Chaos Game Representation: An Alignment-Free Technique for Exploring Evolutionary Relationships of Protein Sequences

Abstract

Chaos Game Representation (CGR) is an iterative mapping technique, which shows patterns in amino acids or nucleotide sequences. Here we present a method for using CGR to explore evolutionary relationships of protein sequences based on amino acid properties and illustrate the approach with complete sets of protein translations from viral genomes. In an analysis of complete polyprotein sequences from the viral family Flaviviridae, the CGR method was able to cluster members of major viral groups together, but relations within groups were not well resolved in comparison to an alignment-based phylogeny. We applied the method to members of five different families of ssRNA positive-strand viruses, and each family formed a distinct cluster. We also present a method of testing the reliability of clustering in CGR-based trees, which involves the use of multiple random starting points for the CGR process.

Evolutionary Relationship of Protein Sequences of SARS-CoV-2 and Other Viruses through Chaos Game Representation

“…Considering the limitation that a 20-vertex CGR cannot be used to demonstrate the similarity of protein sequences with conservative substitution, Basu [14] proposed a 12-vertex CGR, with each vertex of a regular 12-sided polygon representing an amino acid with its conservative substitutions. The number of the vertices in CGR M. D. was then reduced to four [15] [16], with each vertex of the square representing one of the four groups of amino acids, that is, the non-polar, uncharged polar, negative polar, and positive polar groups. The reduction in the vertices of CGR images can help represent the similarity in protein sequences.…”