Next Article in Journal
A New Case Report of Traboulsi Syndrome: A Literature Review and Insights Into Genotype–Phenotype Correlations
Previous Article in Journal
Impact of NSD1 Alternative Transcripts in Actin Filament Formation and Cellular Division Pathways in Fibroblasts
Previous Article in Special Issue
Genome-Editing Products Line up for the Market: Will Europe Harvest the Benefits from Science and Innovation?
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Genes
Volume 15
Issue 9
10.3390/genes15091119
genes-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Screening Wheat Genotypes for Specific Genes Linked to Drought Tolerance

by
Ahmed Sallam
1,2,*,†,
Mohamed M. H. El-Defrawy
2,
Mona F. A. Dawood
3 and
Mostafa Hashem
2,†
1
Genebank Department, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Gatersleben, Germany
2
Department of Genetics, Faculty of Agriculture, Assiut University, Assiut 71526, Egypt
3
Department of Botany and Microbiology, Faculty of Science, Assiut University, Assiut 71516, Egypt
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Genes 2024, 15(9), 1119; https://doi.org/10.3390/genes15091119
Submission received: 10 July 2024 / Revised: 12 August 2024 / Accepted: 14 August 2024 / Published: 24 August 2024
(This article belongs to the Collection Feature Papers: 'Plant Genetics and Genomics' Section)
Browse Figures
Versions Notes

Abstract

:
Drought stress, which significantly affects growth and reduces grain yield, is one of the main problems for wheat crops. Producing promising drought-tolerant wheat cultivars with high yields is one of the main targets for wheat breeders. In this study, a total of seven drought-tolerant wheat genotypes were screened for the presence of 19 specific drought tolerance genes. The genotypes were tested under normal and drought conditions for two growing seasons. Four spike traits, namely, spike length (SPL), grain number per spike (GNPS), number of spikelets per spike (NSPS), and grain yield per spike (GYPS), were scored. The results revealed that drought stress decreased the SPL, GNPS, NSPS, and GYPS, with ranges ranging from 2.14 (NSPS) to 13.92% (GNPS) and from 2.40 (NSPS) to 11.09% (GYPS) in the first and second seasons, respectively. ANOVA revealed high genetic variation among the genotypes for each trait under each treatment. According to the drought tolerance indices, Omara 007 presented the highest level of drought tolerance (average of sum ranks = 3), whereas both Giza-36 genotypes presented the lowest level of drought tolerance (average of sum ranks = 4.8) among the genotypes tested. Among the 19 genes tested, 11 were polymorphic among the selected genotypes. Omara 007 and Omara 002 presented the greatest number of specific drought tolerance genes (nine) tested in this study, whereas Sohag-5, Giza-36, and PI469072 presented the lowest number of drought tolerance genes (four). The number of different genes between each pair of genotypes was calculated. Seven different genes were found between Omara 007 and Giza-36, Omara 007 and Sohag-5, and Omara 002 and PI469072. The results of this study may help to identify the best genotypes for crossing candidate genotypes, and not merely to genetically improve drought tolerance in wheat.

