Multiple Long-Read Sequencing Survey of Herpes Simplex Virus Dynamic Transcriptome

Abstract

Long-read sequencing (LRS) has become increasingly important in RNA research due to its strength in resolving complex transcriptomic architectures. In this regard, currently two LRS platforms have demonstrated adequate performance: the Single Molecule Real-Time Sequencing by Pacific Biosciences (PacBio) and the nanopore sequencing by Oxford Nanopore Technologies (ONT). Even though these techniques produce lower coverage and are more error prone than short-read sequencing, they continue to be more successful in identifying polycistronic RNAs, transcript isoforms including splice and transcript end variants, as well as transcript overlaps. Recent reports have successfully applied LRS for the investigation of the transcriptome of viruses belonging to various families. These studies have substantially increased the number of previously known viral RNA molecules. In this work, we used the Sequel and MinION technique from PacBio and ONT, respectively, to characterize the lytic transcriptome of the herpes simplex virus type 1 (HSV-1). In most samples, we analyzed the poly(A) fraction of the transcriptome, but we also performed random oligonucleotide-based sequencing. Besides cDNA sequencing, we also carried out native RNA sequencing. Our investigations identified more than 2,300 previously undetected transcripts, including coding, and non-coding RNAs, multi-splice transcripts, as well as polycistronic and complex transcripts. Furthermore, we found previously unsubstantiated transcriptional start sites, polyadenylation sites, and splice sites. A large number of novel transcriptional overlaps were also detected. Random-primed sequencing revealed that each convergent gene pair produces non-polyadenylated read-through RNAs overlapping the partner genes. Furthermore, we identified novel replication-associated transcripts overlapping the HSV-1 replication origins, and novel LAT variants with very long 5’ regions, which are co-terminal with the LAT-0.7kb transcript. Overall, our results demonstrated that the HSV-1 transcripts form an extremely complex pattern of overlaps, and that entire viral genome is transcriptionally active. In most viral genes, if not in all, both DNA strands are expressed.

Demand for Multiplatform and Meta-analytic Approaches in Transcriptome Profiling

“…In this study, we employed an integrated approach based on the meta-analysis of the HSV-1 transcriptome data published by Depledge and colleagues (using ONT dRNA-Seq and Illumina RNA-Seq) 7 10 , and our laboratory (Tombácz and colleagues using PacBio RSII 11 , as well as Boldogkői et al 12 and Tombácz et al 13 using PacBio Sequel, ONT dRNA-Seq and cDNA sequencing with multiple library preparation methods; Supplementary Table 1). This analysis led to the discovery of novel transcripts, especially of novel multigenic transcripts ( Supplementary Figure 1), and splice sites (Figure 1, Supplementary Figure 2).…”

“…The LoRTIA tool was used to annotate introns and TSSs, and TESs from the LRS data, whereas we used the STAR software was used to detect introns from the SRS samples. The previously published introns (Tang et al 8 , Wishnant et al 10 , and Tombácz et al 11,13 ) were compared with each other, reanalyzed, and validated by using the datasets from all of the aforementioned publications.…”

“…The datasets generated by Depledge et al 7 and five other datasets (Tombácz et al 11,13 ; Tang et al 8 ; Rutkowski et al 9 , and Whisnant et al 10 ) were reanalyzed in order to define the complete HSV transcriptome.…”

“…The datasets used in this work were obtained from the original publications: Depledge et al, 7 , Whisnant et al 10 , Tang et al 8 , Rutkowski et al 9 , and from Tombácz et al 11,13 . All data generated in this study are included in Supplementary Table 1.…”

“…All data generated in this study are included in Supplementary Table 1. The data of introns plotted in this study were obtained from Tang et al 8 , Rutkowski et al 9 , and from Tombácz et al 11,13 . The codes for the LoRTIA (the toolkit developed by our laboratory) analysis are available at: https://github.com/zsoltbalazs/LoRTIA.…”