HeliyonMolecular BiologyPeer-reviewed journal article
Viral and host small RNA transcriptome analysis of SARS-CoV-1 and SARS-CoV-2-infected human cells reveals novel viral short RNAs.
Tom A. P. DriedonksiD, Lyle H. Nyberg, Abigail R. ConteiD, Zexu Ma, Andrew S PekosziD, Eduard A. DubaniD, Alexander TonevitskyiD, Holger SültmanniD, Andrey A. TurchinovichiD, Kenneth Whitaker WitweriD
Abstract
RNA viruses have been shown to express various short RNAs, some of which have regulatory roles during replication, transcription, and translation of viral genomes. However, short viral RNAs (svRNAs) generated by SARS-CoV-1 and SARS-CoV-2 remained largely unexplored, mainly due limitations of the widely used library preparation methods for small RNA deep sequencing and corresponding data processing. By analyzing publicly available small RNA-seq datasets, we observed that human cells infected by SARS-CoV-1 or SARS-CoV-2 produce multiple short viral RNAs (svRNAs), ranging in size from 15 to 26 nt and deriving predominantly from (+) RNA strands. In addition, we verified the presence of the five most abundant SARS-CoV-2 svRNAs in SARS-CoV-2-infected human lung adenocarcinoma cells by qPCR. Interestingly, the copy number of the observed SARS-CoV-2 svRNAs dramatically exceeded the expression of previously reported viral miRNAs in the same cells. We hypothesize that the reported SARS-CoV-2 svRNAs could serve as biomarkers for early infection stages due to their high abundance. Finally, we found that both SARS-CoV-1 and SARS-CoV-2 infection induced up- and down-regulation of multiple endogenous human short RNAs that align predominantly to protein-coding and lncRNA transcripts. Interestingly, a significant proportion of short RNAs derived from full-length viral genomes also aligned to various hg38 sequences, suggesting opportunities to investigate regulatory roles of svRNAs during infection. Further characterization of the small RNA landscape of both viral and host genomes is clearly warranted to improve our understanding of molecular events related to infection and to design more efficient strategies for therapeutic interventions as well as early diagnosis.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
- 5
- FWCI
- 1.73
- Field percentile
- top 18%
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