Molecular and agro-morphological diversity assessment of some bread wheat genotypes and their crosses for drought tolerance

Plant materials and experimental treatment

Five wheat genotypes were utilized in this study (Table 1). The parents in this study were selected based on diversity in drought tolerance from a preliminary screening trial. A half-diallel mating design (5 ×5) produced 10 F1 hybrids during the winter season of 2020–2021. The genotypes of the parents and their offspring were assessed in field conditions at Experimental Farm of Faculty of Agriculture belongs to Zagazig University, Egypt (30°35′15″N, 31°30′07″E, 16 m asl) under ordinary growing conditions during the growing season of 2021 to 2022. The experimental site has an arid climate and receives low precipitation with an average annual rainfall of approximately 55 mm. The experiment was carried out in three replicates using a completely randomized design. The assessed genotypes (parents and F1 crosses) were represented by fifteen seeds planted in pots containing 10 kg of soil. After 15 days, the number of plants per pot was reduced to ten through thinning. Phosphorus and potassium fertilizers were applied as basal doses with a rate of 30 mg P₂O₅ per kg of soil for superphosphate and 50 mg K₂O per kg of soil for potassium sulfate. Nitrogen fertilizer was applied in three installments at a rate of 80 mg N per kg of soil using ammonium sulfate. These installments were done at 20, 35, and 50 days after sowing, along with irrigation water. Intercultural practices such as weeding were performed as needed to maintain optimal growing conditions. To induce drought stress, the irrigation schedule for the pots was adjusted. The stressed pots received water once a week, while the control well-watered pots were irrigated every three days. Soil water tension was measured using a tensiometer to maintain appropriate irrigation levels for both the well-watered and stressed pots were maintained.

Extraction of genomic DNA

For genomic DNA extraction, 100 grams of young wheat leaves were collected from 20 days old seedlings were employed for the extraction of genomic DNA utilizing a modified CTAB-based protocol (Doyle, 1991; Scobeyeva et al., 2018). The quantity and purity of the extracted DNA were assessed using a NanoDroP2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). The DNA concentration was adjusted to 50 ng/µL, and the isolated DNA was stored at −20 °C for subsequent amplification procedures.

Inter-Simple Sequence Repeats (ISSR-PCR)

Genetic polymorphism analysis of wheat cultivars and their F1 hybrids was conducted utilizing ISSR-PCR. Primers for the analysis are presented in Table 2. The PCR protocol followed the methodology established by Moreno, Martín & Ortiz (1998). Each reaction mixture, with a volume of 25 µL, contained the following components: 2 µL of 5x reaction buffer, 20 ng/µL of template DNA, µL of 200 µM dNTPs, 2 µL of 25 mM MgCl2, 22 µL of primer (10 pmol), and 1 unit of Taq DNA polymerase (Promega). The thermocycling protocol commenced with an initial denaturation step at 94 °C for 5 min, followed by 35 amplification cycles. Each cycle comprised denaturation at 94 °C for 1 min, annealing at a primer-specify temperature for 1 min and extension at 72 °C for 1 min. The procedure concluded with a final extension at 72 °C for 5 min.

Start Codon Targeted amplification

A 25 µL PCR amplification was conducted utilizing a SCoT-PCR based marker system. The reaction mixture consisted of ten µL of GoTaq Green-Master Mix, one µL of template DNA, one µL of primers, and nuclease free water to achieve a final volume of 25 µL. Thermal cycling was carried out using an Applied-Biosystems thermal cycler with the following protocol: initial denaturation at 94 °C for 5 mins, followed by 30 cycles of denaturation at 94 °C for 1 min, annealing at 50 °C for 1 min, and extension at 72 °C for 1 min.

Gel electrophoresis

The amplified products from ISSR and SCoT reactions were separated on 1% agarose gels and visualized using ethidium bromide (MP Biomedicals, Goddard Irvine, CA, USA) staining in TBE buffer (pH 8.5). DNA fragment sizes were estimated using a 1 kbp DNA ladder.

