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The role of the mitochondrial ribosome in human disease: searching for mutations in 12S mitochondrial rRNA with high disruptive potential
Mutations of mitochondrial DNA are linked to many human diseases. Despite the identification of a large number of variants in the mitochondrially encoded rRNA (mt-rRNA) genes, the evidence supporting their pathogenicity is, at best, circumstantial. Establishing the pathogenicity of these variations...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3900107/ https://www.ncbi.nlm.nih.gov/pubmed/24092330 http://dx.doi.org/10.1093/hmg/ddt490 |
Sumario: | Mutations of mitochondrial DNA are linked to many human diseases. Despite the identification of a large number of variants in the mitochondrially encoded rRNA (mt-rRNA) genes, the evidence supporting their pathogenicity is, at best, circumstantial. Establishing the pathogenicity of these variations is of major diagnostic importance. Here, we aim to estimate the disruptive effect of mt-rRNA variations on the function of the mitochondrial ribosome. In the absence of direct biochemical methods to study the effect of mt-rRNA variations, we relied on the universal conservation of the rRNA fold to infer their disruptive potential. Our method, named heterologous inferential analysis or HIA, combines conservational information with functional and structural data obtained from heterologous ribosomal sources. Thus, HIA's predictive power is superior to the traditional reliance on simple conservation indexes. By using HIA, we have been able to evaluate the disruptive potential for a subset of uncharacterized 12S mt-rRNA variations. Our analysis revealed the existence of variations in the rRNA component of the human mitoribosome with different degrees of disruptive power. In cases where sufficient information regarding the genetic and pathological manifestation of the mitochondrial phenotype is available, HIA data can be used to predict the pathogenicity of mt-rRNA mutations. In other cases, HIA analysis will allow the prioritization of variants for additional investigation. Eventually, HIA-inspired analysis of potentially pathogenic mt-rRNA variations, in the context of a scoring system specifically designed for these variants, could lead to a powerful diagnostic tool. |
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