1. Introduction

Wheat (Triticum aestivum L.) is one of the most important cereal crops in the world. It plays a crucial role, providing more than 20% of the calories and protein required to feed more than 35% of the world’s population across 40 countrie [1]. In terms of food security, wheat ranks as the second-most important food crop in developing countries after rice, as approximately 80 million farmers rely on its production for their livelihood [2]. Global wheat production was 783.8 million tons in 2022 [3].
The wheat crop is sensitive to heat and drought stresses, mainly at the flowering and grain development stages, which negatively impact yield and grain quality (lower 1000-grain weight and changes in protein quality) [4,5]. Drought is a global problem and will become more prevalent due to climate change.
The impact of drought on wheat varies across different stages and regions of wheat production. Generally, wheat is highly vulnerable to drought, particularly during the flowering stage [6].
During the vegetative growth stage, water scarcity significantly affects plant physiology. Drought-induced stomatal closure reduces a plant’s ability to transpire and cool itself, leading to a significant increase in leaf temperature and a decrease in photosynthetic efficiency [7]. Furthermore, drought stress during the reproductive phase of wheat, particularly during flowering and grain filling, has severe implications for grain yield. A study by Fischer et al. [8] revealed that water deficit affected pollen viability, impaired fertilization, and decreased grain set, ultimately leading to lower grain yield. In addition to physiological effects, drought stress also triggers various molecular responses in wheat. For example, the expression of stress-responsive genes and the accumulation of stress-related proteins increase under drought conditions [9].
Breeding to improve drought tolerance in wheat is an important task for plant breeders and geneticists seeking to produce drought-tolerant wheat cultivars. Phenotyping selection may be misleading because of human errors and environmental effects.
A comprehensive understanding of the genetic and molecular mechanisms governing drought tolerance in wheat is fundamental for the eventual development of drought-tolerant varieties [10]. Therefore, marker-assisted selection has been widely used in the genetic improvement of drought tolerance and in accelerating the genetic improvement of target traits. Furthermore, identifying the genes underlying drought tolerance presents a major challenge to geneticists and molecular researchers.
Dehydration-responsive element-binding proteins (DREBs) represent a subset of specific molecular markers associated with genes responsive to drought [11]. This expansive family of DREB genes falls under the category of transcription factors (TFs) known to induce the expression of a substantial array of functional genes [12]. These functional genes play crucial roles in both the response to drought stress and the development of drought tolerance [13]. Additionally, many drought genes identified in wheat can be used to screen elite wheat genotypes. Therefore, investigating as many drought-tolerance genes in the tested wheat genotypes as possible will help in the selection of promising drought-tolerant wheat genotypes. The present study aimed to investigate yield traits in a set of seven highly drought-tolerant wheat genotypes and investigate the presence of specific drought tolerance genes in these genotypes for future molecular breeding programs to improve drought tolerance in wheat.

2. Materials and Methods

2.1. Plant Material

Seven drought-tolerant spring wheat genotypes were selected from the study of [14], in which a set of 198 spring wheat genotypes was tested under normal and drought conditions. Initially, the selection index of drought tolerance for each genotype was estimated in each growing season. The 20 drought-tolerant genotypes identified in each growing season were subsequently selected [14]. The genotypes in the tolerant group were compared between the two growing seasons [14]. As a result, seven genotypes were classified as drought tolerant in both growing seasons [14]. These seven genotypes represented three countries: Egypt (Giza-36, Omara002, GIMMIZA11, Omara007, and Sohag-5), Greece (PI469072), and Morocco (PI525241).

2.2. Experimental Layout

The seven genotypes were tested in two consecutive seasons, 2020/2021 and 2021/2022, under two conditions, normal (N) and drought (D), at the Experimental Field Station of the Department of Genetics, Assiut, Egypt (27°11′20.36″ N, 31°10′06.45″ E). The seven genotypes were among a tested population consisting of 198 genotypes which were evaluated by Hashem et al. [14] in two replications with randomized incomplete block design (RCBD). Each replication had 20 blocks with 10 genotypes/block. The soil at the experimental site was clay loam.
In both seasons and under both conditions, the seeds of each genotype were sown by hand in a single row measuring 1.5 m (one row/genotype). The final plant density was maintained at 15 seeds per row, with a spacing of 10 cm between seeds and 30 cm between rows. Under both conditions, the genotypes were sown on a regular wheat sowing date (20 November 2020 and 20 November 2021). Throughout the growing season, irrigation was applied every 21 days under normal conditions, with a total of seven irrigations in each growing season, whereas all the genotypes under drought conditions were irrigated twice throughout the growing season (the first irrigation was at sowing, and the second irrigation was at the booting stage). The location of the experimental field station is dry, and rainfall does not occur in this region.

2.3. Traits Measured

In both seasons and under each condition, ten main spikes were collected from ten plants/genotype. Four spike traits were scored for each genotype under both conditions: spike length (SPL; cm), grain number per spike (GNPS), number of spikelets per spike (NSPS), and grain yield per spike (GYPS, g). The reduction due to drought stress (RDD) for each trait in the two seasons was calculated as follows
RDD = (Xn − Xd)/Xn × 100
where Xn is the main average of the trait under normal conditions and Xd is the main average of the same trait under drought stress.

2.4. Selection of Genotypes Tolerant to Drought Stress

To select the best genotypes that tolerate drought stress, the seven best genotypes were identified on the basis of the iPASTIC [15] toolkit average of sum ranks (ASR) for each studied trait under each condition. The average ASR was subsequently estimated each year and over the two growing seasons for each genotype.

