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Current Genomics

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ISSN (Print): 1389-2029
ISSN (Online): 1875-5488

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Research Article

Using Chaos-Game-Representation for Analysing the SARS-CoV-2 Lineages, Newly Emerging Strains and Recombinants

Author(s): Amarinder Singh Thind and Somdatta Sinha*

Volume 24, Issue 3, 2023

Published on: 24 October, 2023

Page: [187 - 195] Pages: 9

DOI: 10.2174/0113892029264990231013112156

Price: $65

Abstract

Background: Viruses have high mutation rates, facilitating rapid evolution and the emergence of new species, subspecies, strains and recombinant forms. Accurate classification of these forms is crucial for understanding viral evolution and developing therapeutic applications. Phylogenetic classification is typically performed by analyzing molecular differences at the genomic and sub-genomic levels. This involves aligning homologous proteins or genes. However, there is growing interest in developing alignment-free methods for whole-genome comparisons that are computationally efficient.

Methods: Here we elaborate on the Chaos Game Representation (CGR) method, based on concepts of statistical physics and free of sequence alignment assumptions. We adopt the CGR method for classification of the closely related clades/lineages A and B of the SARS-Corona virus 2019 (SARS-CoV-2), which is one of the fastest evolving viruses.

Results: Our study shows that the CGR approach can easily yield the SARS-CoV-2 phylogeny from the available whole genomes of lineage A and lineage B sequences. It also shows an accurate classification of eight different strains and the newly evolved XBB variant from its parental strains. Compared to alignment-based methods (Neighbour-Joining and Maximum Likelihood), the CGR method requires low computational resources, is fast and accurate for long sequences, and, being a K-mer based approach, allows simultaneous comparison of a large number of closely-related sequences of different sizes. Further, we developed an R pipeline CGRphylo, available on GitHub, which integrates the CGR module with various other R packages to create phylogenetic trees and visualize them.

Conclusion: Our findings demonstrate the efficacy of the CGR method for accurate classification and tracking of rapidly evolving viruses, offering valuable insights into the evolution and emergence of new SARS-CoV-2 strains and recombinants.

Keywords: CGR, alignment-free method, SARS-CoV-2, lineages A and B, XBB strain, phylogeny, CGRphylo, maximumlikelihood.

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