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KSHV 3.0: A State-of-the-Art Annotation of the Kaposi’s Sarcoma-Associated Herpesvirus Transcriptome Using Cross-Platform Sequencing

Kaposi’s sarcoma-associated herpesvirus (KSHV) is a large, oncogenic DNA virus belonging to the gammaherpesvirus subfamily. KSHV has been extensively studied with various high-throughput RNA-sequencing approaches to map the transcription start and end sites, the splice junctions, and the translation...

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Detalles Bibliográficos
Autores principales: Prazsák, István, Tombácz, Dóra, Fülöp, Ádám, Torma, Gábor, Gulyás, Gábor, Dörmő, Ákos, Kakuk, Balázs, Spires, Lauren McKenzie, Toth, Zsolt, Boldogkői, Zsolt
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10542539/
https://www.ncbi.nlm.nih.gov/pubmed/37790386
http://dx.doi.org/10.1101/2023.09.21.558842
Descripción
Sumario:Kaposi’s sarcoma-associated herpesvirus (KSHV) is a large, oncogenic DNA virus belonging to the gammaherpesvirus subfamily. KSHV has been extensively studied with various high-throughput RNA-sequencing approaches to map the transcription start and end sites, the splice junctions, and the translation initiation sites. Despite these efforts, the comprehensive annotation of the viral transcriptome remains incomplete. In the present study, we generated a long-read sequencing dataset of the lytic and latent KSHV transcriptome using native RNA and direct cDNA sequencing methods. This was supplemented with CAGE sequencing based on a short-read platform. We also utilized datasets from previous publications for our analysis. As a result of this combined approach, we have identified a number of novel viral transcripts and RNA isoforms and have either corroborated or improved the annotation of previously identified viral RNA molecules, thereby notably enhancing our comprehension of the transcriptomic architecture of the KSHV genome. We also evaluated the coding capability of transcripts previously thought to be non-coding, by integrating our data on the viral transcripts with translatomic information from other publications.