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Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
Published on: January 16, 2019
New insights into the evolutionary features of viral overlapping genes by discriminant analysis
1Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parco Area Delle Scienze 23/A, I-43124, Parma, Italy.
Abstract:
Overlapping genes originate by a mechanism of overprinting, in which nucleotide substitutions in a pre-existing frame induce the expression of a de novo protein from an alternative frame. In this study, I assembled a dataset of 319 viral overlapping genes, which included 82 overlaps whose expression is experimentally known and the respective 237 homologs. Principal component analysis revealed that overlapping genes have a common pattern of nucleotide and amino acid composition. Discriminant analysis separated overlapping from non-overlapping genes with an accuracy of 97%. When applied to overlapping genes with known genealogy, it separated ancestral from de novo frames with an accuracy close to 100%. This high discriminant power was crucial to computationally design variants of de novo viral proteins known to possess selective anticancer toxicity (apoptin) or protection against neurodegeneration (X protein), as well as to detect two new potential overlapping genes in the genome of the new coronavirus SARS-CoV-2.
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