Rat Genome Database

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DESCRIPTION (provided by applicant): Rat research was revolutionized by the draft genomic sequence. To meet the changing needs, the Rat Genome Database is expanding its focus from genomics to disease and phenotype annotation as well as genome sequence maintenance. As datasets increase in number, size and complexity we must develop web-based tools for their efficient use. The goal of RGD is to serve the community with a single, comprehensive, efficient resource. To meet this goal we propose these specific aims: 1. To Expand the Collection of Rat Genomic Data. RGD leads in annotating and integrating rat genomic data. Annotation will include all known and predicted genes; all SNPs; select haplotypes; and select gene expression and proteomics data. RGD will maintain and distribute the data to the major databases. 2. To Curate the Draft Genomic Sequence. Maintaining the draft sequence is a unique challenge. Collaborating with Baylor University, we will track and annotate sequence modifications between sequence rebuilds. RGD will maintain and improve this resource by identifying regions needing resequencing, ensuring the repair is correct, and passing the data to the major databases. We will create and maintain a reference set of rat genes. 3. To Increase the Biological Content of RGD. The genome is studied for its impact on higher-level physiology. Initially focused on increasing annotation of rat strains, their biological measures, and QTLs across multiple species. We will expand biological content through ontology annotations, capturing data on gene functional variants and pathway annotation, add physiological data to our strain reports, and enable users to compare traits between different strains. 4. To Expand Comparative Analysis Tools. Comparative genomics is a strength of RGD and will expand as functional data increases in human and mouse. As sequence is validated, we will convert comparative maps from RH data based to sequence based. We will use phenotype and disease ontology to compare physiological data between strains and species. Analysis tools utilizing comparative mapping will help fill in sequence and enhance our ability to define gene models. 5. To Provide User Education, Interaction, and Collaboration Programs. Activities promoting RGD in genetic and genomic data storage, analysis, and exploration will continue and be supplemented with online training with a new educational portal utilizing multimedia presentations, an expanded glossary, tutorials, and case studies. A visiting scientist program will support curation, analyses and integration of specialized biological datasets.