Phylogeny Reconstruction of an Agricultural Crop Based on Nucleotide Sequence Homology Data Using a Genetic Algorithm

Phylogenetic analysis methods are widely used in the agro-industry to determine the level of divergence from type. Phylogeny allows us to establish a measure of similarity between homologous objects by reconstructing evolutionary history using tree topology based on data from specific regions of nucleotide sequences. There are widely used methods, such as, maximum likelihood and Bayes methods give different results on certain initial datasets of the same samples. This paper considers the genetic algorithm as an alternative method for phylogenetic tree construction. The paper considers a model of a modified genetic algorithm implemented as a program. Comparison in progress of maximum likelihood methods, Bayesian method and the proposed genetic algorithm on data with different homology of nucleotide sequences. The computational experiment using the genetic algorithm for phylogenetic reconstruction of the genus Triticum shows similar results for different sets of initial data, in contrast to other methods. Therefore, we can speak about the reliability of using this method for phylogeny.