Triticale doubled haploid plant regeneration factors linked by structural equation modeling

Triticale regeneration via anther culture faces many difficulties, e.g., a low percentage of regenerated plants and the presence of albinos. Plant regeneration may be affected by abiotic stresses and by ingredients added to the induction medium. The latter influences biochemical pathways and plant regeneration efficiency. Among such ingredients, copper and silver ions acting as cofactors for enzymatic reactions are of interest. However, their role in plant tissue cultures and relationships with biochemical pathways has not been studied yet.The study evaluated relationships between DNA methylation, changes in DNA sequence variation, and green plant regeneration efficiency influenced by copper and silver ions during triticale plant regeneration. For this purpose, a biological model based on donor plants and their regenerants, a methylation-sensitive amplified fragment length polymorphism, and structural equation modeling were employed.The green plant regeneration efficiency varied from 0.71 to 6.06 green plants per 100 plated anthers. The values for the components of tissue culture-induced variation related to cytosine methylation in a CHH sequence context (where H is A, C, or T) were 8.65% for sequence variation, 0.76% for DNA demethylation, and 0.58% for de novo methylation. The proposed model states that copper ions affect the regeneration efficiency through cytosine methylation and may induce mutations through, e.g., oxidative processes, which may interfere with the green plant regeneration efficiency. The linear regression confirms that the plant regeneration efficiency rises with increasing copper ion concentration in the absence of Ag ions in the induction medium. The least absolute shrinkage and selection operator regression shows that de novo methylation, demethylation, and copper ions may be involved in the green plant regeneration efficiency. According to structural equation modeling, copper ions play a central role in the model determining the regeneration efficiency.