2.5. Statistical Analyses of the Phenotypic Data

The statistical analysis of the phenotypic data was performed with PLABSTAT software [16] via the following model:
Y ijk = μ + yi + tn +rj + gk + gyik + tgnk + ygtr(ijk) (error)
where Yijk is an observation of genotype k in year i, treatment n, replication j, and treatment t; μ is the general mean; gy is the genotype × year interaction; and gt is the genotype × treatment interaction. The error is year × treatment × replication × genotype interaction of genotype k within year i. Replications and years were considered random effects, whereas genotypes and treatment were considered fixed effects.

2.6. Molecular Screening for the Best Wheat Genotypes under Drought Stress

2.6.1. DNA Extraction

The DNA was extracted from leaves of the seven drought-tolerant genotypes at the Faculty of Agriculture, Assiut University, Egypt. Genomic DNA was isolated from 6-day-old seedlings via the Thermos Scientific gene JET plant genomic DNA purification mini kit protocol, with minor modifications [17]. The quantity and quality of the purified DNA were checked via a Nanodrop spectrophotometer (Fisher Scientific, Waltham, MA, USA). Finally, concentrated DNA was used to amplify drought-specific markers via an Eppendorf thermocycler (Eppendorf SE, Hamburg, Germany). The protocols for DNA and PCR reactions were previously used under drought stress by Ahmed et al. [18].

2.6.2. Drought-Specific Markers

A total of 19 specific markers were used for screening the best genotypes under drought stress. The primers for the DREB genes were obtained from Liu et al. [19]. The sequences of the other genes were obtained from EnsemblePlants (https://plants.ensembl.org/Triticum_aestivum/Info/Index), and the primers were subsequently designed via OligoPerfect Primer Designer (Thermo Fisher, Dreieich, Germany). The primer names, sequences, and corresponding annealing temperatures are presented in Supplementary Tables S1 and S2.
A 2X PCR Master Mix (Thermo Fisher, Germany) was used for the PCR experiments. The PCR tube containing the DNA sample had a total volume of 20 µL/reaction and was composed of 1.0 µL of genomic DNA, 10 µL of PCR master mixture, 0.2 µL of forward primer, 0.2 µL of reverse primer, and 8.6 µL of nuclease-free water. The reaction mixture was preheated at 94 °C for 5 min, followed by 35 cycles of 30 s denaturation at 94 °C, 30 s annealing at 52–67 °C (based on each primer’s annealing temperature), and elongation at 72 °C for 1 min.
After the last cycle, a final step was maintained at 72 °C for 5 min to allow complete extension of all amplified fragments.

2.6.3. Gel Electrophoresis

The amplification products were visualized on an agarose gel in 1× TAE buffer. The agarose gel was stained with SYBR Safe DNA gel stain for 20 min. The stained agarose gel was illuminated by a gel documentation system (Ultraviolet Product, Upland, CA, USA) to assess the DNA profiles.

3. Results

3.1. Effects of Drought Stress on the Studied Traits

Among the various agronomic traits, spike traits are the most important for improving wheat productivity. In the present study, drought stress decreased the scores of all the traits in the two seasons (Table 2, Figure 1a). In 2020, the GNPS had the greatest reduction due to drought stress (13.92%, from 91.31 to 78.6%), whereas the NSPS had the lowest reduction (2.14%, from 27.79 to 27.19%). In the 2021 growing season, the GYPS was the trait most strongly reduced by drought stress (from 4.7 to 4.18, 11.09%), whereas the NSPS had the lowest reduction (2.4%, from 27.79 to 27.12%).

