Alam-Faruque Yasmin, Hill David P, Dimmer Emily C, Harris Midori A, Foulger Rebecca E, Tweedie Susan, Attrill Helen, Howe Douglas G, Thomas Stephen Randall, Davidson Duncan, Woolf Adrian S, Blake Judith A, Mungall Christopher J, O'Donovan Claire, Apweiler Rolf, Huntley Rachael P
European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom.
The Jackson Laboratory, Bar Harbor, Maine, United States of America.
PLoS One. 2014 Jun 18;9(6):e99864. doi: 10.1371/journal.pone.0099864. eCollection 2014.
Gene Ontology (GO) provides dynamic controlled vocabularies to aid in the description of the functional biological attributes and subcellular locations of gene products from all taxonomic groups (www.geneontology.org). Here we describe collaboration between the renal biomedical research community and the GO Consortium to improve the quality and quantity of GO terms describing renal development. In the associated annotation activity, the new and revised terms were associated with gene products involved in renal development and function. This project resulted in a total of 522 GO terms being added to the ontology and the creation of approximately 9,600 kidney-related GO term associations to 940 UniProt Knowledgebase (UniProtKB) entries, covering 66 taxonomic groups. We demonstrate the impact of these improvements on the interpretation of GO term analyses performed on genes differentially expressed in kidney glomeruli affected by diabetic nephropathy. In summary, we have produced a resource that can be utilized in the interpretation of data from small- and large-scale experiments investigating molecular mechanisms of kidney function and development and thereby help towards alleviating renal disease.
基因本体论(GO)提供动态可控词汇表,以帮助描述所有分类群中基因产物的功能生物学属性和亚细胞定位(www.geneontology.org)。在此,我们描述了肾脏生物医学研究团体与GO联盟之间的合作,以提高描述肾脏发育的GO术语的质量和数量。在相关的注释活动中,新的和修订后的术语与参与肾脏发育和功能的基因产物相关联。该项目总共向本体中添加了522个GO术语,并创建了约9600个与肾脏相关的GO术语关联,涉及940个UniProt知识库(UniProtKB)条目,涵盖66个分类群。我们展示了这些改进对在受糖尿病肾病影响的肾小球中差异表达的基因进行GO术语分析解释的影响。总之,我们生成了一种资源,可用于解释来自研究肾脏功能和发育分子机制的小规模和大规模实验的数据,从而有助于缓解肾脏疾病。