Name
Evaluation of Genetic Distance Cutoffs in Rotavirus alphagastroenteritidis Classification
Presenter
Ricardo Gabriel Díaz Alarcón, National University of Misiones
Co-Author(s)
Ricardo Gabriel Díaz Alarcón; National Council for Scientific and Technical Research (CONICET), Argentina.
Karina Salvatierra; Laboratory “MADAR”, National University of Misiones (UNaM), Ruta 12, Km 7 y ½, Posadas CP3300,
Misiones, Argentina.
Emiliano Gómez Quintero; National Council for Scientific and Technical Research (CONICET), Argentina.
Domingo Javier Liotta; National Institute of Tropical Medicine (INMeT) - ANLIS “Dr. Carlos Malbrán”, Puerto Iguazú, Misiones, Argentina.
Viviana Parreño; National Institute of Agricultural Technology (INTA), Argentina.
Samuel Orlando Miño; National Institute of Agricultural Technology (INTA), Argentina.
Abstract Category
Epidemiology, Evolution, and Diversity
Abstract
Rotavirus alphagastroenteritidis (RVA) is a major etiological agent of acute gastroenteritis in human and young mammals and birds worldwide. RVA is a non-enveloped virus with an 11-segment double-stranded RNA genome. In 2008, the Rotavirus Classification Working Group established a standardized genotyping system based on genetic distance thresholds. This study aims to assess the validity of these cutoff values by systematically analyzing genetic variability across all RVA genome segments.
Multiple sequence alignments were performed for all 11 segments, including individual genotype groups with discrepancies. Pairwise genetic distances were calculated to evaluate adherence to the established cutoffs. The dataset comprised over 26,500 RVA strain sequences spanning 299 genotypes. Our analysis revealed that 99.4% of genotypes conformed to the designated thresholds, indicating the robustness of the classification system. Only 0.63% of strains exhibited genetic distances beyond the established cutoffs, suggesting minimal deviations from expected variability.
These findings support the continued applicability of the current RVA classification system, ensuring consistent and accurate genotyping. The results highlight the system’s effectiveness while identifying rare cases that may require further review. This study reinforces the reliability of RVA genotyping criteria, providing a solid framework for epidemiological surveillance and virological research.
Multiple sequence alignments were performed for all 11 segments, including individual genotype groups with discrepancies. Pairwise genetic distances were calculated to evaluate adherence to the established cutoffs. The dataset comprised over 26,500 RVA strain sequences spanning 299 genotypes. Our analysis revealed that 99.4% of genotypes conformed to the designated thresholds, indicating the robustness of the classification system. Only 0.63% of strains exhibited genetic distances beyond the established cutoffs, suggesting minimal deviations from expected variability.
These findings support the continued applicability of the current RVA classification system, ensuring consistent and accurate genotyping. The results highlight the system’s effectiveness while identifying rare cases that may require further review. This study reinforces the reliability of RVA genotyping criteria, providing a solid framework for epidemiological surveillance and virological research.