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

The objective of this study was to comprehend the efficiency of wheat regeneration, callus induction, and DNA methylation through the application of mathematical frameworks and artificial intelligence (AI)-based models. This research aimed to explore the impact of treatments with AgNO3 and Ag-NPs on various parameters. The study specifically concentrated on analyzing RAPD profiles and modeling regeneration parameters. The treatments and molecular findings served as input variables in the modeling process. It included the use of AgNO3 and Ag-NPs at different concentrations (0, 2, 4, 6, and 8 mg L-1). The in vitro and epigenetic characteristics were analyzed using several machine learning (ML) methods, including support vector machine (SVM), random forest (RF), extreme gradient boosting (XGBoost), k-nearest neighbor classifier (KNN), and Gaussian processes classifier (GP) methods. This study's results revealed that the highest values for callus induction (CI%) and embryogenic callus induction (EC%) occurred at a concentration of 2 mg L-1 of Ag-NPs. Additionally, the regeneration efficiency (RE) parameter reached its peak at a concentration of 8 mg L-1 of AgNO3. Taking an epigenetic approach, AgNO3 at a concentration of 2 mg L-1 demonstrated the highest levels of genomic template stability (GTS), at 79.3%. There was a positive correlation seen between increased levels of AgNO3 and DNA hypermethylation. Conversely, elevated levels of Ag-NPs were associated with DNA hypomethylation. The models were used to estimate the relationships between the input elements, including treatments, concentration, GTS rates, and Msp I and Hpa II polymorphism, and the in vitro output parameters. The findings suggested that the XGBoost model exhibited superior performance scores for callus induction (CI), as evidenced by an R2 score of 51.5%, which explained the variances. Additionally, the RF model explained 71.9% of the total variance and showed superior efficacy in terms of EC%. Furthermore, the GP model, which provided the most robust statistics for RE, yielded an R2 value of 52.5%, signifying its ability to account for a substantial portion of the total variance present in the data. This study exemplifies the application of various machine learning models in the cultivation of mature wheat embryos under the influence of treatments and concentrations involving AgNO3 and Ag-NPs.

Advances in bread wheat production through CRISPR/Cas9 technology: a comprehensive review of quality and other aspects.

MAIN CONCLUSION: This review provides a comprehensive overview of the CRISPR/Cas9 technique and the research areas of this gene editing tool in improving wheat quality. Wheat (Triticum aestivum L.), the basic nutrition for most of the human population, contributes 20% of the daily energy needed because of its, carbohydrate, essential amino acids, minerals, protein, and vitamin content. Wheat varieties that produce high yields and have enhanced nutritional quality will be required to fulfill future demands. Hexaploid wheat has A, B, and D genomes and includes three like but not identical copies of genes that influence important yield and quality. CRISPR/Cas9, which allows multiplex genome editing provides major opportunities in genome editing studies of plants, especially complicated genomes such as wheat. In this overview, we discuss the CRISPR/Cas9 technique, which is credited with bringing about a paradigm shift in genome editing studies. We also provide a summary of recent research utilizing CRISPR/Cas9 to investigate yield, quality, resistance to biotic/abiotic stress, and hybrid seed production. In addition, we provide a synopsis of the laboratory experience-based solution alternatives as well as the potential obstacles for wheat CRISPR studies. Although wheat's extensive genome and complicated polyploid structure previously slowed wheat genetic engineering and breeding progress, effective CRISPR/Cas9 systems are now successfully used to boost wheat development.

Characterization of Two-Component System gene (TCS) in melatonin-treated common bean under salt and drought stress.

The two-component system (TCS) generally consists of three elements, namely the histidine kinase (HK), response regulator (RR), and histidine phosphotransfer (HP) gene families. This study aimed to assess the expression of TCS genes in P. vulgaris leaf tissue under salt and drought stress and perform a genome-wide analysis of TCS gene family members using bioinformatics methods. This study identified 67 PvTCS genes, including 10 PvHP, 38 PvRR, and 19 PvHK, in the bean genome. PvHK2 had the maximum number of amino acids with 1261, whilst PvHP8 had the lowest number with 87. In addition, their theoretical isoelectric points were between 4.56 (PvHP8) and 9.15 (PvPRR10). The majority of PvTCS genes are unstable. Phylogenetic analysis of TCS genes in A. thaliana, G. max, and bean found that PvTCS genes had close phylogenetic relationships with the genes of other plants. Segmental and tandem duplicate gene pairs were detected among the TCS genes and TCS genes have been subjected to purifying selection pressure in the evolutionary process. Furthermore, the TCS gene family, which has an important role in abiotic stress and hormonal responses in plants, was characterized for the first time in beans, and its expression of TCS genes in bean leaves under salt and drought stress was established using RNAseq and qRT-PCR analyses. The findings of this study will aid future functional and genomic studies by providing essential information about the members of the TCS gene family in beans. Supplementary Information: The online version contains supplementary material available at 10.1007/s12298-023-01406-5.

Cobalt-induced retrotransposon polymorphism and humic acid protection on maize genome.

Retrotransposon activity and genomic template stability (GTS) are one of the most significant rearranging mechanisms in environmental stress. Therefore, in this study, it is aimed to elucidate effecting of Cobalt (Co) on the instability of genomes and Long Terminal Repeat retrotransposon polymorphism in Zea mays and whether humic acid (HA) has any role on these parameters. For this purpose, Retrotransposon-microsatellite amplified polymorphism (REMAP) and Inter-Retrotransposon Amplified Polymorphism (IRAP) markers were applied to evaluate retrotransposon polymorphism and the GTS levels. It was found that IRAP and REMAP primers generate unique polymorphic band structures on maize plants treated with various doses of Co. Retrotransposon polymorphism increased and GTS decreased while increasing Co concentration. On the other hand, there was a reduction in negative effects of Co on retrotransposon GTS and polymorphism after treatment with HA. The results indicate that HA may be used effectively for the protection of maize seedlings from the destructive effects of Co toxicity.