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Targeted accurate RNA consensus sequencing (tARC-seq) reveals mechanisms of replication error affecting SARS-CoV-2 divergence. | LitMetric

AI Article Synopsis

  • RNA viruses like SARS-CoV-2 replicate using error-prone RNA-dependent RNA polymerases, making it essential to monitor replication errors for understanding viral evolution.
  • The study introduces a new method called targeted accurate RNA consensus sequencing (tARC-seq) that allows for precise detection of rare RNA mutations in both lab and clinical samples.
  • Findings reveal an average of 2.68 new errors per replication cycle, with specific mutation patterns linked to genomic features, highlighting areas of the virus's genome that are more prone to mutations.

Article Abstract

RNA viruses, like SARS-CoV-2, depend on their RNA-dependent RNA polymerases (RdRp) for replication, which is error prone. Monitoring replication errors is crucial for understanding the virus's evolution. Current methods lack the precision to detect rare de novo RNA mutations, particularly in low-input samples such as those from patients. Here we introduce a targeted accurate RNA consensus sequencing method (tARC-seq) to accurately determine the mutation frequency and types in SARS-CoV-2, both in cell culture and clinical samples. Our findings show an average of 2.68 × 10 de novo errors per cycle with a C > T bias that cannot be solely attributed to APOBEC editing. We identified hotspots and cold spots throughout the genome, correlating with high or low GC content, and pinpointed transcription regulatory sites as regions more susceptible to errors. tARC-seq captured template switching events including insertions, deletions and complex mutations. These insights shed light on the genetic diversity generation and evolutionary dynamics of SARS-CoV-2.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11384275PMC
http://dx.doi.org/10.1038/s41564-024-01655-4DOI Listing

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