Comprehensive annotation of subcellular localization of entire organisms

描述(由申请人提供)：已知序列的蛋白质数量与已充分研究功能的蛋白质数量(序列-功能缺口)之间的差异日益扩大。一个定义明确的粗粒度功能方面是蛋白质的天然亚细胞定位，该蛋白质在基因本体论(GO)层次结构中具有核心作用。许多详细和高通量的实验诠释了本地化。在实验不能达到的地方，基于同源性和从头开始的预测方法成功了。在这里，我们建议开发一个综合的系统，将实验资源与数据挖掘技术和新的预测方法相结合，目的是以前所未有的详细和准确的方式注释完全测序的真核生物的定位。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人类和拟南芥的定位图谱。其次，我们计划开发专门为捕获蛋白质量身定做的新方法，这些蛋白质在完成第一步后没有可靠的注释。我们认为这些方法将侧重于预测插入完整膜蛋白的特定膜类型，以及微小真核细胞间隔(内质网、高尔基体、溶酶体)的天然定位。第三，我们建议对目前基于基序的分泌蛋白和核蛋白方法进行具体改进，并扩展对主要隔室的从头预测。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。总体而言，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；它将产生可通过互联网服务器、独立程序和数据库获得的新信息。 相关性：我们的系统生成的注释将有助于设计详细和高通量的实验研究。特别是，本地化可能会增加其作为用于推断交互网络的一个基本特征的相关性。我们项目的最终目标是生成一份绘制细胞中所有蛋白质的图谱。最终，这一图谱将构成一张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Importin，运输到细胞核，结合DNA，结合Exportin，输出到细胞核；下一个细胞周期。这里提出的组件构成了构建这样一个细胞的4D图的关键构件。

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.