Bioinformatic method for determining single nucleotide polymorphisms on the example of gene <i>WIN</i> in <i>Glycine max</i>

Abstract

In this paper, a hypothetical method for locating SNPs (single nucleotide polymorphisms) on the example of the ribonuclease gene WIN was proposed. Ribonuclease comprises an enzyme that participates in defence reactions against fungal infections in soybeans, as well as other protective responses to biotic stress. Its belonging to the RNA-ases group determines the specific properties, namely the ability to degrade foreign nucleic acids. This ability provides for a general nonspecific immune response of the plant to the invasion of antigenic structures. Modern biotechnology calls for the development of molecular methods and approaches that will increase the resistance of a culture or accelerate the processes of its adaptation in the field. This problem can be solved by using technologies of SNP artificial induction in those parts of the genome that encode proteins capable of acting in protective reactions against biotic stress. In the study, 5 single-nucleotide polymorphisms were proposed using bioinformatic analysis. Since the localisation and detection of SNPs comprise a challenging task due to the presence of a single nucleotide change, in the biotechnological practice, predictive analysis is carried out in order to localise the potential sequence of occurring single-nucleotide polymorphism. Following the identification of the hypothetical SNP location, they can be further detected using complex molecular methods, such as real-time PCR or local sequencing. This technology can become a powerful tool for breeding soybean varieties having predetermined properties. Such theoretical and predictive models will allow for a quicker response to the dynamic environment under manmade load on plants.