Geometric analysis of SARS-CoV-2 variants

Area of Science:

• Virology
• Genomics
• Computational Biology

Background:

• Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a single-stranded RNA virus, causes a global respiratory pandemic.
• High mutation rates lead to diverse SARS-CoV-2 variants, including highly pathogenic strains like Omicron.
• Understanding the relationships and differences between SARS-CoV-2 variants is crucial.

Purpose of the Study:

• To construct a geometric space for representing and comparing SARS-CoV-2 variant genomes.
• To utilize an alignment-free method for genome space construction.
• To validate the geometric space through phylogenetic analysis.

Main Methods:

• Employed the natural vector method, an alignment-free technique, to establish a genome space.
• Utilized a 24-dimensional natural vector to represent SARS-CoV-2 genomes.
• Determined an appropriate metric via phylogenetic analyses to define the genome space.

Main Results:

• Phylogenetic trees constructed using the natural vector and metric aligned with established SARS-CoV-2 lineage naming standards.
• The geometric space successfully clustered lineages with identical alphabetical prefixes.
• The visualized relationships between GISAID clades largely corresponded with GISAID's clade descriptions.

Conclusions:

• The constructed geometric space effectively represents SARS-CoV-2 genomes and their relationships.
• Phylogenetic analyses validated the utility of this geometric space for variant comparison.
• This geometric approach offers a valuable tool for resolving issues related to SARS-CoV-2 variant analysis.