3.2. Genetic Variation in Yield Traits under Drought Stress

The results of the combined analysis of variance (ANOVA) of the measured traits (Table 1) indicated that the differences among years were significant. The differences among treatments were not significant (normal vs. drought stress) for all yield traits. Highly significant genetic variation was found in all the traits among the genotypes. The G × Y interaction was significant for only the SPL and NSPS, whereas the G × T interaction was nonsignificant for all the traits.
The minimum, maximum, and mean values for all trait measurements in the two seasons for all the genotypes under normal and drought conditions are presented in Table 2. In both seasons, all the traits presented a lower average performance under drought stress than under normal conditions. The performance of each genotype for all traits under each condition and growing season is presented in Supplementary Table S3.
The phenotypic correlation for each trait between the two growing seasons under normal and drought stress conditions is presented in Table 3. A highly significant phenotypic correlation was found between the two years under each condition. Under the control, the correlation ranged from 0.72 ** (GYPS) to 0.98 ** (SPL), whereas it ranged from 0.83 ** (GNPS) to 0.99 ** (SPL) under drought stress.
The iPASTIC toolkit rank was used to determine the degree of tolerance for each genotype via various stress tolerance indices. The average ranks of the calculated indices for each genotype for each trait are presented in Table 4. In both growing seasons, the genotype with the greatest degree of drought tolerance differed by trait. The GIMMIZA 11, PI525241, and Sohag-5 genotypes were the most drought tolerant for SPL, NSPS, and GYPS, respectively. For the GYPS, Omara 007 was the most drought-tolerant cultivar in 2020/2021, and GIMMIZA 11 was the most drought-tolerant cultivar in 2021/2022. Interestingly, Omara 007 was the second-most drought-tolerant genotype SPL (in the two seasons), GNPS (in the two seasons), and GYPS (2021/2022). The average of all ranks across all traits was calculated for each genotype in each season (Figure 1b). Omara 007 was the most drought-tolerant genotype in 2020/2021, whereas GIMMIZA 11 was the most drought-tolerant genotype in 2021/2022. On average, during both seasons, Omara 007 presented the highest drought tolerance, whereas Giza-36 and PI469072 presented the lowest drought tolerance among the seven tested genotypes.

3.3. Gene Screening for the Drought-Tolerant Wheat Genotypes

The presence of 19 important drought tolerance genes was investigated in the seven drought-tolerant genotypes. Among the 19 genes, 11 were detected among the seven genotypes via PCR. The banding profile of seven wheat genotypes generated via the use of drought-specific genes is shown in Figure 2. The positions of these genes on the wheat chromosomes are presented in Figure 3. The genes were distributed in 7A (PEPR1), 1D (RHD1), 3B (NIM1 and BIN1), and 5D (EDS1 and DELTA-OAT). The protein encoded by this gene and its biological function related to drought tolerance in wheat are presented in Supplementary Table S2. All the genes were found to encode different proteins that play important roles in enhancing drought tolerance in wheat. BIN1 (3B) and PEPRI (7A) encode the protein kinase-like domain superfamily.
Four of the DREB alleles used in this study were detected in the tolerant genotypes. High polymorphism rates were detected among the seven genotypes in the 11 tested genes. Interestingly, Omara 007 and Omara 002 presented the greatest number of specific drought genes tested in this study, with nine genes, followed by GIMMIZA11, with seven genes (Figure 4a and Table 5). On the other hand, Sohag-5, Giza-36, and PI469072 presented the lowest number of drought genes. Notably, PREP1 and EDS1 were detected in all seven genotypes (Table 5), whereas DREB1-D was detected in only one genotype, namely, Omara 007 (Egypt). PI469072 (Greece) and PI525241 (Morocco) had four and five genes, respectively. Interestingly, the most drought-tolerant genotypes, namely, Omara 007 and Omara 002, presented the greatest number of specific drought tolerance genes (nine genes) (Figure 4).
The number of different genes among each pair of genotypes was estimated (Figure 4b). The number of different genes ranged from two to seven. Notably, seven different genes were found between Omara 007 and both Giza-36 and Sohag-5.

