Exploring human disease using the Rat Genome Database
Open accessAbstract
Rattus norvegicus, the laboratory rat, has been a crucial model for studies of the environmental and genetic factors associated with human diseases for over 150 years. It is the primary model organism for toxicology and pharmacology studies, and has features that make it the model of choice in many complex-disease studies. Since 1999, the Rat Genome Database (RGD; http://rgd.mcw.edu) has been the premier resource for genomic, genetic, phenotype and strain data for the laboratory rat. The primary role of RGD is to curate rat data and validate orthologous relationships with human and mouse genes, and make these data available for incorporation into other major databases such as NCBI, Ensembl and UniProt. RGD also provides official nomenclature for rat genes, quantitative trait loci, strains and genetic markers, as well as unique identifiers. The RGD team adds enormous value to these basic data elements through functional and disease annotations, the analysis and visual presentation of pathways, and the integration of phenotype measurement data for strains used as disease models. Because much of the rat research community focuses on understanding human diseases, RGD provides a number of datasets and software tools that allow users to easily explore and make disease-related connections among these datasets. RGD also provides comprehensive human and mouse data for comparative purposes, illustrating the value of the rat in translational research. This article introduces RGD and its suite of tools and datasets to researchers – within and beyond the rat community – who are particularly interested in leveraging rat-based insights to understand human diseases.
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The rat has potential for geroscience research because its aging physiology is closer to humans than mice, especially for onset of certain age-related conditions, and its larger size permits serial sampling and imaging not feasible in mice.
“However, the rat has tremendous potential for use in geroscience research, owning to its aging physiology being closer to humans compared to mice, especially with respect to onset of certain age-related conditions, as well as its larger size, which permits serial sampling and imaging studies not feasible in the mouse [36–41].”
From Reducing Senescent Cell Burden in Aging and Disease (2020) · cites this paper as [41]
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Self-citation
- Authors
- Shimoyama, M., Laulederkind, S. J. F., De Pons, J., Nigam, R., Smith, J. R., Tutaj, M., Petri, V., Hayman, G. T., Wang, S.-J., Ghiasvand, O., Thota, J., & Dwinell, M. R.
- Affiliations
- Medical College of Wisconsin (US)
- Medical College of Wisconsin, Department of Surgery, Milwaukee, WI 53226, USA
- Corresponding author
- Shimoyama, Mary
- ORCID
- Venue
- Disease Models & Mechanisms
- Publisher
- The Company of Biologists
- Published
- 2016-10-01
- Volume
- 9
- Issue
- 10
- Pages
- 1089-1095
- ISSN
- 1754-8403 (ISSN-L)
- 1754-8411
- PMC
- PMC5087824
- OpenAlex
- W2529573769
- Cited by
- 37
- References
- 22
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 2 · 2023: 1 · 2022: 2 · 2021: 3 · 2020: 4 · 2019: 13 · 2018: 5 · 2017: 1 · 2016: 4
- FWCI
- 3.98
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Disease Models & Mechanisms (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- HighWire Press Open Archive (submittedVersion)
- Funders
- National Heart, Lung, and Blood Institute (R01HL064541)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- Rat Genome Database, laboratory rats, Rattus norvegicus, disease models, gene nomenclature, rat strains, quantitative trait loci, genetic markers, disease annotation, pathway analysis, phenotype data, comparative genomics, human disease
- MeSH terms
- Animals, Disease, Humans, Genome, Databases, Genetic, Rats, Data Mining, Molecular Sequence Annotation, Gene Ontology
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