GWAS TO GENE FUNCTION: NOS1AP AND OTHER QT INTERVAL GENES

描述(由申请人提供)：对心电图QT间期的全基因组关联研究(GWAS)，这是一种影响长QT综合征和心脏性猝死风险的中间性状，已在35个基因座识别出68个独立变异，解释了表型变异的8%(相加变异的20%)。然而，潜在的DNA序列变体和基因的同一性、功能和作用机制仍然未知，并且是理解这种复杂表型的分子结构和功能结构的主要障碍。我们假设大多数功能性状变异是通过改变其顺式调控元件的功能来实现特定基因的多态、非编码和干扰转录。我们提出了一种研究范式，用于系统地识别这些非编码性状变异、它们扰乱的调控功能以及在每个数量性状基因座上功能改变的特定基因。我们将利用遗传学、计算、分子遗传学和细胞学的综合统计方法，以QT间期为模型‘系统’来阐明潜在的机制。我们的具体目标是：(1)对Gwas信号进行高分辨率定位，以识别调控QT间期的基因座上的所有多态(&gt；1%)和罕见变异；(2)进行计算机和体外分析，以预测和优先考虑所有心脏调节元件(增强子、沉默因子、绝缘体)元件和它们的同源DNA结合蛋白；以及(3)识别性状变异、基因及其遗传作用机制。总体目标是改善对多因素性状的分子遗传和机制的理解，以便应用于其他复杂的表型。

DESCRIPTION (provided by applicant): Genome-wide association studies (GWAS) of the electrographic QT-interval, an intermediate trait that impacts the risks of long QT syndrome and sudden cardiac death, have identified 68 independent variants at 35 loci, explaining 8% of the phenotypic (20% of the additive) variance. Nevertheless, the identity, function and mechanisms of action of the underlying DNA sequence variants and genes remain unknown, and are major impediments for understanding the molecular structure and functional architecture of this complex phenotype. We hypothesize that the majority of functional trait variants are polymorphic, non-coding and perturb transcription of a specific gene by altering the functions of their cis-regulatory elements. We propose a research paradigm for systematically identifying these non-coding trait variants, the regulatory functions they disrupt and the specific genes whose functions are altered at each quantitative trait locus. We will utilize integrative statisticl genetic, computational, molecular genetics and cellular approaches for elucidating the underlying mechanisms, using QT interval as a model 'system'. Our specific aims are: (1) to perform high- resolution mapping of GWAS signals to identify all polymorphic (>1%) and rare variants at loci that modulate the QT-interval; (2) to conduct in silico and in vitro analysis to predict and prioritize all cardiac regulatory (enhancer, silencer, insulator) elements and their cognate DNA-binding proteins; and, (3) to identify trait variants, genes and their mechanisms of genetic action. The overall goals are to improve the molecular genetic and mechanistic understanding of multifactorial traits for applications to other complex phenotypes.