Characterization of Bundaberg Bee Virus 4 Genome Identified in Hawaii

James Doherty, Vedbar Khadka, Beatrice Kondo and Jun Panee
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James Doherty: University of Hawaii at Manoa, USA
Vedbar Khadka: University of Hawaii, USA
Beatrice Kondo: University of Maryland, USA
Jun Panee: University of Hawaii at Manoa, USA

European Journal of Biology and Biotechnology, 2023, vol. 4, issue 3, 23-28

Abstract: To identify genetic markers of different cultivars of Stevia rebaudiana (stevia), leaf samples from twenty-three genetically unique stevia plants were subjected to RNA sequencing. Unexpectedly, transcriptome annotation revealed a ‘viral polyprotein’ contig, which was identified as the Bundaberg Bee Virus 4 (BBV4), a virus that has not been found in Hawaii before. BBV4 expression was found in twelve samples, and the expression levels ranged from 0.08-339.18 transcripts per million (TPM). A ‘BBV4-Hawaii’ consensus sequence was generated from 227,427 reads and shares 99.7% identity with the BBV4 reference sample from Australia. A phylogenetic tree estimation constructed using three viral domains placed BBV4 in a monophyletic clade with other members of Iflaviridae, supporting an Iflaviridae classification. A BBV4 intergenic region (IGR) was found to contain a ‘slippery sequence’ within a region that is predicted to contain the unique structure required for Programmed Ribosomal Shifting (PRS). A homological comparison of the BBV4 IGR to two other Picornavirales that utilize alternative translation revealed an area of overlap in the analogous regions. These results suggest that BBV4 may utilize alternative translation and that its IGR is involved in the process. This study also demonstrates the utility of repurposing large Next Generation Sequence (NGS) datasets with sufficiently deep coverage for viral genome identification, quantification, and characterization. The results herein represent the first full capture of the BBV4 genomic sequence and the second reported observation of the virus worldwide.

Keywords: alternative translation; data mining; RNA virus; slippery sequence (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:epw:ejbio0:v:4:y:2023:i:3:id:17461

DOI: 10.24018/ejbio.2023.4.3.461

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