The Rat Genome Database provides a core resource for rat researchers combining genetic, genomic, pathway, phenotype and strain information with a focus on disease. The goal of RGD is to provide investigators with a research platform that facilitates the elucidation of disease mechanisms by implementing standard data formats and ontologies. To meet this goal, we propose three specific aims: 1) To acquire, integrate and functionally annotate emerging genomic elements and variations along with core data to create a comprehensive genome resource. New gene models, sequence and map data and variations such as single nucleotide polymorphisms (SNPs), copy number variants (CNVs), and splice variants will be integrated through collaborations with NCBI and Ensembl and the use of innovative data pipelines. Curators will continue to focus on functional annotation of core data using multiple ontologies. New information including chemical-gene, drug-gene interactions and their impact on biology or disease will be added. Tools will be developed for mining, analysis and visualization of new data types. Educational activities for this aim will focus on new users and new tools for existing users. 2) To create a comprehensive phenome resource including phenotype measurements and strain medical records. We will develop a phenome database and provide individual strain "medical records" to provide easy access to the richness of this information. The phenome resource will include specific educational activities focused on phenotyping protocols, breeding and the use of our new tools and strain resources. 3) To link genotypes (Aim 1) to phenotypes (Aim 2) through QTLs, molecular, cellular and physiological pathways and the disease portals. RGD will continue to curate QTL data and enhance the QTL reports to provide a navigational hub linking genotype and phenotype data. Drug and physiological pathways will be curated in addition to disease related signaling and regulatory pathways and interactive diagrams will be used to link pathways, biological processes, genomic variations and phenotype data. RGD will expand its Disease Portals to serve as integration points for genomic and phenotype data, disease model profiles, and pathway data. Educational activities will focus on tools for comparative studies between rat and human, as well as those which integrate genotype and phenotype data.
The rat has been a primary animal model used to study many complex diseases and physiological processes. The combination of available genomic resources with the biological relevance and wealth of phenotypic data that exists for the rat provides an opportunity to advance the understanding of disease processes and develop new diagnostic, preventative and treatment approaches. However, the large and often disparate data sets are difficult to gain knowledge from. The primary goal of RGD is to reduce the complex data sets, and large volume of literature into a discovery platform that provides support for researchers using the rat as a model organism in which to understand human health and disease through disease-oriented translational research.
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|Hayman, G Thomas; Laulederkind, Stanley J F; Smith, Jennifer R et al. (2016) The Disease Portals, disease-gene annotation and the RGD disease ontology at the Rat Genome Database. Database (Oxford) 2016:|
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|Liu, Weisong; Laulederkind, Stanley J F; Hayman, G Thomas et al. (2015) OntoMate: a text-mining tool aiding curation at the Rat Genome Database. Database (Oxford) 2015:|
|Flister, Michael J; Prokop, Jeremy W; Lazar, Jozef et al. (2015) 2015 Guidelines for Establishing Genetically Modified Rat Models for Cardiovascular Research. J Cardiovasc Transl Res 8:269-77|
|Shimoyama, Mary; De Pons, Jeff; Hayman, G Thomas et al. (2015) The Rat Genome Database 2015: genomic, phenotypic and environmental variations and disease. Nucleic Acids Res 43:D743-50|
|Wang, Shur-Jen; Laulederkind, Stanley J F; Hayman, G Thomas et al. (2015) PhenoMiner: a quantitative phenotype database for the laboratory rat, Rattus norvegicus. Application in hypertension and renal disease. Database (Oxford) 2015:|
|Prokop, Jeremy W; Petri, Victoria; Shimoyama, Mary E et al. (2015) Structural libraries of protein models for multiple species to understand evolution of the renin-angiotensin system. Gen Comp Endocrinol 215:106-16|
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