Microsatellite markers-aided dissection of iron, zinc and cadmium accumulation potential in Triticum aestivum

Total mineral content

The total Fe and Zn content of wheat flour was determined by nitric-hydrochloric acid digestion. Nitric acid (5 ml) was added to wheat flour (1 g) in a 250 ml digestive tube and kept in the fume hood overnight. After 24 h, freshly prepared aqua regia (three parts of 37% HCl and one part of 65% HNO₃) was added to the tube and heated at 200 °C for 45 min or until the volume reduced to about 1 ml and the fumes disappeared. After cooling, interior tube walls were washed with distilled water to avert the loss of sample and filtered with Whatman filter paper. In the end, a sufficient amount of distilled water was added to make the final volume (50 ml). An atomic absorption spectrometer (novAA® 350; Analytik Jena, Neckarsulm, Germany) was used to quantify the concentration of metals in the digestion mixture.

In vitro gastrointestinal digestion

Grain samples of 189 wheat accessions were used to evaluate Fe/Zn bioavailability by utilizing in vitro gastrointestinal digestion method described by Akhter et al. (2012) with apt modifications. Briefly, 3 g wheat flour was homogenized in 120 ml distilled water. The pH of the samples was maintained at 2.0 with 6 M/L HCL. The pH was checked and readjusted to 2 every 15 min. Subsequently, pepsin solution (1 ml) was added to the mixture followed by incubation in a shaking incubator (37 °C, 120 revolutions/min) for 2 h. An aliquot of gastric digest (12.5 ml) was obtained and raised to 120 ml with deionized water followed by the addition of pancreatin bile extract and pH was adjusted to 7.5 by 0.5 M NaOH. Afterward, 25 ml of 0.2 M NaHCO₃ was added and segments of dialysis tubing (Molecular mass cut off 10 kDa) were positioned on the flask containing gastric digest. It was then incubated in a shaker at 37 °C for 30 min. Later on, pancreatin-bile extract (5 ml) was added and incubated for 2 h until its pH reached 7. Bioavailability of Zn and Fe in the dialyzate was evaluated by atomic absorption spectrometry and calculated by the following formula:

$$Bioavailability\left(\mathrm{\%}\right)={\displaystyle \frac{Y}{Z}\times 100}$$where Y and Z represent the element content of the bioavailable fraction (mg mineral element/100 g grain) and the total Zn or Fe content (mg mineral element/100 g grain) respectively.

Phenotyping wheat accessions for agronomic traits

The Zn and Cd contents in wheat grains were not related to each other, but they were both negatively correlated with grain yield. Cd stress reduced plant height, 1,000 grain weight, number of tillers per plant, spike length, and number of grains per spike as compared to control conditions. The application of Zn enhanced the morphological and yield traits of wheat. Among two levels of Zn application, the high level (20 mg) had the maximum and more significant improving effect on agronomic traits, followed by the low level (5 mg) of Zn (Table 1 and Data S3). The combination of 10 mg Cd with 20 and 5 mg Zn showed improved patterns as compared to Cd-stressed plants. A combination of 20 mg Zn application and induced Cd stress recorded greater plant height, 1,000 grain weight, number of tillers per plant, spike length, and number of grains per spike, while the least was observed for wheat plants grown under 5 mg Zn and Cd stressed condition (Table 1). A study conducted by Farooq et al. (2020) also observed a higher impact of Cd on wheat grown at low levels of Zn. The present study proved that Zn supplements in soil fertilizers could reduce the effects of Cd and improve the agronomically important traits of wheat plants. During the early stages of the crop, a higher level of Zn enhances the dry matter and root growth, making it a fundamental micronutrient for seed germination.

Traits based germplasm evaluation

A wider range of phenotypes (Fe and Zn accumulation) was detected in the genotypes. The analysis of variation (ANOVA) was performed to reveal the genetic and environmental variations. A highly significant variation among genotypes indicated the availability of genetic variation among the selected genotypes, while a relatively non-significant environmental variation also indicated the accuracy of pot experiment (Table 1 and Data S3). The trait frequency distribution of Fe and Zn accumulation was performed and a normal distribution was observed among the genotypes for Zn accumulation. On the other hand, the frequency distribution for Fe accumulation was highly skewed and concentrated within a range of 25 to 75 mg/kg (Fig. 1 and Data S3). Further coefficient of variation (CV) was estimated. The CV also indicated a higher degree of variability in the selected germplasm (Descriptive). The genetic and environmental variations were used to estimate the possible heritability of genotypes for any of the next breeding programs.

