Genomic Diversity and Recombination Analysis of the Spike Protein Gene from Selected Human Coronaviruses.
Sayed Sartaj SohrabFatima AlsaqafAhmed Mohamed HassanAhmed Majdi TolahLeena Hussein BajraiEsam Ibraheem AzharPublished in: Biology (2024)
Human coronaviruses (HCoVs) are seriously associated with respiratory diseases in humans and animals. The first human pathogenic SARS-CoV emerged in 2002-2003. The second was MERS-CoV, reported from Jeddah, the Kingdom of Saudi Arabia, in 2012, and the third one was SARS-CoV-2, identified from Wuhan City, China, in late December 2019. The HCoV-Spike (S) gene has the highest mutation/insertion/deletion rate and has been the most utilized target for vaccine/antiviral development. In this manuscript, we discuss the genetic diversity, phylogenetic relationships, and recombination patterns of selected HCoVs with emphasis on the S protein gene of MERS-CoV and SARS-CoV-2 to elucidate the possible emergence of new variants/strains of coronavirus in the near future. The findings showed that MERS-CoV and SARS-CoV-2 have significant sequence identity with the selected HCoVs. The phylogenetic tree analysis formed a separate cluster for each HCoV. The recombination pattern analysis showed that the HCoV-NL63-Japan was a probable recombinant. The HCoV-NL63-USA was identified as a major parent while the HCoV-NL63-Netherland was identified as a minor parent. The recombination breakpoints start in the viral genome at the 142 nucleotide position and end at the 1082 nucleotide position with a 99% CI and Bonferroni-corrected p -value of 0.05. The findings of this study provide insightful information about HCoV-S gene diversity, recombination, and evolutionary patterns. Based on these data, it can be concluded that the possible emergence of new strains/variants of HCoV is imminent.
Keyphrases
- sars cov
- respiratory syndrome coronavirus
- copy number
- genome wide
- saudi arabia
- endothelial cells
- dna damage
- dna repair
- genetic diversity
- escherichia coli
- induced pluripotent stem cells
- pluripotent stem cells
- coronavirus disease
- healthcare
- dna methylation
- oxidative stress
- machine learning
- electronic health record
- deep learning
- binding protein
- health information