4. Discussion

4.1. Phenotypic and Genetic Variation in Drought Tolerance

Wheat yield under drought stress suffers from severe moisture deficit throughout its growth stages, from seedling to full maturity [20]. In general, drought stress has a negative effect on physiological and agronomic traits in wheat, regardless of the genotype and duration of stress application [21]. In this study, the genetic variation in spike traits among promising drought-tolerant genotypes was studied. These genotypes were selected from a panel of 198 highly diverse wheat genotypes [14]. Analysis of variance revealed highly significant genetic variation among the drought-tolerant genotypes, indicating that these genotypes are very useful as candidate parents for crossing to produce wheat cultivars with a relatively high degree of drought tolerance. Although the average number of genotypes associated with each trait was lower under drought stress than under normal conditions, the differences between the two treatments were not significant. This result indicated that drought stress had a nonsignificant effect on spike traits compared with those under normal conditions in drought-tolerant genotypes. Moreover, these results indicated that the selection for high drought tolerance among 198 genotypes evaluated by Hashem et al. [14] was accomplished. Additionally, the nonsignificant G × T effect supported the stability of the performance of the drought-tolerant genotypes under both conditions. The high phenotypic correlations for each trait between the two years indicated that the seven genotypes presented approximately the same performance under normal and drought stress conditions. Within the whole set of genotypes (198 genotypes), there were significant differences among the treatments (drought stress and normal conditions) [14]. Additionally, NSPS was the trait least affected by drought stress, followed by SPL, GNPS, and GYPS [14], as shown among the drought-tolerant genotypes. A reduction in spike traits due to drought stress has also been reported in previous studies [22] Moreover, various factors, such as pollen abortion, an increased number of sterile tillers, and a reduction in food reserves, have the potential to negatively influence yield performance under drought stress conditions [23].
Drought stress negatively affected spike length, the number of spikelets per spike, the grain number per spike, and the grain yield per spike across all the tested genotypes. Under drought conditions, a decreasing pattern of morphological yield contributes to drought stress [24]. Drought stress led to a reduction in the grain number and number of spikelets, which ultimately caused noticeably low yield productivity. Paknejad et al. [25] reported that the improvement in cultivar yield under drought stress resulted from a longer duration of grain filling, a greater chlorophyll content, or a combination of both.
A set of nine different stress susceptibility and tolerance indices was calculated for each trait to identify the most drought-tolerant genotypes. It has been reported that the use of multiple selection indices is a more precise tool for identifying genotypes with desirable traits in breeding programs, compared to single-trait selection [26]. In this regard, Omara 007, which was the average of all ranks in each index, was the most drought-tolerant genotype. However, the overall average values for all ranks for each genotype was very close to each other, ranging from 3 (Omara 007) to 4.8 (Giza-36). The Giza-36 genotype was found to have a strong ability to extract water at very deep depths in soils [27]. Additionally, the same genotype was previously reported to have an ability to tolerate soil lead and tin contents [28]. The PI 525241 genotype was found to be a salt-tolerant genotype at the germination stage [29]. However, no previous studies have examined these sugar signaling genotypes under drought stress in wheat. Moreover, given that these seven genotypes originated from Egypt (five), Greece (one), and Morocco (one), a certain level of genetic diversity among them is anticipated. Therefore, crossing between genotypes from Egypt and Greece or Morocco will be very useful for drought-susceptible cultivars with high tolerance to drought stress. Highly divergent genotypes should be selected and crossed in breeding programs to improve cultivar crops genetically for target traits (e.g., biotic and abiotic stress tolerance [30].