Agro-morphological characterization

After 60 days from cultivation, the following measurements were taken; shoot length (cm), root length (cm), shoot fresh weight (g), shoot dry weight (g), root fresh weight (g), and root dry weight (g). The proline content in the plant samples was assessed as follows: 0.5 g of leaves were ground and mixed with 10 mL of 3% aqueous sulfosalicylic-acid to create an extract. After filtration through filter paper, two mL of this extract were combined with two mL of acid ninhydrin-reagent and two mL of glacial-acetic acid. The mixture was heated at 100 °C for 1 h, followed by rapid cooling on ice. To extract the proline, 4 mL of toluene were added to the reaction mixture, and the resulting supernatant was used for proline determination. Absorbance was measured at 520-nm employing a spectrophotometer with toluene used as the blank (Bates, Waldren & Teare, 1973). Additionally, following the experiment, the following traits were collected when the plants reached physiological maturity after about 140 days after sowing: the number of spikelets/spike, spike length (cm), number of grains/spike, and grain weight/spike were recorded from five main spikes from each pot.

Data analysis

Using molecular markers, this study explored the genetic diversity and relatedness among the studied wheat genotypes and crosses. Specific PCR loci based on SCoT and ISSR techniques were employed. Each locus was classified as either absent (0) or present (1) and all loci were regarded as independent variables. Genetic diversity was assessed by analyzing the banding patterns generated from the PCR amplifications across all genotypes. The polymorphism level, a measure of genetic variation, was determined by dividing the number of loci exhibiting polymorphism (different banding patterns) by the total number of scored loci. Genetic similarities among the wheat cultivars and hybrids were computed using Dice’s coefficient (Dice, 1945). This coefficient was determined utilizing SPSS software version 29.0.10 (Norušis, 1993). A clustering analysis was subsequently performed to generate a dendrogram depicting the phylogenetic relationships among the genotypes (Rokach & Maimon, 2005). The dendrogram, principal component, and heatmap analyses were applied R programming version 4.1.1 (R Core Team, 2021). The analysis of variance (ANOVA) was performed on all studied traits using a completely randomized design. Combining abilities were evaluated employing Griffing Method 4, Model 1 (Griffing, 1956) using R programming version 4.1.1 (R Core Team, 2021). Statistically significant differences among the evaluated wheat genotypes were determined employing least significant difference (LSD) test at P < 0.01.

Molecular analyses

The genetic diversity analysis among the developed crosses and their parental genotypes was assessed via ISSR and SCoT molecular markers using six ISSR primers and two SCoT primers (Fig. 1). Seventy-six loci were detected using ISSR and SCoT-PCR primers screened in the 15 genotypes (Table 3). The amplified loci/primer were 9.5. Among 76 ISSR and SCoT-PCR loci, 28 were polymorphic (9.5/primer), and 48 were monomorphic (6/primer). Polymorphism ranged from 58.3% (ISSR3) to 23% (SCoT2), averaging 36.36%. The lowest genetic distance (1.41) was observed between P1 ×P4 vs. P4 ×P5, as well as P3 ×P5 vs P4 ×P5. This suggests a close genetic similarity between these populations. Conversely, the highest genetic distance (3.61) was detected between P2 ×P4 vs P2 ×P5, indicating greater genetic divergence (Table 4). The Dice coefficient was employed to analyze similarity matrices constructed from data obtained with eight primers. According to Table 5, the highest similarity (0.975) was observed between P4 ×P5 and P1 ×P4, whereas the lowest similarity (0.818) was found between P2 ×P5 and P2. These findings may be useful for understanding the genetic relationships between different wheat populations and informing breeding programs.

Phylogeny analysis

The clustering analysis based on ISSR and SCoT banding profiles grouped the evaluated wheat genotypes into five groups A–E (Fig. 2). Cluster A included only P2 ×P5, while B contained P1, and C comprised P2. Besides, Group D contained four genotypes P1 ×P2, P1 ×P3, P1 ×P5, and P3 ×P4. Finally, cluster E comprised eight genotypes P4, P3, P2 ×P3, P2 ×P4, P5, P1 ×P4, P3 ×P5, and P4 ×P5.

Diallel analysis

The analysis of variance exhibited significant differences among genotypes, parents, F1 crosses, and parent vs cross for all evaluated traits under both conditions (Table 6). Dividing the genotypic effect into GCA and SCA components showed that the mean squares of GCA and SCA were highly significant for all studied traits. The ratio of GCA/SCA was more than the unity for all evaluated traits, except root dry weight under normal conditions indicating the preponderance of additive gene effects in controlling the inheritance of these traits.

The parental genotypes P1 and P3 exhibited positive and significant general combining ability (GCA) effects for shoot fresh weight, shoot dry weight, root fresh weight, root dry weight, shoot length, and root length under well-watered conditions (Table 7). Additionally, P3 and P4 presented the highest GCA effects for number of spikelets per spike, number of grains per spike, and grain weight per spike under normal conditions. While, under drought stress, P3 and P5 had the highest GCA estimates. In contrast, P5 presented the maximum GCA effects and proved to be the best combiner under drought stress conditions.

