Rat Genome Database, Human and Molecular Genetics Center, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA.
Database (Oxford). 2013 Jun 21;2013:bat046. doi: 10.1093/database/bat046. Print 2013.
The Rat Genome Database (RGD) is the premier resource for genetic, genomic and phenotype data for the laboratory rat, Rattus norvegicus. In addition to organizing biological data from rats, the RGD team focuses on manual curation of gene-disease associations for rat, human and mouse. In this work, we have analyzed disease-associated strains, quantitative trait loci (QTL) and genes from rats. These disease objects form the basis for seven disease portals. Among disease portals, the cardiovascular disease and obesity/metabolic syndrome portals have the highest number of rat strains and QTL. These two portals share 398 rat QTL, and these shared QTL are highly concentrated on rat chromosomes 1 and 2. For disease-associated genes, we performed gene ontology (GO) enrichment analysis across portals using RatMine enrichment widgets. Fifteen GO terms, five from each GO aspect, were selected to profile enrichment patterns of each portal. Of the selected biological process (BP) terms, 'regulation of programmed cell death' was the top enriched term across all disease portals except in the obesity/metabolic syndrome portal where 'lipid metabolic process' was the most enriched term. 'Cytosol' and 'nucleus' were common cellular component (CC) annotations for disease genes, but only the cancer portal genes were highly enriched with 'nucleus' annotations. Similar enrichment patterns were observed in a parallel analysis using the DAVID functional annotation tool. The relationship between the preselected 15 GO terms and disease terms was examined reciprocally by retrieving rat genes annotated with these preselected terms. The individual GO term-annotated gene list showed enrichment in physiologically related diseases. For example, the 'regulation of blood pressure' genes were enriched with cardiovascular disease annotations, and the 'lipid metabolic process' genes with obesity annotations. Furthermore, we were able to enhance enrichment of neurological diseases by combining 'G-protein coupled receptor binding' annotated genes with 'protein kinase binding' annotated genes. Database URL: http://rgd.mcw.edu
大鼠基因组数据库（RGD）是用于实验室大鼠（Rattus norvegicus）的遗传、基因组和表型数据的首要资源。除了组织大鼠的生物数据外，RGD 团队还专注于大鼠、人类和小鼠基因-疾病关联的人工注释。在这项工作中，我们分析了与疾病相关的大鼠品系、数量性状基因座（QTL）和基因。这些疾病对象构成了七个疾病门户的基础。在疾病门户中，心血管疾病和肥胖/代谢综合征门户拥有最多的大鼠品系和 QTL。这两个门户共享 398 个大鼠 QTL，这些共享的 QTL 高度集中在大鼠染色体 1 和 2 上。对于与疾病相关的基因，我们使用 RatMine 富集小部件在门户之间进行了基因本体（GO）富集分析。选择了 15 个 GO 术语，每个 GO 方面有 5 个，以分析每个门户的富集模式。在所选择的生物学过程（BP）术语中，“程序性细胞死亡的调节”是除肥胖/代谢综合征门户外所有疾病门户中最富集的术语，在肥胖/代谢综合征门户中，“脂质代谢过程”是最富集的术语。“细胞质”和“细胞核”是疾病基因的常见细胞成分（CC）注释，但只有癌症门户基因高度富集了“细胞核”注释。使用 DAVID 功能注释工具进行的平行分析中观察到了类似的富集模式。通过检索注释了这些预选术语的大鼠基因，反过来检查了预选的 15 个 GO 术语与疾病术语之间的关系。个别 GO 术语注释基因列表显示与生理相关疾病的富集。例如，“血压调节”基因与心血管疾病注释富集，“脂质代谢过程”基因与肥胖注释富集。此外，通过将注释有“G 蛋白偶联受体结合”的基因与注释有“蛋白激酶结合”的基因相结合，我们能够增强神经系统疾病的富集。数据库网址：http://rgd.mcw.edu