4.2. Molecular Screening for the Tested Wheat Genotypes in This Study

Studying the specific DNA molecular markers for target characteristics in the breeding program will help improve and accelerate the breeding program. DREB genes form an extensive gene family and are categorized as transcription factors (TFs) that induce the expression of numerous functional genes [12]. A total of 210 DREB genes are associated with abiotic stress tolerance [31]. DREB genes encode dehydration-responsive element-binding proteins. The DREB gene family plays a pivotal role in drought tolerance in wheat by regulating stress-responsive genes. The activation of DREB genes by drought stress leads to the expression of stress-responsive genes that are involved in various protective mechanisms, such as osmotic adjustment, detoxification of reactive oxygen species (ROS), and maintenance of cellular structures [32]. In this study, we used DREB alleles that were previously reported by [19]. Ahmed et al. [18] used the same genes to screen drought-tolerant genotypes evaluated at the seedling stage in wheat. In this study, non-drought-tolerant genotypes presented all the DREB alleles tested. Omara 002 and Omara 007 had only three and two DREB alleles, respectively. Although the DREB gene family plays a critical role in drought tolerance, as drought tolerance is a polygenic trait controlled by many genes, it is worth investigating other important drought tolerance genes [30,33]. A set of seven drought genes were polymorphic among the drought-tolerant genotypes. The BINI and PEPRI genes encode a protein kinase-like domain superfamily. This protein plays a role in the plant response to drought stress. SnRK2 protein kinases regulate ABA signaling under drought stress. Additionally, SnRK2 was found to be associated with yield traits, especially 1000-kernel weight, in wheat [30]. The PERPI gene was found in all the genotypes, whereas BINI was found in only two. The NIM1 gene encodes an Ankyrin repeat protein, which is essential for cell growth and response to environmental stresses. High expression of this protein was found to be associated with a high survival rate under drought stress [34]. RHD2 encodes the EF-hand domain pair. The EF-hand motif was found to be included in Ca2+-binding proteins that are important in the plant response to drought stress and plant development during abiotic stress [35]. The DELTA-OAT gene encodes a pyridoxal phosphate-dependent transferase that is involved in plant proline biosynthesis. Additionally, these genes are highly expressed under drought stress, indicating their vital role in alleviating the effects of drought stress in wheat plants [36]. OBF 5 encodes a basic-leucine zipper (bZIP). The bZIP transcription factors are involved in various biological processes, such as flower and seed development, seed germination, light signaling, and hormone and sugar signaling [37]. Moreover, these proteins are highly expressed under abiotic stresses, such as drought stress [37]. The α/β hydrolase (EDS1 gene) was found to be highly expressed 6 h after drought stress in wheat [38].
The greatest number of gene alleles was present in both the Egyptian genotypes Omara 007 (nine genes) and Omara 002 (nine genes), whereas the lowest number (4 genes) of these genes was present in genotypes Giza-36, Sohag-5, and PI469072. Although Omara 002 had nine genes, it was ranked after Giza GIMMIZA 11, which had only four alleles. This may be because GIMMIZA 11 may contain other drought tolerance genes that were not tested in this study. In addition, some genes related to drought stress may have major or minor effects on drought tolerance. Therefore, compared with GIMMIZA 11, Omara 002 could have some minor genes. Given that these genes were, as described above, reported to be associated with drought tolerance in this study, the associations between these genes and yield traits in wheat under drought stress should be investigated. This can be investigated by genotyping a wheat population (more than 100 individuals) with these genes and phenotyping the same panel for all yield traits under drought stress. Thus, association analysis should be conducted to identify the effects (major or minor) of these genes on yield traits under drought stress.
The number of different genes among the drought-tolerant genotypes provides useful information on the diversity of drought tolerance genes. Omara 007 presented the greatest number of different genes, compared to Giza-36 and Sohag-5. Moreover, Omara 002 was found to have seven different genes relative to PI469072. It is expected that crossing these genotypes (Omara 002 and PI467072) may lead to the production of wheat cultivars with relatively high levels of drought tolerance. The cross between PI469072 and Omara 002 may be fruitful because it could not only improve drought tolerance, but also increase the genetic diversity among wheat genotypes grown in Egypt.
In conclusion, the identification and validation of novel primers for these genes are highly beneficial for wheat breeding and genetic programs. Eleven specific primers were polymorphic among the seven drought-tolerant genotypes. The high polymorphism and diversity observed among drought-tolerant genotypes suggest variation in the number of drought-specific gene haplotypes among these genotypes. The results also revealed that, compared with the Greece and Morocco genotypes, the Egyptian genotypes presented greater drought tolerance; therefore, they probably included drought genes other than those described in this study. These seven genotypes can be used for crossing in order to genetically improve drought tolerance at the adult stage in spring wheat.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/genes15091119/s1, Table S1: Primer codes, sequences of the forward and reverse primers, and annealing temperature used in this study; Table S2: List of primers used for PCR analysis and associated proteins; Table S3: The means of studied traits under normal and drought conditions in the two seasons.

Author Contributions

A.S.: conceptualization, methodology, validation, investigation, writing—review and editing, supervision; M.H.: methodology, data curation, validation, investigation, original draft preparation; M.F.A.D.: supervision; M.M.H.E.-D.: supervision, A.S.: resources, writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Science and Technology Development Fund (STDF) under Project ID 39444, Egypt. Costs for open-access publishing were partially funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, grant 491250510).

Data Availability Statement

The sequence data presented in this study are not publicly available due to some ongoing projects on the same plant materials. Other data is presented in the Supplementary Files.

