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GOing Forward With the Cardiac Conduction System Using Gene Ontology.
Chloe Li, Kan Yan; Cook, Andrew C; Lovering, Ruth C.
Afiliación
  • Chloe Li KY; Department of Preclinical and Fundamental Science, Institute of Cardiovascular Science, Functional Gene Annotation, University College London, London, United Kingdom.
  • Cook AC; Department of Children's Cardiovascular Disease, Centre for Morphology and Structural Heart Disease, Institute of Cardiovascular Science, University College London, London, United Kingdom.
  • Lovering RC; Department of Children's Cardiovascular Disease, Centre for Morphology and Structural Heart Disease, Institute of Cardiovascular Science, University College London, London, United Kingdom.
Front Genet ; 13: 802393, 2022.
Article en En | MEDLINE | ID: mdl-35309148
ABSTRACT
The cardiac conduction system (CCS) comprises critical components responsible for the initiation, propagation, and coordination of the action potential. Aberrant CCS development can cause conduction abnormalities, including sick sinus syndrome, accessory pathways, and atrioventricular and bundle branch blocks. Gene Ontology (GO; http//geneontology.org/) is an invaluable global bioinformatics resource which provides structured, computable knowledge describing the functions of gene products. Many gene products are known to be involved in CCS development; however, this information is not comprehensively captured by GO. To address the needs of the heart development research community, this study aimed to describe the specific roles of proteins reported in the literature to be involved with CCS development and/or function. 14 proteins were prioritized for GO annotation which led to the curation of 15 peer-reviewed primary experimental articles using carefully selected GO terms. 152 descriptive GO annotations, including those describing sinoatrial node and atrioventricular node development were created and submitted to the GO Consortium database. A functional enrichment analysis of 35 key CCS development proteins confirmed that this work has improved the in-silico interpretation of this CCS dataset. This work may improve future investigations of the CCS with application of high-throughput methods such as genome-wide association studies analysis, proteomics, and transcriptomics.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Genet Año: 2022 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Genet Año: 2022 Tipo del documento: Article País de afiliación: Reino Unido