Precise genotyping and recombination detection of Enterovirus

Chieh Hua Lin, Yu Bin Wang, Shu Hwa Chen, Chao Agnes Hsiung, Chung Yen Lin

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Enteroviruses (EV) with different genotypes cause diverse infectious diseases in humans and mammals. A correct EV typing result is crucial for effective medical treatment and disease control; however, the emergence of novel viral strains has impaired the performance of available diagnostic tools. Here, we present a web-based tool, named EVIDENCE (EnteroVirus In DEep conception, http://symbiont.iis.sinica.edu.tw/evidence ), for EV genotyping and recombination detection. We introduce the idea of using mixed-ranking scores to evaluate the fitness of prototypes based on relatedness and on the genome regions of interest. Using phylogenetic methods, the most possible genotype is determined based on the closest neighbor among the selected references. To detect possible recombination events, EVIDENCE calculates the sequence distance and phylogenetic relationship among sequences of all sliding windows scanning over the whole genome. Detected recombination events are plotted in an interactive figure for viewing of fine details. In addition, all EV sequences available in GenBank were collected and revised using the latest classification and nomenclature of EV in EVIDENCE. These sequences are built into the database and are retrieved in an indexed catalog, or can be searched for by keywords or by sequence similarity. EVIDENCE is the first web-based tool containing pipelines for genotyping and recombination detection, with updated, built-in, and complete reference sequences to improve sensitivity and specificity. The use of EVIDENCE can accelerate genotype identification, aiding clinical diagnosis and enhancing our understanding of EV evolution.

Original languageEnglish
Article numberS8
JournalBMC Genomics
Volume16
Issue number12
DOIs
Publication statusPublished - Dec 9 2015
Externally publishedYes

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ASJC Scopus subject areas

  • Biotechnology
  • Genetics

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