互作用。

DESCRIPTION (provided by applicant): Functional variants associated with complex traits tend to fall in non-coding regions and affect regulatory mechanisms that are not yet well characterized. Furthermore, it is generally difficult to determine in which tissues and conditions they may have a functional impact. This is because the effect of a genetic variant on a molecular pathway, and ultimately on the individual's phenotype, may be modulated by "environmental" factors. We denominate such variants "gene-expression environment-specific quantitative trait nucleotides" GxE-QTNs. Achieving a better understanding of the mechanisms underlying GxE-QTNs is a critical step in understanding the link between genotype and complex phenotype. It is also crucial to develop computationally efficient and statistically sound methods capable to integrate tissue/condition-specific functional genomics data to predict and validate when a sequence variant is functional. We propose to develop novel experimental and computational approaches to screen, analyze and functionally characterize genetic variants for complex traits modulated by environmental exposures. To identify and characterize GxE-QTNs, we will analyze allele specific gene expression in a panel of relevant tissues (e.g. the vascular endothelium for cardiovascular diseases) under a series of controlled environmental conditions (e.g. glucocorticoids treatment, as a proxy for stress exposure). The proposed computational tools will integrate different sources of evidence including data collected by ENCODE, Road Map Epigenome and GTEx projects to functionally annotate GWAS variants. The experimental and computational tools developed by this project have widespread applicability; for example, can be used to tackle the functional basis of complex traits in other environmental contexts (e.g. other types of stress and hormonal levels) and genetic backgrounds. Relevance to public health: Our findings will represent the first comprehensive catalog of genetic variants that interact with environmental exposure in determining human complex traits.