Large-scale inference of gene function through phylogenetic annotation of Gene Ontology terms: case study of the apoptosis and autophagy cellular processes
Large-scale inference of gene function through phylogenetic annotation of Gene Ontology terms: case study of the apoptosis and autophagy cellular processes
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DOI：
10.1093/database/baw155
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发表时间：
2016-12-26
影响因子：
5.8
通讯作者：
Thomas, Paul D.
中科院分区：
文献类型：
--
作者：
Feuermann, Marc;Gaudet, Pascale;Thomas, Paul D.
我们以前报道了一个范例，大规模的基因家族的基因组学分析，利用实验支持的基因本体论（GO）注释的大型语料库。这种“GO系统发育注释”方法在基因家族树的背景下整合了来自100种不同生物体中进化相关基因的GO注释，其中管理员构建了基因功能进化的明确模型。GO系统发育注释模型在基因家族树中的功能的获得和丧失，其用于推断未表征（或不完全表征）的基因产物的功能，即使对于相对较好研究的人类蛋白质也是如此。在这里，我们报告我们的结果，从应用这种模式，两个良好的特征细胞过程，细胞凋亡和自噬。这揭示了关于GO注释的几个重要观察以及它们如何用于函数推理。值得注意的是，我们只应用了一小部分实验支持的GO注释来推断其他家族成员的功能。大多数其他注释描述了间接效应、表型或来自高通量实验的结果。此外，我们在这里展示了系统发育注释的反馈如何导致PANTHER树，GO注释和GO本身的显着改进。因此，GO系统发育注释既增加了数量，又提高了提供给研究社区的GO注释的准确性。我们期望这些基于遗传学的注释在基因富集分析以及GO注释的其他应用中具有广泛的用途。
We previously reported a paradigm for large-scale phylogenomic analysis of gene families that takes advantage of the large corpus of experimentally supported Gene Ontology (GO) annotations. This 'GO Phylogenetic Annotation' approach integrates GO annotations from evolutionarily related genes across similar to 100 different organisms in the context of a gene family tree, in which curators build an explicit model of the evolution of gene functions. GO Phylogenetic Annotation models the gain and loss of functions in a gene family tree, which is used to infer the functions of uncharacterized (or incompletely characterized) gene products, even for human proteins that are relatively well studied. Here, we report our results from applying this paradigm to two well-characterized cellular processes, apoptosis and autophagy. This revealed several important observations with respect to GO annotations and how they can be used for function inference. Notably, we applied only a small fraction of the experimentally supported GO annotations to infer function in other family members. The majority of other annotations describe indirect effects, phenotypes or results from high throughput experiments. In addition, we show here how feedback from phylogenetic annotation leads to significant improvements in the PANTHER trees, the GO annotations and GO itself. Thus GO phylogenetic annotation both increases the quantity and improves the accuracy of the GO annotations provided to the research community. We expect these phylogenetically based annotations to be of broad use in gene enrichment analysis as well as other applications of GO annotations.