The Vertebrate Trait Ontology: a controlled vocabulary for the annotation of trait data across species

详细信息    查看全文

• 作者：Carissa A Park (1)
  Susan M Bello (2)
  Cynthia L Smith (2)
  Zhi-Liang Hu (1)
  Diane H Munzenmaier (3) (4)
  Rajni Nigam (3)
  Jennifer R Smith (3)
  Mary Shimoyama (3) (5)
  Janan T Eppig (2)
  James M Reecy (1)
  
• 关键词：Quantitative trait loci ; Gene association ; Trait ontology
• 刊名：Journal of Biomedical Semantics
• 出版年：2013
• 出版时间：December 2013
• 年：2013
• 卷：4
• 期：1
• 全文大小：618 KB
• 参考文献：1. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, / et al.: Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. / Nat Genet 2000,25(1):25鈥?9. CrossRef
  2. Smith CL, Goldsmith CA, Eppig JT: The Mammalian Phenotype Ontology as a tool for annotating, analyzing and comparing phenotypic information. / Genome Biol 2005,6(1):R7. CrossRef
  3. Robinson PN, K枚hler S, Bauer S, Seelow D, Horn D, Mundlos S: The Human Phenotype Ontology: a tool for annotating and analyzing human hereditary disease. / Am J Hum Genet 2008,83(5):610鈥?15. CrossRef
  4. Dahdul WM, Lundberg JG, Midford PE, Balhoff JP, Lapp H, Vision TJ, Haendel MA, Westerfield M, Mabee PM: The teleost anatomy ontology: anatomical representation for the genomics age. / Syst Biol 2010,59(4):369鈥?83. CrossRef
  5. Haendel M, Neuhaus F, Osumi-Sutherland D, Mabee P, Mejino JJ, Mungall C, Smith B: CARO - The Common Anatomy Reference Ontology. In / Anatomy Ontologies for Bioinformatics: Principles and Practice. Edited by: Burger A, Davidson D, Baldock R. London: Springer; 2008:327鈥?50. CrossRef
  6. Washington NL, Haendel MA, Mungall CJ, Ashburner M, Westerfield M, Lewis SE: Linking human diseases to animal models using ontology-based phenotype annotation. / PLoS Biol 2009,7(11):e1000247. CrossRef
  7. Rosse C, Mejino JL: A reference ontology for biomedical informatics: the Foundational Model of Anatomy. / J Biomed Inform 2003,36(6):478鈥?00. CrossRef
  8. Bard J, Rhee SY, Ashburner M: An ontology for cell types. / Genome Biol 2005,6(2):R21. CrossRef
  9. Degtyarenko K, de Matos P, Ennis M, Hastings J, Zbinden M, McNaught A, Alc谩ntara R, Darsow M, Guedj M, Ashburner M: ChEBI: a database and ontology for chemical entities of biological interest. / Nucleic Acids Res 2008,36(Database issue):D344鈥?50.
  10. Natale DA, Arighi CN, Barker WC, Blake J, Chang TC, Hu Z, Liu H, Smith B, Wu CH: Framework for a protein ontology. / BMC Bioinformatics 2007,9(8 Suppl):S1. CrossRef
  11. Rubin DL, Lewis SE, Mungall CJ, Misra S, Westerfield M, Ashburner M, Sim I, Chute CG, Solbrig H, Storey MA, / et al.: National Center for Biomedical Ontology: advancing biomedicine through structured organization of scientific knowledge. / OMICS 2006,10(2):185鈥?98. CrossRef
  12. Noy NF, Shah NH, Whetzel PL, Dai B, Dorf M, Griffith N, Jonquet C, Rubin DL, Storey MA, Chute CG, / et al.: BioPortal: ontologies and integrated data resources at the click of a mouse. / Nucleic Acids Res 2009,37(Web Server issue):W170鈥?73. CrossRef
  13. / Rat Genome Database. http://rgd.mcw.edu/
  14. / Mouse Genome Informatics. http://www.informatics.jax.org/
  15. Hu ZL, Fritz ER, Reecy JM: AnimalQTLdb: a livestock QTL database tool set for positional QTL information mining and beyond. / Nucleic Acids Res 2007,35(Database issue):D604鈥?09. CrossRef
  16. Gkoutos GV, Green EC, Mallon AM, Hancock JM, Davidson D: Using ontologies to describe mouse phenotypes. / Genome Biol 2005,6(1):R8. CrossRef
  17. Harris MA, Lock A, B盲hler J, Oliver SG, Wood V: FYPO: the fission yeast phenotype ontology. / Bioinformatics 2013,29(13):1671鈥?678. CrossRef
  18. Sprague J, Bayraktaroglu L, Bradford Y, Conlin T, Dunn N, Fashena D, Frazer K, Haendel M, Howe DG, Knight J, / et al.: The Zebrafish Information Network: the zebrafish model organism database provides expanded support for genotypes and phenotypes. / Nucleic Acids Res 2008,36(Database issue):D768鈥?72.
  19. Smith CL, Eppig JT: The mammalian phenotype ontology: enabling robust annotation and comparative analysis. / Wiley Interdiscip Rev Syst Biol Med 2009,1(3):390鈥?99. CrossRef
  20. Osborne JD, Flatow J, Holko M, Lin SM, Kibbe WA, Zhu LJ, Danila MI, Feng G, Chisholm RL: Annotating the human genome with Disease Ontology. / BMC Genomics 2009,1(10 Suppl):S6. CrossRef
  21. / SNOMED Clinical Terms. http://www.ihtsdo.org/snomed-ct
  22. / International Classification of Diseases. [http://bioportal.bioontology.org/ontologies/1101]
  23. Shimoyama M, Nigam R, McIntosh LS, Nagarajan R, Rice T, Rao DC, Dwinell MR: Three ontologies to define phenotype measurement data. / Front Genet 2012, 3:87. CrossRef
  24. Bogue MA, Grubb SC, Maddatu TP, Bult CJ: Mouse Phenome Database (MPD). / Nucleic Acids Res 2007,35(Database issue):D643鈥?49. CrossRef
  25. / Mouse Phenome Database. [http://phenome.jax.org/]
  26. Bradford Y, Conlin T, Dunn N, Fashena D, Frazer K, Howe DG, Knight J, Mani P, Martin R, Moxon SA, / et al.: ZFIN: enhancements and updates to the Zebrafish Model Organism Database. / Nucleic Acids Res 2011,39(Database issue):D822鈥?29. CrossRef
  27. Day-Richter J, Harris MA, Haendel M, Lewis S, Group GOO-EW: OBO-Edit鈥揳n ontology editor for biologists. / Bioinformatics 2007,23(16):2198鈥?200. CrossRef
  28. Smith B, Ceusters W, Klagges B, K枚hler J, Kumar A, Lomax J, Mungall C, Neuhaus F, Rector AL, Rosse C: Relations in biomedical ontologies. / Genome Biol 2005,6(5):R46. CrossRef
  29. Washington N, Lewis S: Ontologies: Scientific Data Sharing Made Easy. / Nature Education 2008.,1(3):
  30. Jensen LJ, Bork P: Ontologies in quantitative biology: a basis for comparison, integration, and discovery. / PLoS Biol 2010,8(5):e1000374. CrossRef
  31. / OBO Foundry Principles. [http://obofoundry.org/wiki/index.php/OBO_Foundry_Principles]
  32. Smith B, Ashburner M, Rosse C, Bard J, Bug W, Ceusters W, Goldberg LJ, Eilbeck K, Ireland A, Mungall CJ, / et al.: The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. / Nat Biotechnol 2007,25(11):1251鈥?255. CrossRef
  33. / Product Trait Ontology. [http://www.animalgenome.org/cgi-bin/amido/browse.cgi]
  34. / Phenominer Database. [http://rgd.mcw.edu/phenotypes/]
  35. Davis AP, Wiegers TC, Rosenstein MC, Mattingly CJ: MEDIC: a practical disease vocabulary used at the Comparative Toxicogenomics Database. / Database (Oxford) 2012. doi:10.1093/database/bar065.
  36. / Pathway Ontology. [http://bioportal.bioontology.org/ontologies/1035]
  37. Bard JB, Rhee SY: Ontologies in biology: design, applications and future challenges. / Nat Rev Genet 2004,5(3):213鈥?22. CrossRef
  38. Stein LD: Integrating biological databases. / Nat Rev Genet 2003,4(5):337鈥?45. CrossRef
  
