Toward a mtDNA locus-specific mutation database using the LOVD platform

TitreToward a mtDNA locus-specific mutation database using the LOVD platform
Type de publicationArticle de revue
AuteurElson, J. L, Sweeney, M. G, Procaccio, Vincent , Yarham, J. W, Salas, A., Kong, Q. P, van der Westhuizen, F. H, Pitceathly, R. D, Thorburn, D. R, Lott, M. T, Wallace, D. C, Taylor, Robert W., McFarland, R.
TypeArticle scientifique dans une revue à comité de lecture
Pagination1352 - 8
Titre de la revueHuman Mutation
Mots-clésComputational Biology/methods, Databases, Nucleic Acid, DNA Mutational Analysis/methods/standards, DNA, Mitochondrial/genetics, Genetic Loci, Genome, Human, Genotype, High-Throughput Nucleotide Sequencing, Humans, Information Storage and Retrieval, internet, Mitochondrial Diseases/diagnosis/genetics, Mutation, Oxidative Phosphorylation, Phenotype, Software
Résumé en anglais

The Human Variome Project (HVP) is a global effort to collect and curate all human genetic variation affecting health. Mutations of mitochondrial DNA (mtDNA) are an important cause of neurogenetic disease in humans; however, identification of the pathogenic mutations responsible can be problematic. In this article, we provide explanations as to why and suggest how such difficulties might be overcome. We put forward a case in support of a new Locus Specific Mutation Database (LSDB) implemented using the Leiden Open-source Variation Database (LOVD) system that will not only list primary mutations, but also present the evidence supporting their role in disease. Critically, we feel that this new database should have the capacity to store information on the observed phenotypes alongside the genetic variation, thereby facilitating our understanding of the complex and variable presentation of mtDNA disease. LOVD supports fast queries of both seen and hidden data and allows storage of sequence variants from high-throughput sequence analysis. The LOVD platform will allow construction of a secure mtDNA database; one that can fully utilize currently available data, as well as that being generated by high-throughput sequencing, to link genotype with phenotype enhancing our understanding of mitochondrial disease, with a view to providing better prognostic information.

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Titre abrégéHum Mutat