Rat Genome Database: a unique resource for rat, human, and mouse quantitative trait locus data

Author:

Nigam Rajni1,Laulederkind Stanley J. F.1,Hayman G. Thomas1,Smith Jennifer R.1,Wang Shur-Jen1,Lowry Timothy F.1,Petri Victoria1,Pons Jeff De1,Tutaj Marek1,Liu Weisong1,Jayaraman Pushkala1,Munzenmaier Diane H.12,Worthey Elizabeth A.13,Dwinell Melinda R.12,Shimoyama Mary14,Jacob Howard J.12

Affiliation:

1. Human and Molecular Genetics Center, Medical College of Wisconsin, Milwaukee, Wisconsin;

2. Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin;

3. Department of Pediatrics, Medical College of Wisconsin, Milwaukee, Wisconsin; and

4. Department of Surgery, Medical College of Wisconsin, Milwaukee, Wisconsin

Abstract

The rat has been widely used as a disease model in a laboratory setting, resulting in an abundance of genetic and phenotype data from a wide variety of studies. These data can be found at the Rat Genome Database (RGD, http://rgd.mcw.edu/ ), which provides a platform for researchers interested in linking genomic variations to phenotypes. Quantitative trait loci (QTLs) form one of the earliest and core datasets, allowing researchers to identify loci harboring genes associated with disease. These QTLs are not only important for those using the rat to identify genes and regions associated with disease, but also for cross-organism analyses of syntenic regions on the mouse and the human genomes to identify potential regions for study in these organisms. Currently, RGD has data on >1,900 rat QTLs that include details about the methods and animals used to determine the respective QTL along with the genomic positions and markers that define the region. RGD also curates human QTLs (>1,900) and houses >4,000 mouse QTLs (imported from Mouse Genome Informatics). Multiple ontologies are used to standardize traits, phenotypes, diseases, and experimental methods to facilitate queries, analyses, and cross-organism comparisons. QTLs are visualized in tools such as GBrowse and GViewer, with additional tools for analysis of gene sets within QTL regions. The QTL data at RGD provide valuable information for the study of mapped phenotypes and identification of candidate genes for disease associations.

Publisher

American Physiological Society

Subject

Genetics,Physiology

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