Full text
2,010 characters
· extracted from
oa-doi-fallback
· click to expand
Full text loading...
Abstract
SARS-CoV-2 infection triggers complex host responses, including alterations in RNA transcription, and modification. Understanding these changes is crucial for elucidating viral pathogenesis and identifying potential therapeutic targets. We used direct RNA sequencing to comprehensively profile the transcriptomic and epitranscriptomic landscapes of human HEK-AT cells infected with SARS-CoV-2 at 8 hours post-infection, compared to mock controls. We analyzed viral and host transcriptomes, focusing on gene and transcript expression, isoform usage, and RNA m6A modifications. Viral RNA sequencing reads showed 3’ end-biased coverage indicative of subgenomic RNA synthesis, with high expression of N and ORF10 genes. Sixteen m6A modification sites were consistently identified in the viral genome, primarily within the ORF1ab and S genes. In the human transcriptome, we found 254 positions with significantly altered m6A modification rates, with 119 showing decreased modification and 135 showing increased modification in infected cells. Genes with decreased m6A modifications were enriched in the neurotrophin signaling pathway. Transcript-level analysis identified 19 upregulated and 12 downregulated transcripts. Notably, transcript discovery and quantification revealed a novel isoform of the HIST1H2BK gene, which was significantly more expressed in infected cells compared to mock controls. Isoform switching analysis revealed 24 significant switches involving 21 genes, implicating mitochondrial reprogramming and immune-related pathways. In conclusion, this study provides a detailed, direct RNA sequencing-based characterization of host-virus RNA interactions, revealing key insights into SARS-CoV-2 infection mechanisms and potential therapeutic targets.
- Received:
- Version Posted:
Funding
-
Research Council of Finland
(Award 336472)
- Principal Award Recipient: Petri Auvinen
-
Sigrid Juselius Foundation
(Award 336471)
- Principal Award Recipient: Sarah J. Butcher
Text is read by the "Ask this paper" AI Q&A widget below.
Extraction quality varies by source — PMC NXML preserves structure
cleanly, OA-HTML may include some navigation residue, and OA-PDF can
have broken hyphenation. The publisher copy
(via DOI)
is the canonical version.