• 作者单位：Carissa A Park (1)
  Susan M Bello (2)
  Cynthia L Smith (2)
  Zhi-Liang Hu (1)
  Diane H Munzenmaier (3) (4)
  Rajni Nigam (3)
  Jennifer R Smith (3)
  Mary Shimoyama (3) (5)
  Janan T Eppig (2)
  James M Reecy (1)
  
  1. Department of Animal Science, Iowa State University, Ames, IA, USA
  2. Mouse Genome Informatics, The Jackson Laboratory, Bar Harbor, ME, USA
  3. Human and Molecular Genetics Center, Medical College of Wisconsin, Milwaukee, WI, USA
  4. Department of Physiology, Medical College of Wisconsin, Milwaukee, WI, USA
  5. Department of Surgery, Medical College of Wisconsin, Milwaukee, WI, USA
  
• ISSN：2041-1480

文摘

Background The use of ontologies to standardize biological data and facilitate comparisons among datasets has steadily grown as the complexity and amount of available data have increased. Despite the numerous ontologies available, one area currently lacking a robust ontology is the description of vertebrate traits. A trait is defined as any measurable or observable characteristic pertaining to an organism or any of its substructures. While there are several ontologies to describe entities and processes in phenotypes, diseases, and clinical measurements, one has not been developed for vertebrate traits; the Vertebrate Trait Ontology (VT) was created to fill this void. Description Significant inconsistencies in trait nomenclature exist in the literature, and additional difficulties arise when trait data are compared across species. The VT is a unified trait vocabulary created to aid in the transfer of data within and between species and to facilitate investigation of the genetic basis of traits. Trait information provides a valuable link between the measurements that are used to assess the trait, the phenotypes related to the traits, and the diseases associated with one or more phenotypes. Because multiple clinical and morphological measurements are often used to assess a single trait, and a single measurement can be used to assess multiple physiological processes, providing investigators with standardized annotations for trait data will allow them to investigate connections among these data types. Conclusions The annotation of genomic data with ontology terms provides unique opportunities for data mining and analysis. Links between data in disparate databases can be identified and explored, a strategy that is particularly useful for cross-species comparisons or in situations involving inconsistent terminology. The VT provides a common basis for the description of traits in multiple vertebrate species. It is being used in the Rat Genome Database and Animal QTL Database for annotation of QTL data for rat, cattle, chicken, swine, sheep, and rainbow trout, and in the Mouse Phenome Database to annotate strain characterization data. In these databases, data are also cross-referenced to applicable terms from other ontologies, providing additional avenues for data mining and analysis. The ontology is available at http://bioportal.bioontology.org/ontologies/50138.