Improving interpretation of cardiac phenotypes and enhancing discovery with expanded knowledge in the gene ontology
| Autor: | Lovering, R, Roncaglia, P, Howe, D, Laulederkind, S, Khodiyar, V, Berardini, T, Tweedie, S, Foulger, R, Osumi-Sutherland, D, Campbell, N, Huntley, R, Talmud, P, Blake, J, Breckenridge, R, Riley, P, Lambiase, P, Elliott, P, Clapp, L, Tinker, A, Hill, D |
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| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: | |
| Zdroj: | Circulation. Cardiovascular Genetics |
| Popis: | Supplemental Digital Content is available in the text. Background: A systems biology approach to cardiac physiology requires a comprehensive representation of how coordinated processes operate in the heart, as well as the ability to interpret relevant transcriptomic and proteomic experiments. The Gene Ontology (GO) Consortium provides structured, controlled vocabularies of biological terms that can be used to summarize and analyze functional knowledge for gene products. Methods and Results: In this study, we created a computational resource to facilitate genetic studies of cardiac physiology by integrating literature curation with attention to an improved and expanded ontological representation of heart processes in the Gene Ontology. As a result, the Gene Ontology now contains terms that comprehensively describe the roles of proteins in cardiac muscle cell action potential, electrical coupling, and the transmission of the electrical impulse from the sinoatrial node to the ventricles. Evaluating the effectiveness of this approach to inform data analysis demonstrated that Gene Ontology annotations, analyzed within an expanded ontological context of heart processes, can help to identify candidate genes associated with arrhythmic disease risk loci. Conclusions: We determined that a combination of curation and ontology development for heart-specific genes and processes supports the identification and downstream analysis of genes responsible for the spread of the cardiac action potential through the heart. Annotating these genes and processes in a structured format facilitates data analysis and supports effective retrieval of gene-centric information about cardiac defects. |
| Databáze: | OpenAIRE |
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