Functional Profiling of Human Disease Targets

描述（由申请人提供）：我们在该提案中的总体目标是功能性分析与一组模型复杂疾病相关的人类基因突变，已获得大量未表征的遗传变异。随着了解多个个体的完整基因型的前景和测量表型的日益复杂的方法，生物医学现在可以探索基因型-表型关系的机制细节。基因型表征中需要解决的一个基本问题是遗传变异如何直接与表型相关。我们的前提是，仅仅序列是不够的。我们需要的是一个颠覆性的转变，以更好地了解基因型差异的功能和机制的分子后果。我们对这个具有挑战性的问题的解决方案是调查复杂的大分子网络，或“interactomes”，形成了大量的相互作用的基因和基因产物的细胞内，这些网络的扰动发生的遗传变异的结果。在通过相互作用组网络方法表征基因型与表型的关系时，基因型变异可以导致完全基因敲除，建模为网络中节点及其所有边缘的去除，或者可替代地，作为相互作用特异性扰动，导致特定相互作用的去除或加强，建模为边缘特异性或“边缘”扰动。我们建议，为了更好地理解基因型-表型的关系，“edgotypes”的特点是系统地建立节点删除与边缘扰动的状态，为每一个生物物理相互作用。这些策略将应用于一小部分 选择复杂的临床表型是因为它们表现出广泛的遗传异质性、多效性和表型重叠。这四种临床表型（Usher综合征;视网膜色素变性;先天性巨结肠; Bardet-Biedl综合征）也已被充分研究，已知大量突变能够在足够的深度进行边缘分型分析，以生成信息丰富的疾病网络。因此，这四种临床表型的研究应提供基因型-表型关系，DNA序列变异对特定生物学功能，疾病模块和疾病分类的影响的基本见解。我们的具体目标是：i）为所选的一组临床表型生成深度和稳健的相互作用组网络图，ii）生成在所选的一组临床表型中涉及的基因产物之间的扰动的物理和生化相互作用的边缘型图，iii）通过计算利用边缘分型数据以获得对所选的一组临床表型的基因型-表型关系的机制分子见解。

DESCRIPTION (provided by applicant): Our overall goal in this proposal is to functionally analyze mutations in human genes associated with a set of model complex disorders for which a large number of uncharacterized genetic variants have been obtained. With the prospect of knowing the complete genotype of multiple individuals and with increasingly sophisticated ways of measuring phenotypes, biomedicine can now explore genotype-phenotype relationships in mechanistic detail. A fundamental issue to be resolved in the characterization of genotypes is how genetic variation directly relates to phenotype. Our premise is that sequence alone is not sufficient. What is needed is a disruptive shift to better understand the functional and mechanistic molecular consequences of genotypic differences. Our solution to this challenging problem is to investigate the complex macromolecular networks, or "interactomes", formed by large numbers of interacting genes and gene products inside cells and to the perturbations of these networks that occur as a consequence of genetic variation. In characterizing genotype- to-phenotype relationships via an interactome network approach, genotypic variation can lead to either a complete gene knockout, modeled as removal of a node and all of its edges in the network, or alternatively, as interaction-specific perturbation, leading to the removal or strengthening of specific interactions, modeled as edge-specific, or "edgetic" perturbations. We propose that to better understand genotype-phenotype relationships, "edgotypes" should be characterized by systematically establishing the state of node removal versus edgetic perturbations for every biophysical interaction. These strategies will be applied to a small set of complex clinical phenotypes chosen because they exhibit extensive genetic heterogeneity, pleiotropy and phenotypic overlap. These four clinical phenotypes (Usher syndrome; retinitis pigmentosa; Hirschsprung disease; Bardet-Biedl syndrome) have also been studied enough that ample numbers of mutations are known to enable edgotyping profiling at sufficient depth to generate informative disease networks. Study of these four clinical phenotypes should accordingly provide fundamental insights into genotype-phenotype relationships, the impact of DNA sequence variants on specific biological functions, disease modules, and disease classification. Our specific aims are to: i) Generate deep and robust interactome network maps for the selected set of clinical phenotypes, ii) Generate edgotypic maps of perturbed physical and biochemical interactions amongst gene products implicated in the selected set of clinical phenotypes, iii) Exploit edgotyping data computationally to derive mechanistic molecular insights into genotype-phenotype relationships for the selected set of clinical phenotypes.