ArticleBriefings in bioinformatics2021
Functional alterations caused by mutations reflect evolutionary trends of SARS-CoV-2.
Article in Briefings in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed.
- The disappearance of ORF8 in human-adapted coronaviruses: the Cheshire cat paradigm.Virus genes · 2026Article
- Drug-target interaction prediction based on graph convolutional autoencoder with dynamic weighting residual GCN.BMC bioinformatics · 2025Article
- Sequence signatures within the genome of SARS-CoV-2 can be used to predict host source.Microbiology spectrum · 2024Article
- Catechin Protects against Lipopolysaccharide-induced Depressive-like Behaviour in Mice by Regulating Neuronal and Inflammatory Genes.Current gene therapy · 2024Article
- Characterisation of SARS-CoV-2 clades based on signature SNPs unveils continuous evolution.Methods (San Diego, Calif.) · 2022Article
- Predicting protein stability changes upon single-point mutation: a thorough comparison of the available tools on a new dataset.Briefings in bioinformatics · 2022Article
- SARS-CoV-2 Mutations and their Viral Variants.Cytokine & growth factor reviews · 2022Review
- Comparative analysis of machine learning-based approaches for identifying therapeutic peptides targeting SARS-CoV-2.Briefings in bioinformatics · 2022Article
- Phylogenetic analysis of 17271 Indian SARS-CoV-2 genomes to identify temporal and spatial hotspot mutations.PloS one · 2022Article
- Drug repositioning for SARS-CoV-2 by Gaussian kernel similarity bilinear matrix factorization.Frontiers in microbiology · 2022Article
- Application of artificial intelligence and machine learning for COVID-19 drug discovery and vaccine design.Briefings in bioinformatics · 2021Article
- Hotspot Mutations in SARS-CoV-2.Frontiers in genetics · 2021Article
- Identification of Causal Genes of COVID-19 Using the SMR Method.Frontiers in genetics · 2021Article
- Prediction of Gastric Cancer-Related Proteins Based on Graph Fusion Method.Frontiers in cell and developmental biology · 2021Article
- Genomic Variation Prediction: A Summary From Different Views.Frontiers in cell and developmental biology · 2021Review
- Application of Machine Learning for Drug-Target Interaction Prediction.Frontiers in genetics · 2021Review
- Synthesis of Hetaryl-Substituted Asymmetric Porphyrins and Their Affinity to SARS-CoV-2 Helicase.Russian journal of general chemistry · 2021Article
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6 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Since the first report of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in December 2019, the COVID-19 pandemic has spread rapidly worldwide. Due to the limited virus strains, few key mutations that would be very important with the evolutionary trends of virus genome were observed in early studies. Here, we downloaded 1809 sequence data of SARS-CoV-2 strains from GISAID before April 2020 to identify mutations and functional alterations caused by these mutations. Totally, we identified 1017 nonsynonymous and 512 synonymous mutations with alignment to reference genome NC_045512, none of which were observed in the receptor-binding domain (RBD) of the spike protein. On average, each of the strains could have about 1.75 new mutations each month. The current mutations may have few impacts on antibodies. Although it shows the purifying selection in whole-genome, ORF3a, ORF8 and ORF10 were under positive selection. Only 36 mutations occurred in 1% and more virus strains were further analyzed to reveal linkage disequilibrium (LD) variants and dominant mutations. As a result, we observed five dominant mutations involving three nonsynonymous mutations C28144T, C14408T and A23403G and two synonymous mutations T8782C, and C3037T. These five mutations occurred in almost all strains in April 2020. Besides, we also observed two potential dominant nonsynonymous mutations C1059T and G25563T, which occurred in most of the strains in April 2020. Further functional analysis shows that these mutations decreased protein stability largely, which could lead to a significant reduction of virus virulence. In addition, the A23403G mutation increases the spike-ACE2 interaction and finally leads to the enhancement of its infectivity. All of these proved that the evolution of SARS-CoV-2 is toward the enhancement of infectivity and reduction of virulence.
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