Discovering the functions of the tens of thousands of genes in the human genome is a required step for understanding human biology and disease. Genetic model organisms, including Zebrafish, play a critical role in this discovery process, because genetic analysis can connect gene sequence and function. Model organism databases, like ZFIN, provide tools required to make this connection. Zebrafish has emerged as a premiere model organism because powerful techniques allow efficient generation and recovery of zebrafish mutations affecting genes that regulate developmental patterning, organogenesis, physiology, and behavior. Recent advances make it easy to study gene function by generating transgenic zebrafish or by knocking down gene function with morpholino antisense oligonucleotides. The functions of many of these genes are conserved among vertebrate groups. Thus, analysis of zebrafish mutations provides insights into gene functions in other vertebrates, including humans. The long term goals for ZFIN are a) to be the community database resource for the laboratory use of zebrafish, b) to develop and support integrated zebrafish genetic, genomic, developmental, and physiological information, c) to maintain the definitive reference data sets of zebrafish research information, d) to link this information extensively to corresponding data in other model organism and human databases, e) to facilitate the use of zebrafish as a model for human biology, and f) to help serve the broad needs of the biomedical research community. This project will continue and expand curation of zebrafish research data, develop expanded support for zebrafish models of human disease, expand and integrate links to other databases, and develop enhanced support for searching, exploring, and mining ZFIN data. This work will provide a powerful means for researchers to associate gene sequence and function, thus facilitating studies of human gene function and disease as well as cross-species analyses of genome organization and evolution.
Zebrafish are widely used to study vertebrate gene function and many zebrafish models of human diseases are being created. ZFIN is the centralized database of zebrafish research information and will provide efficient means to identify gene candidates and animal models of human disease, which may shorten the lengthy path to identification and understanding of the genetic basis of human disease.
|Diehl, Alexander D; Meehan, Terrence F; Bradford, Yvonne M et al. (2016) The Cell Ontology 2016: enhanced content, modularization, and ontology interoperability. J Biomed Semantics 7:44|
|Howe, Douglas G; Bradford, Yvonne M; Eagle, Anne et al. (2016) The Zebrafish Model Organism Database: new support for human disease models, mutation details, gene expression phenotypes and searching. Nucleic Acids Res :|
|Huntley, Rachael P; Sitnikov, Dmitry; Orlic-Milacic, Marija et al. (2016) Guidelines for the functional annotation of microRNAs using the Gene Ontology. RNA 22:667-76|
|Howe, D G; Bradford, Y M; Eagle, A et al. (2016) A scientist's guide for submitting data to ZFIN. Methods Cell Biol 135:451-81|
|Van Slyke, Ceri E; Bradford, Yvonne M; Westerfield, Monte et al. (2014) The zebrafish anatomy and stage ontologies: representing the anatomy and development of Danio rerio. J Biomed Semantics 5:12|
|KÃ¶hler, Sebastian; Doelken, Sandra C; Mungall, Christopher J et al. (2014) The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data. Nucleic Acids Res 42:D966-74|
|Haendel, Melissa A; Balhoff, James P; Bastian, Frederic B et al. (2014) Unification of multi-species vertebrate anatomy ontologies for comparative biology in Uberon. J Biomed Semantics 5:21|
|Midford, Peter E; Dececchi, Thomas Alex; Balhoff, James P et al. (2013) The vertebrate taxonomy ontology: a framework for reasoning across model organism and species phenotypes. J Biomed Semantics 4:34|
|Doelken, Sandra C; KÃ¶hler, Sebastian; Mungall, Christopher J et al. (2013) Phenotypic overlap in the contribution of individual genes to CNV pathogenicity revealed by cross-species computational analysis of single-gene mutations in humans, mice and zebrafish. Dis Model Mech 6:358-72|
|Mabee, By Paula; Balhoff, James P; Dahdul, Wasila M et al. (2012) 500,000 fish phenotypes: The new informatics landscape for evolutionary and developmental biology of the vertebrate skeleton. J Appl Ichthyol 28:300-305|