Genomic Analysis of Network Perturbations in Human Disease

描述（由申请人提供）：我们的基因组科学卓越中心（CEGS）的总体目标是对影响蛋白质编码基因的人类遗传变异进行功能表征，这些基因变异与从简单的孟德尔疾病到复杂性状的疾病有关，这些疾病从细胞网络的角度来看很难建模和预测。我们将开发概念、技术和系统的数据集，从它们对相应基因产物介导的分子功能和物理生化相互作用的影响方面对大量基因型进行功能表征，这对阐明人类基因-基因相互作用、理解遗传力和改进基因组医学具有重要意义。为了实现我们的目标，我们将i)收集现有信息，通过实验绘制、建模和预测选定遗传疾病的人类大分子相互作用网络（“参考基因型”），ii)系统地揭示由等位基因扰动修饰的蛋白质相互作用图（“等位基因型”），以揭示疾病亚型和机制，iii)建立可能解释这些疾病中涉及的基因-基因相互作用的分子路径模型。并利用这些模型来检测非加性的等位基因组合来预测疾病风险。这种CEGS的高风险/高回报方面将是：i)优先考虑从GWA研究中出现的疾病候选基因，以及突变测序，ii)解决复杂性状中的“缺失遗传性问题”，以及iii)证明基因分型将如何帮助我们更好地预测疾病结果。总之，我们的具体目标是：i)为选定的疾病模块（“参考基因型”）生成深度、健壮的相互作用组网络，ii)生成与相应人类疾病相关的基因产物之间受干扰的物理和生化相互作用的基因型图（“等位基因型”），iii)利用基因型数据识别新的疾病亚型，以及

DESCRIPTION (provided by applicant): The overall goal of our Center of Excellence in Genome Sciences (CEGS) is to functionally characterize human genetic variants affecting protein-coding genes that are associated with disorders ranging from simple Mendelian diseases to complex traits, which are much harder to model and predict from a cellular network point-of-view. We will develop concepts, technologies and systematic datasets to functionally characterize large numbers of genotypes in terms of the effects they have on the molecular functions and physical and biochemical interactions mediated by the corresponding gene products, with implications for elucidating human gene-gene interactions and understanding heritability and improving genomic medicine. To achieve our goal, we will i) gather existing information, experimentally map, model and predict networks of human macromolecular interactions for selected inherited disorders ("reference edgotypes"), ii) systematically reveal protein interaction maps modified by allelic perturbation ("allelic edgotypes") to uncover disease subtypes and mechanisms, and iii) model molecular paths that likely explain gene-gene interactions involved in these disorders, and use these models to empower the detection of allele combinations that combine non-additively to predict disease risk. The high-risk/high-reward aspects of this CEGS will be: i) prioritizing disease gene candidates emerging from GWA studies, and mutation sequencing, ii) solving the "missing heritability problem" in complex traits, and iii) demonstrating how edgotyping will help us to better predict disease outcomes. In summary, our specific aims are to: i) Generate deep, robust interactome networks for selected disease modules ('reference edgotypes'), ii) Generate edgotypic maps of perturbed physical and biochemical interactions amongst gene products implicated in the corresponding human disorders ('allelic edgotypes'), iii) Exploit edgotyping data to identify new disease subtypes, and to empower discovery of allele combinations that non-additively predict disease risk, iv) Establish an inter-disciplinary collaborative environment with human genetics laboratories specialized in one or a few human genetic diseases in the context of the "Edgotyping Initiative", v) Provide a training and outreach program centered on novel experimental and computational methods.