Abstract
In this meta-analysis, we re-analysed and compared herpes simplex virus type 1 transcriptomic data generated by eight studies using various short- and long-read sequencing techniques and different library preparation methods. We identified a large number of novel mRNAs, non-coding RNAs and transcript isoforms, and validated many previously published transcripts. Here, we present the most complete HSV-1 transcriptome to date. Furthermore, we also demonstrate that various sequencing techniques, including both cDNA and direct RNA sequencing approaches, are error-prone, which can be circumvented by using integrated approaches. This work draws attention to the need for using multiple sequencing approaches and meta-analyses in transcriptome profiling studies to obtain reliable results.
Highlights
Second-generation short-read sequencing (SRS) technology -launched in the mid-2000s, has revolutionized both genomic and transcriptomic research because of its ability to sequence millions of nucleic acid fragments simultaneously at a relatively low expenditure per base
We employed an integrated approach based on the meta-analysis of the Herpes simplex virus type 1 (HSV-1) transcriptome data published by Depledge and colleagues[19], Tang et al[20], Rutkowski et al[21], Wishnant et al[22,23], Pheasant et al[24] and our laboratory (Tombácz and colleagues using Pacific Biosciences (PacBio) RSII25, as well as Boldogkői et al.[26], and Tombácz et al.[27] using PacBio Sequel, Oxford Nanopore Technologies (ONT) Direct RNA (dRNA)-Seq and cDNA sequencing with multiple library preparation methods; Fig. 1, Supplementary Table 1)
We identified a number of novel RNA molecules and transcript isoforms, including intron and length variants
Summary
Second-generation short-read sequencing (SRS) technology -launched in the mid-2000s-, has revolutionized both genomic and transcriptomic research because of its ability to sequence millions of nucleic acid fragments simultaneously at a relatively low expenditure per base. LRS can overcome several shortcomings of SRS in transcriptome analysis mainly based on the ability of LRS techniques to read full-length RNA molecules. The low throughput of dRNA-Seq makes both transcript identification and the annotation of nucleic acid sequences at base-pair resolution difficult, which is especially critical in species with large genomes. LRS techniques can be used in analyses that are challenging for SRS approaches, such as the detection of multi-spliced transcripts, parallel transcriptional overlaps, low-abundance transcripts, very long RNA molecules and embedded transcripts, including 5′-truncated ORF-containing mRNAs and non-coding transcripts. A meta-analysis including multiplatform approaches, such as various LRS and SRS techniques, as well as different auxiliary methods, such as cap selection, and 5′- and 3′-ends mapping can circumvent the aforementioned problems, especially if different
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