Identification of herpesvirus transcripts from genomic regions around the replication origins.

Long-read sequencing (LRS) techniques enable the identification of full-length RNA molecules in a single run eliminating the need for additional assembly steps. LRS research has exposed unanticipated transcriptomic complexity in various organisms, including viruses. Herpesviruses are known to produce a range of transcripts, either close to or overlapping replication origins (Oris) and neighboring genes related to transcription or replication, which possess confirmed or potential regulatory roles. In our research, we employed both new and previously published LRS and short-read sequencing datasets to uncover additional Ori-proximal transcripts in nine herpesviruses from all three subfamilies (alpha, beta and gamma). We discovered novel long non-coding RNAs, as well as splice and length isoforms of mRNAs. Moreover, our analysis uncovered an intricate network of transcriptional overlaps within the examined genomic regions. We demonstrated that herpesviruses display distinct patterns of transcriptional overlaps in the vicinity of or at the Oris. Our findings suggest the existence of a 'super regulatory center' in the genome of alphaherpesviruses that governs the initiation of both DNA replication and global transcription through multilayered interactions among the molecular machineries.

In-depth Temporal Transcriptome Profiling of Monkeypox and Host Cells using Nanopore Sequencing.

The recent human Monkeypox outbreak underlined the importance of studying basic biology of orthopoxviruses. However, the transcriptome of its causative agent has not been investigated before neither with short-, nor with long-read sequencing approaches. This Oxford Nanopore long-read RNA-Sequencing dataset fills this gap. It will enable the in-depth characterization of the transcriptomic architecture of the monkeypox virus, and may even make possible to annotate novel host transcripts. Moreover, our direct cDNA and native RNA sequencing reads will allow the estimation of gene expression changes of both the virus and the host cells during the infection. Overall, our study will lead to a deeper understanding of the alterations caused by the viral infection on a transcriptome level.

High temporal resolution Nanopore sequencing dataset of SARS-CoV-2 and host cell RNAs.

BACKGROUND: Recent studies have disclosed the genome, transcriptome, and epigenetic compositions of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the effect of viral infection on gene expression of the host cells. It has been demonstrated that, besides the major canonical transcripts, the viral genome also codes for noncanonical RNA molecules. While the structural characterizations have revealed a detailed transcriptomic architecture of the virus, the kinetic studies provided poor and often misleading results on the dynamics of both the viral and host transcripts due to the low temporal resolution of the infection event and the low virus/cell ratio (multiplicity of infection [MOI] = 0.1) applied for the infection. It has never been tested whether the alteration in the host gene expressions is caused by aging of the cells or by the viral infection. FINDINGS: In this study, we used Oxford Nanopore's direct cDNA and direct RNA sequencing methods for the generation of a high-coverage, high temporal resolution transcriptomic dataset of SARS-CoV-2 and of the primate host cells, using a high infection titer (MOI = 5). Sixteen sampling time points ranging from 1 to 96 hours with a varying time resolution and 3 biological replicates were used in the experiment. In addition, for each infected sample, corresponding noninfected samples were employed. The raw reads were mapped to the viral and to the host reference genomes, resulting in 49,661,499 mapped reads (54,62 Gbs). The genome of the viral isolate was also sequenced and phylogenetically classified. CONCLUSIONS: This dataset can serve as a valuable resource for profiling the SARS-CoV-2 transcriptome dynamics, the virus-host interactions, and the RNA base modifications. Comparison of expression profiles of the host gene in the virally infected and in noninfected cells at different time points allows making a distinction between the effect of the aging of cells in culture and the viral infection. These data can provide useful information for potential novel gene annotations and can also be used for studying the currently available bioinformatics pipelines.