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Viral Mutations

Viral Mutations

A mutation is a change in the sequence of bases of DNA or RNA in a genome. Some mutations occur during replication of the genome due to errors made by the polymerase enzymes that replicate DNA or RNA. Unlike DNA polymerase, RNA polymerase is prone to errors because it is not capable of “proofreading” its work. Viruses with RNA-based genomes, like HIV, therefore accrue mutations faster than viruses with DNA-based genomes. Because mutation and recombination provide the raw material...

Single Nucleotide Polymorphisms-SNPs

Single Nucleotide Polymorphisms-SNPs

A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...

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Related Experiment Video

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DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning

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Rapidly Identifying New Coronavirus Mutations of Potential Concern in the Omicron Variant Using an Unsupervised

Lue Ping Zhao¹, Terry Lybrand², Peter Gilbert¹

¹Fred Hutchinson Cancer Research Center.

Research Square

|March 2, 2022

Summary

Machine learning identified core mutations in Omicron's spike protein and non-spike genes, accelerating SARS-CoV-2 transmission. Emerging mutations require close monitoring due to potential impacts on viral fusion and drug binding.

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Author Spotlight: A Pseudotype Virus System for Assessing Omicron Subvariants and Neutralizing Antibodies in SARS-CoV-2 Research

Author Spotlight: A Pseudotype Virus System for Assessing Omicron Subvariants and Neutralizing Antibodies in SARS-CoV-2 Research

Published on: September 8, 2023

Area of Science:

Virology
Genomics
Machine Learning

Background:

The Omicron variant of SARS-CoV-2 exhibits extensive mutations in its spike protein, potentially increasing transmission rates.
Rapid viral spread can lead to the emergence of new viral mutants, necessitating continuous genomic surveillance.

Approach:

An unsupervised machine learning model was applied to 4296 Omicron viral genomes.
Identified core haplotypes of mutations in both spike and non-spike genes.

Key Points:

A core haplotype of 28 polymutants in the spike protein and 17 in non-spike genes were identified.
Four new spike protein polymutants and five non-spike gene polymutants show significant increasing trajectories.
The N1192S mutation is in a conserved region critical for viral fusion; F694Y may affect Remdesivir binding.

Conclusions:

The identified core haplotypes provide a framework for investigating viral evolution.
Emerging mutations, particularly N1192S and F694Y, warrant close monitoring for their potential impact on viral behavior and therapeutic efficacy.
Continuous genomic surveillance is crucial for understanding and responding to SARS-CoV-2 evolution.