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Heterologous Inferential Analysis (HIA) as a Method to Understand the Role of Mitochondrial rRNA Mutations in Pathogenesis

Lookup NU author(s): Dr Joanna Elson, Dr Paul Smith


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Despite the identification of a large number of potentially pathogenic variants in the mitochondrially encoded rRNA (mt-rRNA) genes, we lack direct methods to firmly establish their pathogenicity. In the absence of such methods, we have devised an indirect approach named heterologous inferential analysis or HIA that can be used to make predictions on the disruptive potential of a large subset of mt-rRNA variants. First, due to the high evolutionary conservation of the rRNA fold, comparison of phylogenetically derived secondary structures of the human mt-rRNAs and those from model organisms allows the location of structurally equivalent residues. Second, visualization of the heterologous equivalent residue in high-resolution structures of the ribosome allows a preliminary structural characterization of the residue and its neighboring region. Third, an exhaustive search for biochemical and genetic information on the residue and its surrounding region is performed to understand their degree of involvement in ribosomal function. Additional rounds of visualization in biochemically relevant high-resolution structures will lead to the structural and functional characterization of the residue’s role in ribosomal function and to an assessment of the disruptive potential of mutations at this position. Notably, in the case of certain mitochondrial variants for which sufficient information regarding their genetic and pathological manifestation is available; HIA data alone can be used to predict their pathogenicity. In other cases, HIA will serve to prioritize variants for additional investigation. In the context of a scoring system specifically designed for these variants, HIA could lead to a powerful diagnostic tool.

Publication metadata

Author(s): Elson JL, Smith PM, Vila-Sanjurjo A

Publication type: Article

Publication status: Published

Journal: Methods in Molecular Biology

Year: 2015

Volume: 1264

Pages: 369-383

Print publication date: 06/01/2015

ISSN (print): 1064-3745

Publisher: Springer New York


DOI: 10.1007/978-1-4939-2257-4_32


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