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)的总体目标是从功能上表征影响蛋白质编码基因的人类遗传变异，这些变异与从简单的孟德尔疾病到复杂的特征等疾病有关，从细胞网络的角度来看，这些疾病更难建模和预测。我们将发展概念、技术和系统的数据集，从功能上描述大量的基因类型对分子功能和相应基因产物介导的物理和生化相互作用的影响，这对阐明人类基因-基因相互作用、了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，实验性地绘制、建模和预测选定遗传性疾病的人类大分子相互作用网络(“参考EDG型”)，ii)系统地揭示由等位基因扰动修改的蛋白质相互作用图(“等位EDG型”)，以揭示疾病亚型和机制，以及iii)建立可能解释这些疾病所涉及的基因-基因相互作用的分子路径，并使用这些模型来使检测非加性结合以预测疾病风险的等位基因组合成为可能。CEGS的高风险/高回报方面将是：i)对GWA研究中出现的疾病基因候选进行优先排序，并进行突变测序；ii)解决复杂性状中的“缺失遗传性问题”；以及iii)展示EDGO分型如何帮助我们更好地预测疾病结果。综上所述，我们的具体目标是：i)为选定的疾病模块生成深入、稳健的交互组网(参考edgotype)，ii)生成与相应的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edgotype图(等位基因edgotype)，iii)利用edgotype数据来识别新的疾病亚型，以及 为了能够发现非加性预测疾病风险的等位基因组合，iv)在“EDGOGING倡议”的背景下，与专门研究一种或几种人类遗传病的人类遗传学实验室建立一个跨学科的协作环境，v)提供以新的实验和计算方法为中心的培训和推广计划。

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.