CDDP variability
Different fingerprints were obtained for individual primer combinations. The primer combination F1R3b generated monomorphic profiles for all of the analysed accessions. The other used degenerate WRKY primers amplified a total of 34 consistent band lines, of which 22 were polymorphic. Fragment sizes ranged from 50 bp up to the 1200 bp when compared to 100 bp ladder (Bioline). A total of 258 bands were amplified in the set of control plants and six analysed variants of ZnO treatments and the polymorphism generated by individual primer pair ranged from 18% up to the 88% (Table 1). No unique amplicons were obtained, but the generated fingerprint profiles differ in control plants of both varieties (Fig 1).
The ability of used primer combinations to detect polymorphism was comparable only for combinations F1R2b and F1R3a, in the case of primer combination F1R1, the PIC value was much lower-0.08. The highest discrimination power was obtained for primer combination F1R2b, what correspond to the most distinct fingerprints for individual analysed accessions.
Constructed dendrogram for CDDP (Fig 2) was able to distinguish all analysed accessions. A total of two main branches were separated, distinctive fingerprints were obtained for control plants of both analysed soybean varieties with the Jaccard coefficient of genetic similarity 0.38. These two accessions produced specific fingerprints for all the primer combinations used in this study.
WRKY genes expression
Selected WRKY genes were subjected to compare its expression in leaves of ZnO foliar application treated plants compared to control ones as they represent the functional part of CDDP technique used in this study. Two different soybean varieties were used for this purpose. Effectivity of the real-time PCR for individual analysed WRKY genes was 0.97 for WRKY11, 0.90 for WRKY90, 0.96 for WRKY106 and 0.94 for WRKY149. The average Cts for individual WRKY genes were 31.7 for WRKY11, 33.1 for WRKY90, 31.8 for WRKY106 and 35.2 for WRKY149. Both analysed varieties were similar in the expression changes except of the WRKY90, where different patterns were obtained (Fig 3). No significant changes of expression were in the case of 1.4 mgxL
-1 foliar application of ZnO nanoparticles for WRKY11, WRKY106 and WRKY149 genes. The highest applied concentration of ZnO nanoparticles resulted in the relevant upregulation of all the analysed WRKY genes with the values from 5 times (Adelfia, WRKY 90) up to the 80 times (Mentor, WRKY 106). In none of analysed variants, downregulation of analysed genes was obtained.
Expression profiles of WRKY 11 gene were the most similar in both of analysed soybean varieties. WRKY90 expression profiles showed higher expression in 1.4 mgxL
-1 foliar application of ZnO nanoparticles when compared to all other evaluated WRKY genes and for Adelfia variety, 14 mgxL
-1 foliar application of ZnO nanoparticles showed 8 times higher expression, what was unique result.
The narrow gap between Zn essentiality and toxicity in plants exist (
Kaur and Garg, 2021), in sweet potato a total of 17.945 differentially expressed genes were identified in the two genotypes under zinc stress by transcriptomic analysis
(Meng et al., 2023). Conversely, Zn is involved in the defence mechanism of plants as well, such as Zn finger WRKY transcription factors control various plant processes including systemic acquired resistance (SAR)
(Rushton et al., 2010).
The mechanisms by which nanoparticles influence WRKY gene expression may involve several pathways. One potential pathway includes the activation of signalling cascades that lead to the phosphorylation of WRKY proteins, thus modulating their activity and stability
(Liu et al., 2024; Ma and Hu, 2024). Additionally, the involvement of reactive oxygen species (ROS) generated by nanoparticles could further stimulate the expression of WRKY genes, as ROS are known to act as signalling molecules in stress response pathways
(Li et al., 2025). The interaction of WRKY proteins with other regulatory elements and proteins, such as plant resistance (R) proteins, may also enhance their role in mediating responses to nanoparticles
(Liu et al., 2024; Ma and Hu, 2024).
WRKY11 transcription factors in
Glycine max L. have variable evolutionary conservation and functional importance in different roles. They express across tissues and WRKY11-1, WRKY11-2 and WRKY11-3 have been identified as being ubiquitously expressed across soybean tissues, indicating a broad regulatory role
(Mohanta et al., 2016). They are active in response to low phosphorus, as WRKY genes in soybean, including WRKY11 orthologs, show significant transcriptional responses to phosphorus deficiency, which is crucial for developing phosphorus-efficient soybean cultivars (
Kurt and Filiz, 2020). Their role in stress response in soybean was described with its co-expression networks suggesting involvement in tolerance to environmental challenges
(Mohanta et al., 2016). The expression pattern of WRKY genes in response to water deficit was found to be different in drought tolerant and drought susceptible genotypes
(Dias et al., 2016) and a concordance was for this and our study for WRKY106 and WRKY149 genes.
CDDP uses long primers that target plants’ genes responsive to abiotic and biotic stress (
Collard and Mackill, 2009). To our knowledge, in this study, it is the first time CDDP markers were used to characterize these genetic fingerprints to analyse plant response to nanoparticles foliar application. The typical fragment size range for
CDDP markers is between 200 and 1,500 bp stress (
Collard and Mackill, 2009). The results presented in our study contain a total of 258 amplified fragments in the range that not fully corresponding to the expected length, such as shortest amplicon started with the length of 50 bp, what should be specific for soybean genomic characteristics of WRKY genome-conserved sections of CDDP markers. When examining the averages of fragment sizes and their deviations, it was observed a distinctive pattern in the fingerprint of control plants of varieties Adelfia and Mentor. The CDDP was reported previously to be able revealed the same grouping pattern for genotypes of stressed plants (
El-Mogy et al., 2022) and for tomato, CDDP-genotypic and visual phenotypic assortment permitted the selection of two contrasting heat-tolerant and heat-sensitive cultivars
(Werghi et al., 2021). CDDP markers was proved to be used to determine the genetic variations among nanoparticles affected plant accessions.