BBSRC-NSF/BIO:CIBR:Implementing an explicit phylogenetic framework for large-scale protein sequence annotation

技术进步使研究人员能够确定数千种生物体中数百万种不同蛋白质的化学组成（序列）。 然而，利用这些信息在应用中，如医学和农业需要额外的工作，以确定这些蛋白质的功能，他们在分子和生物体水平上做什么。 确定新蛋白质功能的第一步是将其序列与已通过实验分析功能的其他蛋白质进行比较。 在以前的资助下，开发了用于重建每组相关蛋白质进化历史的计算方法，并将此历史用于提出在进化过程中保守的功能，并为蛋白质功能分析提供起点。这项工作的下一步是将其应用于数百万可用的蛋白质序列，并将该方法扩展到包括有关蛋白质功能的更详细信息。 该项目将开发和测试我们的方法的实际生产级实现，并将其应用于世界上最大的蛋白质序列数据库UniProt。 UniProt是公开的，因此结果将被科学家和非科学家广泛使用。 UniProt蛋白质知识库的目标是最大化蛋白质序列数据对科学界的效用，它不仅表示序列本身，而且还表示注释：描述可以推断这些序列的信息的元数据，例如预测的蛋白质功能。 目前对UniProt进行大规模注释的方法称为UniRule，它依赖于专门的规则来定义应进行类似注释的蛋白质组。 虽然这些规则隐含地利用了关于进化关系的信息（例如蛋白质家族中的成员），但它们并没有明确地对功能进化进行建模，因此在它们可以表达的注释的特异性方面受到限制。 该项目实现了一个显式的进化方法来大规模序列注释，建立在以前的工作1）在基因家族中蛋白质功能的获得和丧失（表示为来自基因本体论的术语）的进化建模，以及2）在软件上重建任何任意蛋白质序列的进化历史，通过将其放置在系统发育树的上下文中。这种方法在UniProt资源中的生产级实施将整合UniProt和基因本体项目中已经使用的大规模注释系统，并导致UniProt知识库中注释的特异性和覆盖范围增加。该项目将显著改善UniProt知识库中数千万序列的注释，影响庞大的UniProt用户群。它还将为UniProt中大量完全测序的基因组的基于基因本体的分析提供注释，使此类分析更广泛地可用。 一个新的蛋白质功能进化的在线教育模块将从这个模块开始，包括其他可用的在线模块。 该奖项反映了NSF的法定使命，并已被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

Technological advances have enabled researchers to determine the chemical composition (sequence) of millions of different proteins from thousands of organisms. However, making use of this information in applications such as medicine and agriculture requires additional work to determine the functions of these proteins-what they do at the molecular and organism levels. The first step in determining function of a new protein is to compare its sequence to other proteins whose functions have been analyzed experimentally. Under previous funding, computational methods for reconstructing the evolutionary history of each group of related proteins developed and this history was used to suggest functions that have been conserved during evolution and provide the starting point for protein function analysis. The next step in this work is to enable application to the millions of protein sequences available, and to extend the method to include more detailed information about protein function. This project will develop and test a practical, production-grade implementation of our method, and apply it to UniProt, the world's largest database of protein sequences. UniProt is publicly available, so results will be broadly available and usable by both scientists and non-scientists alike. Educational materials will be developed to help make the results more accessible to students and non-scientists.The UniProt protein knowledgebase aims to maximize the utility of protein sequence data to the scientific community by representing not only the sequences themselves, but also annotations: metadata describing information that can be inferred about those sequences, such as predicted protein function. The current approach to large-scale annotation of UniProt, called UniRule, relies on ad hoc rules to define sets of proteins that should be annotated similarly. While these rules implicitly utilize information about evolutionary relationships (e.g. membership in a protein family), they do not model function evolution explicitly and are therefore limited in the specificity of annotations they can express. This project implements an explicit evolutionary approach to large-scale sequence annotation, building upon previous work 1) on evolutionary modeling of gain and loss of protein functions (represented as terms from the Gene Ontology) in gene families, and 2) on software to reconstruct the evolutionary history any arbitrary protein sequence by placing it in the context of a phylogenetic tree. Production-level implementation of this approach within the UniProt resource will integrate the large-scale annotation systems already used in the UniProt and Gene Ontology projects, and result in increased specificity and coverage of annotations in the UniProt knowledgebase. The project will significantly improve annotations on tens of millions of sequences in the UniProt knowledgebase, impacting the massive UniProt user base. It will also provide the annotations for Gene Ontology-based analyses of the large number of fully sequenced genomes in UniProt, making such analyses more broadly available. A new online educational module for protein function evolution will curate a learning path starting with this module and including other available online modules. The results will be available in the UniProt resource (uniprot.org), and all software and annotation metadata will be available at pantree.org.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.