Sodium Azide as a Chemical Mutagen in Wheat (Triticum aestivum L.): Patterns of the Genetic and Epigenetic Effects with iPBS and CRED-iPBS Techniques

Abstract

Wheat, which is scientifically known as Triticum aestivum L., is a very nutritious grain that serves as a key component of the human diet. The use of mutation breeding as a tool for crop improvement is a reasonably rapid procedure, and it generates a variety that may be used in selective breeding programs as well as functional gene investigations. The present experiment was used to evaluate the potential application of a conventional chemical mutagenesis technique via sodium azide (NaN3) for the germination and seedling growth stage in wheat. Experiments with NaN3 mutagenesis were conducted using four different treatment periods (0, 1, 2, and 3 h) and five different concentrations (0, 0.5, 1, 1.5, and 2 mM). The genomic instability and cytosine methylation of wheat using its seeds were investigated after they were treated. In order to evaluate the genomic instability and cytosine methylation in wheat that had been treated, interprimer binding site (iPBS) markers were used. The mutagenic effects of NaN3 treatments had considerable polymorphism on a variety of impacts on the cytosine methylation and genomic instability of wheat plants. The results of the experiment showed considerable changes in the iPBS profiles produced by the administration of the same treatments at different dosages and at different times. Coupled restriction enzyme digestion interprimer binding site (CRED-iPBS) assays identified changes in gDNA cytosine methylation. The highest polymorphism value was obtained during 1 h + 2 mM NaN3, while the lowest (20.7%) was obtained during 1 h + 1.5 mM NaN3. Results showed that treatments with NaN3 had an effect on the level of cytosine methylation and the stability of the genomic template in wheat plants in the germination stage. Additionally, an integrated method can be used to for mutation-assisted breeding using a molecular marker system in wheat followed by the selection of desired mutants.

In Vitro Genotoxic and Antigenotoxic Effects of Ten Novel Synthesized 4‐Thiazolidinone Derivatives

“…The mutagenicity of NaN 3 is due to the production of an organic metabolite ( L ‐azidoalanine) that enters the nucleus, and interacts with DNA, causing point mutations in the genome. One of the possible mechanisms responsible for the moderate (28.7 %) antimutagenic activity of C9 against NaN 3 ‐induced mutagenicity at a dose of 1.0 mM/plate could be inhibition of L ‐azidoalanine production [46–48] . This effect can be achieved by replacing the ‐Cl group on the carbon in the 4th position of the phenyl ring of C9 with the azide via the nucleophilic aromatic substitution reaction (S N Ar) [49] .…”

“…One of the possible mechanisms responsible for the moderate (28.7 %) antimutagenic activity of C9 against NaN 3 -induced mutagenicity at a dose of 1.0 mM/ plate could be inhibition of L-azidoalanine production. [46][47][48] This effect can be achieved by replacing the -Cl group on the carbon in the 4th position of the phenyl ring of C9 with the azide via the nucleophilic aromatic substitution reaction (S N Ar). [49] Furthermore, the positive mutagen NaN 3 is known to induce G : C!…”

Machine Learning Analysis of the Impact of Silver Nitrate and Silver Nanoparticles on Wheat (Triticum aestivum L.): Callus Induction, Plant Regeneration, and DNA Methylation

“…When compared to the control, the RAPD profiles revealed polymorphism when a band that was predicted to be present did not exist and a novel band did appear. Changes in the average polymorphism were calculated for each treatment group (changing concentrations of AgNO 3 and Ag-NPs), and the results were reported as a percentage in comparison to the value obtained from the control (which was set to 100%) [ 45 , 46 , 104 , 105 ]. A quantitative metric known as genomic template stability (GTS%) was estimated for RAPD using the formula GTS = (1 − a/n) × 100.…”

“…In this calculation, a represents the mean number of polymorphic bands in each treated template, and n represents the total number of bands in the control [ 38 , 103 ]. With the use of the formula Polymorphism = a/n × 100 [ 45 , 46 , 104 , 105 ], we were able to calculate the average polymorphism values (in percent) for each concentration.…”

“…In most cases, traditional statistical methods have been employed to analyze and interpret the output variables. These methodologies often utilize variance analysis and linear regression models to determine the degree of correlation between independent input factors and dependent output variables [ 45 , 46 ]. Complex factors and non-linear features present some of the most significant challenges for researchers working in the field of plant tissue culture [ 47 , 48 ].…”