The SCA values for the cross combinations are presented in Table 8. The highest significant and positive SCA effects for shoot fresh weight were observed in P1 ×P3 under well-watered conditions and P2 ×P3 under water scarcity conditions. For shoot dry weight, the highest significant and positive SCA values were exhibited by P1 ×P2, P1 ×P3, and P4 ×P5 under normal conditions, and by P1 ×P2, P1 ×P3, P2 ×P5, P3 ×P4, and P3 ×P5 under drought stress conditions. For root fresh weight, P3 ×P5 showed positive and significant SCA effects under drought stress. Additionally, the crosses P1 ×P3, P1 ×P4, P2 ×P4, P2 ×P5, and P3 ×P5 recorded the highest positive and significant SCA effects under both conditions. Regarding shoot length, the crosses P1 ×P2 and P1 ×P3 displayed significantly positive SCA effects under normal conditions, while P3 ×P5 did so under water-stress conditions. P4 ×P5 possessed the highest positive and significant SCA effects for root length under both conditions, with P2 ×P3 showing similar effects under drought stress. For spike length, high SCA effects were obtained by P1 ×P4 and P2 ×P3 under normal conditions, and by P2 ×P3, P3 ×P4, and P3 ×P5 under stressed conditions. In the case of the number of spikelets per spike, the cross P3 ×P5 recorded the highest positive and significant SCA effects under drought conditions. For the number of grains per spike, the cross combinations P1 ×P4 and P3 ×P5 possessed the highest values under normal conditions, while P3 ×P4 and P3 ×P5 did so under stress. Similarly, the crosses P1 ×P4, P1 ×P5, and P4 ×P5 were identified as good specific combiners for grain weight per spike under well-watered conditions, while P2 ×P3 showed the highest values under drought stress.

Agro-morphological traits

The performance of the studied wheat genotypes and their corresponding F1 crosses for agro-morphological traits under both drought and well-watered conditions is illustrated in Figs. 3 to 5. Differences between the assessed genotypes were observed for all studied attributes. P1 and P3 exhibited high shoot fresh and dry weights under well-watered conditions which was reflected in the performance of their F1 crosses P1 ×P3, P1 ×P2, P3 ×P5, and P2 ×P3 (Fig. 3). The shoot fresh weight of P3 and P1 was reduced by 40.9% and 49.2% under drought stress compared to well-watered conditions. Besides, the crosses P3 ×P5, P2 ×P3, P1 ×P2, and P1 ×P3 displayed reductions in shoot fresh weight by 24.7%, 18.9%, 41.3%, and 45.4%, respectively. Similarly, P3 ×P5, P2 ×P3, P1 ×P2, P1 ×P3, P1, and P3 exhibited reductions in their shoot dry weight by 25.1%, 26.1%, 35.9%, 37.2%, 39.6%, and 41.3%, respectively. The greatest root fresh and dry weights under water deficit were achieved by P5 (Orabi-1881) and its F1 crosses P2 ×P5 and P3 ×P5 (Fig. 3), highlighting the significance of these crosses in breeding programs. The root fresh weight of P5, P2 ×P5, and P3 ×P5 was reduced by 16.2%, 21.1%, and 27.9%, respectively, under water deficit conditions compared to well-watered conditions. However, these genotypes showed an increase in root dry weight by 3.9%, 3.5%, and 1.4%, respectively.

