Department of Medical Biology, Faculty of Medicine, University of Szeged, Somogyi B. u. 4., 6720, Szeged, Hungary.
Department of Genetics, School of Medicine, Stanford University, 300 Pasteur Dr, Stanford, California, USA.
Sci Data. 2020 Jul 9;7(1):223. doi: 10.1038/s41597-020-0558-8.
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.
在这项荟萃分析中，我们重新分析和比较了使用各种短读长和长读长测序技术以及不同文库制备方法的八项研究产生的单纯疱疹病毒 1 转录组数据。我们鉴定了大量新的 mRNA、非编码 RNA 和转录本异构体，并验证了许多先前发表的转录本。在此，我们呈现了迄今为止最完整的 HSV-1 转录组。此外，我们还证明了各种测序技术，包括 cDNA 和直接 RNA 测序方法，都存在错误，通过使用集成方法可以避免这些错误。这项工作提请注意在转录组分析研究中需要使用多种测序方法和荟萃分析来获得可靠的结果。
