Dual platform long-read RNA-sequencing dataset of the human Cytomegalovirus Lytic transcriptome
RNA-sequencing has revolutionized transcriptomics and the way we measure gene expression (Wang et al., 2009). As of today, short-read RNA sequencing is more widely used, and due to its low price and high throughput, is the preferred tool for the quantitative analysis of gene expression. However, the annotation of transcript isoforms is rather difficult using only short-read sequencing data, because the reads are shorter than most transcripts (Steijger et al., 2013). Long-read sequencing, on the other hand, can provide full contig information about transcripts, including exon-connectivity, and its merits in transcriptome profiling are being increasingly acknowledged (Sharon et al., 2013; Abdel-Ghany et al., 2016; Wang et al., 2016; Kuo et al., 2017). Due to the relatively low throughput of current long-read sequencing technologies, they can only characterize smaller transcriptomes in high-depth (Weirather et al., 2017). The Human cytomegalovirus (HCMV) is a ubiquitous betaherpesvirus, which can cause mononucleosis-like symptoms in adults (Cohen and Corey, 1985), and severe life-threatening infections in newborns (Wen et al., 2002). Latent HCMV infection has recently been implicated to affect cancer formation (Dziurzynski et al., 2012; Jin et al., 2014). Examining the transcriptome of the virus can go a long way in helping understand its molecular biology. Short-read RNA sequencing studies have discovered splice junctions and non-coding transcripts (Gatherer et al., 2011) and have shown that the most abundant HCMV transcripts are similarly expressed in different cell types (Cheng et al., 2017). Our long-read RNA sequencing experiments using the Pacific Biosciences (PacBio) RSII platform revealed a great number of transcript isoforms, polycistronic RNAs and transcriptional overlaps (Balázs et al., 2017a).