Back

Identification of an ambisense kolmiovirus from birds

Kishimoto, M.; Imai, S.; Igarashi, M.; Horie, M.

2025-01-08 microbiology
10.1101/2025.01.08.631871 bioRxiv
Show abstract

Viruses in the family Kolmioviridae (KoVs) are unique among RNA viruses in that they have small, highly self-complementary, circular, negative-sense genomes and are satellite viruses requiring the envelope protein of co-infected helper viruses to form infectious virions. For approximately 40 years, only hepatitis D virus (HDV) had been identified, but recent studies have uncovered novel KoVs in diverse animal species. Serinus canaria-associated deltavirus (scKoV) was recently identified form a single RNA-seq data from canary skin. However, only the partial genome sequence corresponding to the transcript encoding DAg has been identified, leaving questions regarding its full genetic composition and origins. In this study, we examined publicly available RNA-seq data and identified multiple complete genome sequences of scKoV. Our results demonstrated that genetically diverse scKoVs infect multiple bird species with recent inter-order transmission. Additionally, scKoV was detected in various tissues including parenchymal organs, suggesting that scKoV is a genuine avian KoV. Notably, analysis of the genome structure and transcriptional pattern clearly revealed that scKoV transcribes a genomic-sense mRNA encoding a novel gene, in addition to the previously known antigenomic-sense DAg transcript. Furthermore, this newly identified gene appears to express two protein isoforms via alternative splicing. These findings mark the first KoV with an ambisense genome that utilizes alternative splicing, which may represent a strategy to increase gene-coding capacity despite the constraints imposed by its small and self-complementarity genome. Moreover, co-infection with avian bornaviruses was detected in most scKoV-positive RNA-seq datasets, suggesting that avian bornaviruses are candidate helper viruses for scKoV. In conclusion, our study on scKoV provides novel insights into the evolution and diversity of KoVs.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.