Accurate quantification of overlapping herpesvirus transcripts from RNA-seq data

Herpesviruses employ extensive bidirectional transcription of overlapping genes to overcome length constraints on their gene product repertoire. As a consequence, many lytic transcripts cannot be measured individually by RT-qPCR or conventional RNA-seq analysis. Bruce et al. (Pathogens 2017, 6, 11; doi:10.3390/pathogens6010011) proposed an approximation method using Unique CoDing Sequences (UCDS) to estimate lytic gene abundance from KSHV RNA-seq data. Although UCDS has been widely employed, its accuracy, to our knowledge, has never been rigorously validated for any herpesvirus. In this study, we use CAGE-seq as a gold-standard to determine the accuracy of UCDS for estimating EBV lytic gene expression levels from RNA-seq data. We also introduce the Unique TranScript (UTS) method that, like UCDS, estimates transcript abundance from changes in mean RNA-seq read-depth. UTS is distinguished by its use of empirically determined 5’ and 3’ transcript ends, rather than coding sequence annotations. Compared to conventional read assignment, both UCDS and UTS improved quantitation accuracy of overlapping genes, with UTS giving the most accurate results. The UTS method discards fewer reads and may be advantageous for experiments with less sequencing depth. UTS is compatible with any aligner and, unlike isoform-aware alignment methods, can be implemented on a laptop computer. Our findings demonstrate that accuracy achieved by complex and expensive techniques such as CAGE-seq can be approximated using conventional short-read RNA-seq data when read assignment methods address transcript overlap. Although our study focuses on EBV transcription, the UTS method should be applicable across all herpesviruses and other genomes with extensively overlapping transcriptomes. IMPORTANCE Many viruses employ extensively overlapping transcript structures. This complexity makes it difficult to quantify gene expression using conventional methods including RNA-seq. Although high-throughput techniques that overcome these limitations exist, they are complex, expensive, and scarce in herpesvirus literature relative to short-read RNA-seq. Here, using Epstein-Barr virus (EBV) as a model, we demonstrate that conventional RNA-seq analysis methods fail to accurately quantify abundance of many overlapping transcripts. We further show that the previously described Unique CoDing Sequence (UCDS) and our Unique TranScript (UTS) methods greatly improve the accuracy of EBV lytic gene measurements obtained from RNA-seq data. The UTS method has the advantages of discarding fewer reads and being implementable on a laptop computer. Although this study focuses on EBV, the UCDS and UTS methods should be applicable across herpesviruses and for other viruses that make extensive use of overlapping transcription.