Functional Profiling of Human Disease Targets

人类疾病靶标的功能分析

基本信息

批准号：
8896825
负责人：
Michael A Calderwood
金额：
$ 45.27万
依托单位：
DANA-FARBER CANCER INST
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-08-01 至 2018-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8896825
关键词：
Bardet-Biedl Syndrome Biochemical Biological Process Cells Code Complex Congenital Megacolon DNA Sequence DNA Sequence Alteration Data Diagnostic Disease Etiology Excision Exhibits Genes Genetic Heterogeneity Genetic Variation Genotype Goals Health Hereditary Disease Human Human Genetics Inborn Genetic Diseases Individual Lead Link Macromolecular Complexes Maps Measures Methods Modeling Molecular Mutation Outcome Patients Phenotype Property Protein-Protein Interaction Map Proteins Proteome Relative (related person)Retinitis Pigmentosa Solutions System Therapeutic Therapeutic Intervention Time Tissues Usher Syndrome Variant Work clinical phenotype disease classification disease-causing mutation disorder subtype genetic variant human disease human genome sequencing improved insight knockout gene macromolecule network models next generation sequencing pleiotropism trait

项目摘要

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.

描述（由申请人提供）：我们在此提案中的总体目标是在与一组模型复杂疾病相关的人类基因中的功能分析突变，并获得了大量未表征的遗传变异。有了了解多个个体的完整基因型以及越来越复杂的表型方法，生物医学现在可以通过机械细节探索基因型 - 表型关系。在基因型的表征中要解决的基本问题是遗传变异如何直接与表型相关。我们的前提是仅序列就不够。需要的是一种破坏性的转变，以更好地理解基因型差异的功能和机械分子后果。我们解决这个具有挑战性的问题的解决方案是研究复杂的大分子网络或“相互作用”，该网络由细胞内部的大量相互作用的基因和基因产物以及由于遗传变异而发生的这些网络的扰动。在通过Interactome网络方法来表征基因型 - 对表型的关系时，基因型变化可以导致完整的基因敲除，该基因型敲除，被建模为删除节点及其在网络中的所有边缘，或者作为交互作用特异性扰动，导致删除或加强特定的相互作用，以使特定的相互作用或增强为边缘，以边缘为模型，或者是Edgefient的特定相互作用。我们建议，为了更好地理解基因型 - 表型关系，“ Edgotypes”的特征在于系统地确定每种生物物理相互作用的节点去除状态与散热性扰动的状态。这些策略将应用于一小部分之所以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；色素性视网膜炎； Hirschsprung疾病； Bardet-Biedl综合征）也进行了足够的研究，已知已知足够数量的突变可以在足够的深度上进行足够的EDGOTSING分析以产生信息性疾病网络。对这四种临床表型的研究应相应地提供对基因型 - 表型关系的基本见解，DNA序列变体对特定生物学功能，疾病模块和疾病分类的影响。我们的具体目的是：i）为选定的一组临床表型生成深层且鲁棒的相互作用网络图，ii）在基因产物中生成扰动的物理和生物化学相互作用的预型图，与所选临床表型相关的基因产物中的基因产物中的基因产物，III，iii）对基因型的相关型相关性，以启用基因型的相关性，以启用基因型的相关性。临床表型。