Drought significantly reduces overall wheat growth, which is evident in the substantial reduction in plant height for most genotypes. P1, P3, and their cross P1 ×P3 showed high shoot length under normal conditions (Fig. 4). Under water deficit conditions, P3, P5, P3 ×P5, and P1 ×P3 performed best for shoot length. Under water deficit conditions compared to well-watered conditions, the genotypes P5, P3 ×P5, P3, P1 ×P3, and P1, displayed reductions in shoot length by 18.6%, 25.1%, 30.6%, 45.5%, and 55.2%, respectively. The genotypes P5 and P2 ×P5 maintained shoot and root length under both conditions. Root length values of P5, P4 ×P5, P3 ×P5, and P3 ×P4 were higher under drought than under well-watered conditions (Fig. 4). The genotypes P5, P4 ×P5, P3 ×P5, and P3 ×P4, displayed increases in root length by 48.9%, 21.8%, 4.0%, 3.1%, and respectively under drought stress compared to normal conditions. All genotypes showed significantly higher proline accumulation under drought stress. P2 had the highest proline content under drought and the lowest under well-watered conditions, while P3 had the opposite (Fig. 4). P2 ×P3, P3 ×P5, P3, and P3 ×P4 had the highest mean spike length under normal conditions, while P1 ×P5 and P1 had the lowest values (Fig. 5). Under drought stress compared to normal conditions, the genotypes P3 ×P5, P3 ×P4, P2 ×P3, and P3, exhibited reductions in spike length by 19.5%, 19.6%, 20.0%, and 25.3%, respectively. On the other hand, under drought conditions, P1 spike length was less affected compared to P2, P4, and P2 ×P4. P1 exhibited a reduction in spike length by 11.9%, while P2, P4, and P2 ×P4 showed reductions of 32.9%, 34.6%, and 41.5%, respectively under drought stress compared to normal conditions. P3 ×P5 possessed the uppermost number of spikelets per spike under both conditions, while P2 had the lowest number. Under well-watered conditions, P3 ×P4, P1 ×P4, and P3 showed the highest grain number per spike. However, under drought stress, these genotypes exhibited 42.5%, 50.0%, and 57.6% reductions, respectively. In contrast, P2 and P1 ×P5 had the lowest grain number per spike under well-watered conditions, with reductions of 30.9% and 40.1%, respectively, under drought stress. Conversely, under drought stress, P5, P2 ×P5, P3 ×P5, and P3 ×P4 exhibited the greatest grain number per spike, with reduction percentages of 22.7%, 29.4%, 35.7%, and 42.5%, respectively. Moreover, under drought stress, P5, P3 ×P4, P2 ×P5, and P4 ×P5 had the highest grain weight per spike, with reduction percentages of 42.4%, 76.0%, 65.6%, and 73.2%, respectively. Conversely, P3, P1 ×P3, P1 ×P5, and P4 showed the lowest grain weight per spike, with reductions of 81.07%, 75.33%, 74.90%, and 74.48%, respectively, indicating their higher sensitivity to drought.

Genotypic classification

The data obtained from agro-morphological characters were employed to illustrate the relatedness among the tested wheat genotypes based on their agronomic performance under drought stress (Fig. 6). The analysis grouped wheat genotypes into three distinct clusters (A–C). Group A included three genotypes: P5, P2 ×P5, and P3 ×P5, which exhibited the best performance under drought stress, identifying them as highly drought-tolerant. Group B consisted of six genotypes: P4 ×P5, P1, P1 ×P3, P3, P3 ×P4, and P2 ×P3, which showed intermediate tolerance to drought stress. This indicates that these genotypes possess moderate drought resilience. Group C comprised six genotypes: P1 ×P5, P2, P1 ×P4, P4, P1 ×P2, and P2 ×P4, which exhibited the lowest tolerance to drought stress. These genotypes are considered drought-sensitive. This clustering provides valuable insights for selecting genotypes for breeding programs to improve wheat drought tolerance.

Association among assessed genotypes and evaluated characters

Principal component analysis was performed to illustrate the association among agro-morphological attributes of the wheat crosses and their parental genotypes. The first two PCs displayed the most variance registering around 85.08% (62.36% and 22.72% for PC1 and PC2 in the same order), and were used to construct the PC-biplot (Fig. 7). PCA1 effectively categorized the assessed genotypes into groups depending on their position on the positive or negative side. The genotypes on the positive side of PCA1 were associated with high performance, particularly P5, P3 ×P 5, P2 ×P5, P3 ×P4, P2 ×P3, P4 ×P5, and P1. Conversely, the genotypes on the negative side of PCA1 exhibited inferior performance, remarkably P1 × P5, P2, P1 ×P4, P1 ×P2, and P2 ×P4. Yield-contributing traits showed a strong positive correlation with root characteristics. Moreover, heatmap based on the agro-morphological attributes characterized the genotypes into distinct groups (Fig. 8). Using a color scale under drought stress, the heatmap analysis illustrated the relationship between the assessed genotypes and the studied traits. High values of measured agronomic characteristics were displayed in blue, while low values were shown in red. The genotypes P5, P3 ×P5, P2 ×P5, P2 ×P3, P3 ×P4, and P4 ×P5 exhibited greater values for all agronomic attributes corresponding to blue color in the heatmap. Otherwise, genotypes P1 ×P5, P2, P1 ×P4, P1 ×P2, and P2 ×P4 had the lowest values, expressed in red under water deficit conditions.