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In this study, we applied short- and long-read RNA sequencing techniques, as well as PCR analysis to investigate the transcriptome of the porcine endogenous retrovirus (PERV) expressed from cultured porcine kidney cell line PK-15. This analysis has revealed six novel transcripts and eight transcript isoforms, including five length and three splice variants. We were able to establish whether a deletion in a transcript is the result of the splicing of mRNAs or of genomic deletion in one of the PERV clones. Additionally, we re-annotated the formerly identified RNA molecules. Our analysis revealed a higher complexity of PERV transcriptome than it was earlier believed. [ABSTRACT FROM AUTHOR]

Background Poxviruses are large DNA viruses that infect humans and animals. Vaccinia virus (VACV) has been applied as a live vaccine for immunization against smallpox, which was eradicated by 1980 as a result of worldwide vaccination. VACV is the prototype of poxviruses in the investigation of the molecular pathogenesis of the virus. Short-read sequencing methods have revolutionized transcriptomics; however, they are not efficient in distinguishing between the RNA isoforms and transcript overlaps. Long-read sequencing (LRS) is much better suited to solve these problems and also allow direct RNA sequencing. Despite the scientific relevance of VACV, no LRS data have been generated for the viral transcriptome to date. Findings For the deep characterization of the VACV RNA profile, various LRS platforms and library preparation approaches were applied. The raw reads were mapped to the VACV reference genome and also to the host (Chlorocebus sabaeus) genome. In this study, we applied the Pacific Biosciences RSII and Sequel platforms, which altogether resulted in 937,531 mapped reads of inserts (1.42 Gb), while we obtained 2,160,348 aligned reads (1.75 Gb) from the different library preparation methods using the MinION device from Oxford Nanopore Technologies. Conclusions By applying cutting-edge technologies, we were able to generate a large dataset that can serve as a valuable resource for the investigation of the dynamic VACV transcriptome, the virus-host interactions, and RNA base modifications. These data can provide useful information for novel gene annotations in the VACV genome. Our dataset can also be used to analyze the currently available LRS platforms, library preparation methods, and bioinformatics pipelines. [ABSTRACT FROM AUTHOR]