Comprehensive annotation of subcellular localization of entire organisms

描述（由申请人提供）：具有已知序列的蛋白质和具有充分研究的功能的蛋白质（序列-功能缺口）之间的差异每天都在增长。功能的一个明确定义的粗粒度方面是在基因本体论（GO）层次结构中发挥核心作用的蛋白质的天然亚细胞定位。许多详细的和高通量的实验注释本地化。在实验没有达到的地方，基于同源性和从头预测方法取得了成功。在这里，我们提出了一个全面的系统，结合实验资源与数据挖掘技术和新的预测方法，其目的是注释定位完全测序的真核生物在一个前所未有的细节和准确性的发展。首先，我们建议收集所有可用的数据和所有相关的方法来建立一个全面的定位图谱为人类和拟南芥。其次，我们计划开发专门用于捕获蛋白质的新方法，在完成第一步后，我们没有留下可靠的注释。我们假设，这些方法将集中在预测的特定类型的膜插入一个完整的膜蛋白，和本地化的小真核细胞室（ER，高尔基体，溶酶体）。第三，我们建议实施的具体改进，今天的基序为基础的方法分泌和核蛋白，以及扩展的从头预测的主要车厢。一个重要的目标将是保持剪接变体和序列片段的高水平性能。总的来说，该项目将需要分析现有的生物数据库，开发新的方法，并结合现有的方法;它将通过互联网服务器，独立程序和数据库生成新的信息。 相关性：我们的系统生成的注释将有助于详细和高通量实验研究的设计。特别是，本地化可能会增加其相关性作为一个基本特征，用于推断网络的互动。我们项目的最终目标是生成一个图谱，映射细胞中的所有蛋白质。最终，这个图谱将构成一个4D图谱;它将定位蛋白质在其3D细胞环境中的位置，并解析系统的粗粒度动力学，例如“在核糖体上表达，结合输入蛋白，运输到细胞核中，结合DNA，结合输出蛋白，输出到细胞核外;下一个细胞周期”。这里提出的组件构成了一个关键的构建块，朝着这样一个细胞的4D地图。

DESCRIPTION (provided by applicant): The difference between the number of proteins with known sequence and those with well- studied function (sequence-function gap) is growing daily. One well-defined coarse-grained aspect of function is the native subcellular localization of a protein that has a central role in the Gene Ontology (GO) hierarchy. Many detailed and high-throughput experiments annotate localization. Where experiments do not reach, homology-based and de novo prediction methods succeed. Here, we propose the development of a comprehensive system that combines experimental resources with data mining techniques and novel prediction methods with the objective to annotate localization for entirely sequenced eukaryotes at an unprecedented detail and accuracy. Firstly, we propose to gather all available data and all relevant methods to build a comprehensive localization atlas for human and Arabidopsis. Secondly, we plan to develop novel methods tailored specifically to capture proteins for which we are left with no reliable annotations after completing the first step. We assume that these methods will focus on the prediction of the particular type of membrane into which an integral membrane protein is inserted, and of the native localization for minor eukaryotic compartments (ER, Golgi, lysosome). Thirdly, we propose the implementation of specific improvements over today's motif-based methods for secreted and nuclear proteins, as well as the extension of de novo predictions for the major compartments. An important objective will be to maintain high levels of performance for splice variants and for sequence fragments. Overall, the project will require the analysis of existing biological databases, the development of novel methods, and the combination of existing ones; it will generate novel information available through internet servers, standalone programs and databases. RELEVANCE: The annotations generated by our system will aid the design of detailed and high-throughput experimental studies. In particular, localization may increase in its relevance as one essential feature used to infer networks of interactions. The ultimate goal of our project is the generation of an atlas that maps all proteins in a cell. Eventually, this atlas will constitute a 4D map; it will localize proteins in their 3D cellular environments and resolve the coarse-grained dynamics of the system, e.g. "expression on ribosomes, bind importin, transport into nucleus, bind DNA, bind exportin, export out of nucleus; next cell cycle". The components proposed here constitute one crucial building block toward such a 4D map of a cell.