Mapping the first half of the REFERENCE human binary protein interactome

绘制参考人类二元蛋白质相互作用组的前半部分

• 批准号: 8245460
• 负责人: David E. Hill
• 金额: $ 185.11万
• 依托单位: DANA-FARBER CANCER INST
• 依托单位国家: 美国
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-07-01 至 2015-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8245460
• 关键词: Address; Animal Model; Beryllium; Biological; Biological Process; Biology; Biomedical Research; Cell Line; Cells; Code; Collaborations; Complement; Complex; Cosmids; DNA; DNA Sequence; Data; Data Quality; Data Set; Development; Disease; Enzymes; Fluorescence; Genes; Genome; Genotype; Goals; Grant; Hand; Human; Human Genome; Lasers; Literature; Maps; Methods; Modeling; Nature; Network-based; Open Reading Frames; Organism; Paper; Phase; Phenotype; Play; Process; Protein-Protein Interaction Map; Proteins; Proteome; Publishing; RNA; Resources; Role; Science; Scientist; Systems Biology; Technology; Testing; Therapeutic Intervention; Time; Tissues; Work; YAC Clone; base; complex biological systems; cost; gene cloning; genome sequencing; improved; in vivo; innovation; insight; macromolecule; next generation; predictive modeling; protein protein interaction; scaffold

DESCRIPTION (provided by applicant): Complex biological systems and cellular networks underlie most genotype to phenotype relationships. In the last decade, basic concepts of network biology have been described, emphasizing why cellular networks are important to consider in biology. Importantly, it is becoming increasingly clear that more high quality empirically derived datasets are needed to better describe biological networks and genotype to phenotype relationships. The interactome of an organism is the network formed by the complete set of interactions that can occur in a physiologically relevant dynamic range between all its macromolecules, including protein-protein, DNA-protein, RNA-protein, and RNA-RNA interactions. In this proposal, we focus on high-throughput (HT), proteome-scale mapping of what we refer to as the REFERENCE human binary protein-protein interactome network map. Major innovations in this application enable to define a clear roadmap for completion of this REFERENCE map by the end of this decade. During this coming cycle, we will expand the human HT binary interactome map from ~15% coverage, which is the milestone of the current cycle, to ~50%. We will also briefly discuss how we foresee further expansion to near completeness thereafter. The accumulation of DNA sequencing data exploded for the Human Genome Sequencing project in the 1990s when four crucial elements were assembled: i) cosmids, BAC, and YAC clone resources covering most of the genome; ii) automated laser-fluorescence sequencing, iii) the PHRED score used to systematically assess sequencing data quality, and iv) the development of "hands-off" automated experimental steps. We describe below how the human binary interactome mapping project is reaching a similarly exploding phase: i) having significantly contributed to the ORFeome Collaboration (OC) we now have a nearly complete protein-coding ORF clone resource, ii) we developed a new strategy to apply the power of next-generation sequencing to interactome mapping, iii) we have published a new empirical framework that systematically assess interactome mapping data quality, and iv) we will describe new "hands-off" automated strategies that greatly increase throughput and decrease cost. Our specific aims are: i) to expand human binary interactome mapping to a full complement of protein-coding genes cloned by OC, ii) to reach ~50% coverage of the REFERENCE human binary interactome network map, and iii) to expand global network analyses of our newly mapped human binary interactome network. PUBLIC HEALTH RELEVANCE: The availability of (nearly) complete genome sequences for several model organisms and for human is changing the way scientists formulate and address biological questions. With large numbers of protein predictions, the traditional one-at-a-time approach can now be complemented by more global strategies that consider all proteins at once. Such approaches, referred to as "systems biology" have the ultimate goal of providing quantitative and dynamic models to describe biological processes. One major impediment to this prospect however is that most predicted proteins have not yet been experimentally characterized in detail. Interactome maps can be used to formulate functional hypotheses for thousands of uncharacterized genes. In addition, global features of the resulting interactome networks have been proposed that provide worthwhile biological insights. From these insights and hypotheses, a better understanding of disease processes and better strategies for therapeutic intervention are anticipated.

描述（由申请人提供）：复杂的生物系统和细胞网络是大多数基因型与表型关系的基础。在过去的十年中，网络生物学的基本概念已经被描述，强调了为什么细胞网络在生物学中是重要的。重要的是，越来越清楚的是，需要更多高质量的经验数据集来更好地描述生物网络和基因型与表型的关系。生物体的相互作用组是由一整套相互作用形成的网络，这些相互作用可以在其所有大分子之间的生理相关动态范围内发生，包括蛋白质-蛋白质、DNA-蛋白质、RNA-蛋白质和RNA-RNA相互作用。在这个建议中，我们专注于高通量（HT），蛋白质组规模的映射，我们称之为参考人类二元蛋白质-蛋白质相互作用组网络图。该应用程序的主要创新使我们能够为在本十年末完成该参考地图定义一个清晰的路线图。在即将到来的周期中，我们将把人类HT二元相互作用组图谱的覆盖率从当前周期的里程碑--约15%扩大到约50%。我们还将简要地讨论我们如何预见进一步扩大到接近完成之后。DNA测序数据的积累在20世纪90年代为人类基因组测序项目爆发，当时组装了四个关键要素：i）覆盖大部分基因组的cosmetry，BAC和YAC克隆资源; ii）自动化激光荧光测序，iii）用于系统评估测序数据质量的PHRED评分，以及iv）“放手”自动化实验步骤的开发。我们在下面描述了人类二元相互作用组映射项目是如何达到类似的爆炸阶段的：i）在对ORFeome协作（OC）做出重大贡献之后，我们现在拥有几乎完整的蛋白质编码ORF克隆资源，ii）我们开发了一种新策略，将下一代测序的力量应用于相互作用组作图，iii）我们已经发表了一个新的经验框架，该框架系统地评估相互作用组作图数据质量，以及iv）我们将描述新的“不干涉”自动化策略，该策略大大增加了吞吐量并降低了成本。我们的具体目标是：i）将人类二元相互作用组图谱扩展到OC克隆的蛋白质编码基因的完整互补，ii）达到参考人类二元相互作用组网络图谱的约50%覆盖率，以及iii）扩展我们新绘制的人类二元相互作用组网络的全球网络分析。 公共卫生关系：几种模式生物和人类的（几乎）完整基因组序列的可用性正在改变科学家制定和解决生物学问题的方式。随着大量的蛋白质预测，传统的一次一个的方法现在可以通过一次考虑所有蛋白质的更全局的策略来补充。这种方法被称为“系统生物学”，其最终目标是提供定量和动态模型来描述生物过程。然而，这一前景的一个主要障碍是，大多数预测的蛋白质还没有被详细地实验表征。相互作用基因组图谱可以用于为数千个未表征的基因制定功能假设。此外，全球功能所产生的相互作用网络已被提出，提供有价值的生物学见解。从这些见解和假设，更好地了解疾病的过程和更好的治疗干预策略的预期。