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Prediction of two novel overlapping ORFs in the genome of SARS-CoV-2.
Pavesi, Angelo.
  • Pavesi A; Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parco Area Delle Scienze 23/A, I-43124, Parma, Italy. Electronic address: angelo.pavesi@unipr.it.
Virology ; 562: 149-157, 2021 10.
Article in English | MEDLINE | ID: covidwho-1331287
ABSTRACT
Six candidate overlapping genes have been detected in SARS-CoV-2, yet current methods struggle to detect overlapping genes that recently originated. However, such genes might encode proteins beneficial to the virus, and provide a model system to understand gene birth. To complement existing detection methods, I first demonstrated that selection pressure to avoid stop codons in alternative reading frames is a driving force in the origin and retention of overlapping genes. I then built a detection method, CodScr, based on this selection pressure. Finally, I combined CodScr with methods that detect other properties of overlapping genes, such as a biased nucleotide and amino acid composition. I detected two novel ORFs (ORF-Sh and ORF-Mh), overlapping the spike and membrane genes respectively, which are under selection pressure and may be beneficial to SARS-CoV-2. ORF-Sh and ORF-Mh are present, as ORF uninterrupted by stop codons, in 100% and 95% of the SARS-CoV-2 genomes, respectively.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Genes, Overlapping / Open Reading Frames / Codon Usage / SARS-CoV-2 Type of study: Prognostic study Language: English Journal: Virology Year: 2021 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Genes, Overlapping / Open Reading Frames / Codon Usage / SARS-CoV-2 Type of study: Prognostic study Language: English Journal: Virology Year: 2021 Document Type: Article