Fe, Zn, and Cd contents in wheat grains

The wheat grains were evaluated for their available micronutrients. Reduced concentrations of Fe and Zn were observed in wheat grains that were raised from Cd-contaminated soil to control. Cd was transferred from roots to shoots and eventually to grains. It caused a reduction in the accumulation of micronutrients. Sole application of Zn enhanced Fe and Zn concentrations in grains of all wheat plants (Table 1). Among two levels (5 and 20 mg/Kg) of Zn, the higher concentration showed maximum Fe and Zn accumulation in grains compared to the lower Zn concentration. This may be due to sufficient Zn supply, which enhances germination and seedling growth owing to high cell division and expansion, enzyme activity, and protein synthesis. When 5, 20 mg/kg Zn was applied in soil contaminated with Cd (10 mg/kg), the Fe and Zn concentrations in wheat grains declined. However, the concentrations were still higher compared to the grains treated only with Cd.

Selection of markers and genotyping

The genes linked to the mineral accumulation were reviewed and the genes for Zn, Fe, and Cd were selected for further analysis. The genomic information for selected genes (5 kb $\pm$ genomic regions of a gene) was used to design primers as markers for Zn (18 primer sets), Fe (27 primer sets), and Cd (56 primer sets). All the designed primer sequences were verified against online databases (NCBI and Ensembl plants). The non-specific primers were removed from consideration (Table 2, Data S4). The 45 primer pairs were used to genotype the 189 wheat accessions which yielded a total of 101 alleles for further evaluation.

Population structure

The posterior probability of data, the LnP(D) scores for the number of populations (K) increased continuously from 1 to 3 and showed the inflation point at 3 (Table 3 and Fig. 2A), which split up the entire panel into three subgroups (Fig. 3). Therefore, 189 genotypes were divided into three sub-populations. These included a smaller subpopulation of 39 individuals (P1), and a major group of 76 individuals (P2) followed by a subpopulation of 74 genotypes (P3) (Fig. 2B). The subpopulation P3 also includes individuals with genetic admixture from the other two populations which may be due to the breeding activities at various research institutes. On the other hand, most of the genotypes were pure (Figs. 2B and 2C).

Principal component analysis

The first two PCs denoted as PC1 and PC2, explained the maximum variation among individuals as shown in Fig. 3A. PC1 divided the population into two distinct groups, while PC2 revealed a group of admixed germplasm (Fig. 3B). These results are consistent with the population genetic structure revealed by kinship analysis using K-matrix in GAPIT (Fig. 3D). Notably, the first two PCs account for the maximum variation in the dataset.

Phylogenetic analysis

The phylogenetic analysis divided the entire panel into three clades, similar to the population structure analysis (Fig. 3C). The first clade with nine genotypes represented the ancient and parental genotypes at the root of the phylogenetic tree while the other two bigger clades with maximum population sizes showed mixed genetic information and allelic combinations among the individuals.

Marker traits association

The statistical regression-based markers traits association was investigated (Fig. 4). The genetic markers were first classified as per their targeted traits such as the nutrient’s accumulations. A total of 18 markers were associated with Zn accumulation in plant tissues. Similarly, 27 and 56 genetic markers were associated with Fe and Cd accumulation, respectively. Out of the 18 markers associated with Zn accumulation, marker 1 and marker 2 were found to be highly associated with this trait, with the highest –log10 P-values (ranging from 7.34 to 13.83) across all five treatments (control, Cd₁₀, Zn₅, Zn₂₀, Cd₁₀+Zn₅, Cd₁₀+Zn₂₀). Similarly, among the 27 markers associated with Fe accumulation, the maximum association with the trait was observed for marker 19 and marker 20 (−log10 P values range 8.86–10.37) followed by markers 30, 31, and 32 (with –log10 P values range 7.6–9.97). Among the evaluated markers for Cd accumulation, two markers 90 and 91 did not show any genetic polymorphism. Therefore, the marker-traits association analysis was performed by using the information from 54 selected markers. Among the studied markers, marker 62 was the most associated (−log10 P value 4.00–4.54) followed by marker 89 for Cd accumulation in wheat plants (Data S5). The maximum number of significant associations was found for Fe accumulation in the wheat population. Among the evaluated markers for Fe accumulation, five markers (19, 20, 25, 26, and 37) were the most associated (−log10 P value 10.374) followed by markers 30, 31, and 32 for Fe accumulation (Data S5).

Germplasm selection

In light of the genotypic and phenotypic results, the top 20 wheat accessions for both Zn and Fe accumulation traits were selected. Among the pool of 40 genotypes with high Zn and Fe accumulation, eight were prominently selected for future breeding and research and were common to both pools (Table 4). The genotype FA-40 exhibited the highest score for Fe accumulation, while FA-35 showed the maximum Zn accumulation.