bioRxivGeneticsPreprint
Structural Variants in SARS-CoV-2 Occur at Template-Switching Hotspots
Brianna ChrismaniD, Kelley Marie PaskoviD, Nate StockhamiD, Kevin Tabatabaei, Jae-Yoon JungiD, Peter Yigitcan WashingtoniD, Maya VarmaiD, Min SuniD, Sepideh MalekiiD, Dennis Paul WalliD
Abstract
The evolutionary dynamics of SARS-CoV-2 have been carefully monitored since the COVID-19 pandemic began in December 2019, however, analysis has focused primarily on single nucleotide polymorphisms and largely ignored the role of structural variants (SVs) as well as recombination in SARS-CoV-2 evolution. Using sequences from the GISAID database, we catalogue over 100 insertions and deletions in the SARS-CoV-2 consensus sequences. We hypothesize that these indels are artifacts of imperfect homologous recombination between SARS-CoV-2 replicates, and provide four independent pieces of evidence. (1) The SVs from the GISAID consensus sequences are clustered at specific regions of the genome. (2) These regions are also enriched for 5 and 3 breakpoints in the transcription regulatory site (TRS) independent transcriptome, presumably sites of RNA-dependent RNA polymerase (RdRp) template-switching. (3) Within raw reads, these structural variant hotspots have cases of both high intra-host heterogeneity and intra-host homogeneity, suggesting that these structural variants are both consequences of de novo recombination events within a host and artifacts of previous recombination. (4) Within the RNA secondary structure, the indels occur in "arms" of the predicted folded RNA, suggesting that secondary structure may be a mechanism for TRS-independent template-switching in SARS-CoV-2 or other coronaviruses. These insights into the relationship between structural variation and recombination in SARS-CoV-2 can improve our reconstructions of the SARS-CoV-2 evolutionary history as well as our understanding of the process of RdRp template-switching in RNA viruses.
- organism: virus
- assay: whole-genome sequencing
- research focus: variant calling
- approach: statistical model
- Citations
- 2
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