Acknowledgments

The authors would like to thank Andreas Börner (Leibniz Institute of Plant Genetics and Crop Plant Research), for his kind support of this work. The authors wish to thank Ameer Effat, and Asmaa Ali, Department of Genetics, Faculty of Agriculture, Assiut University, for their support of this work.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

NNormal conditions
DDrought conditions
SPLSpike length
GNPSGrain number per spike
NSPSNumber of spikelets per spike
GYPSGrain yield per spike
RDDReduction due to drought effect
TFsTranscription factors
RCBDRandomized complete block design
ASRAverage of sum ranks

References

  1. Medhat, A.; Al-Naggar, M.; Abd, M.; Abd El-Shafi, E.-M.; Helmy El-Shal, M.; Anany, A.H. Evaluation of Egyptian Wheat Landraces (Triticum aestivum L.) For Drought Tolerance, Agronomic, Grain Yield and Quality Traits. Plant Arch. 2020, 20, 3487–3504. [Google Scholar]
  2. Challinor, A.J.; Watson, J.; Lobell, D.B.; Howden, S.M.; Smith, D.R.; Chhetri, N. A Meta-Analysis of Crop Yield under Climate Change and Adaptation. Nat. Clim. Change 2014, 4, 287–291. [Google Scholar] [CrossRef]
  3. World Food and Agriculture—Statistical Yearbook 2022; FAO: Rome, Italy, 2022.
  4. Kulkarni, M.; Soolanayakanahally, R.; Ogawa, S.; Uga, Y.; Selvaraj, M.G.; Kagale, S. Drought Response in Wheat: Key Genes and Regulatory Mechanisms Controlling Root System Architecture and Transpiration Efficiency. Front. Chem. 2017, 5, 106. [Google Scholar] [CrossRef]
  5. Eltaher, S.; Sallam, A.; Emara, H.A.; Nower, A.A.; Salem, K.F.M.; Börner, A.; Baenziger, P.S.; Mourad, A.M.I. Genome-Wide Association Mapping Revealed SNP Alleles Associated with Spike Traits in Wheat. Agronomy 2022, 12, 1469. [Google Scholar] [CrossRef]
  6. Sallam, A.; Alqudah, A.M.; Dawood, M.F.A.; Baenziger, P.S.; Börner, A. Drought Stress Tolerance in Wheat and Barley: Advances in Physiology, Breeding and Genetics Research. Int. J. Mol. Sci. 2019, 20, 3137. [Google Scholar] [CrossRef]
  7. Flexas, J.; Barón, M.; Bota, J.; Ducruet, J.M.; Gallé, A.; Galmés, J.; Jiménez, M.; Pou, A.; Ribas-Carbó, M.; Sajnani, C.; et al. Photosynthesis Limitations during Water Stress Acclimation and Recovery in the Drought-Adapted Vitis Hybrid Richter-110 (V. berlandieri × V. rupestris). J. Exp. Bot. 2009, 60, 2361–2377. [Google Scholar] [CrossRef]
  8. Fischer, R.A. Wheat Physiology: A Review of Recent Developments. Crop Pasture Sci. 2010, 62, 95–114. [Google Scholar] [CrossRef]
  9. Aprile, A.; Havlickova, L.; Panna, R.; Marè, C.; Borrelli, G.M.; Marone, D.; Perrotta, C.; Rampino, P.; De Bellis, L.; Curn, V.; et al. Different Stress Responsive Strategies to Drought and Heat in Two Durum Wheat Cultivars with Contrasting Water Use Efficiency. BMC Genom. 2013, 14, 821. [Google Scholar] [CrossRef]
  10. Thabet, S.G.; Moursi, Y.S.; Karam, M.A.; Graner, A.; Alqudah, A.M. Genetic Basis of Drought Tolerance during Seed Germination in Barley. PLoS ONE 2018, 13, e0206682. [Google Scholar] [CrossRef]
  11. Rasheed, A.; Wen, W.; Gao, F.; Zhai, S.; Jin, H.; Liu, J.; Guo, Q.; Zhang, Y.; Dreisigacker, S.; Xia, X.; et al. Development and Validation of KASP Assays for Genes Underpinning Key Economic Traits in Bread Wheat. Theor. Appl. Genet. 2016, 129, 1843–1860. [Google Scholar] [CrossRef]
  12. Agarwal, P.K.; Agarwal, P.; Reddy, M.K.; Sopory, S.K. Role of DREB Transcription Factors in Abiotic and Biotic Stress Tolerance in Plants. Plant Cell Rep. 2006, 25, 1263–1274. [Google Scholar] [CrossRef] [PubMed]
  13. Egawa, C.; Kobayashi, F.; Ishibashi, M.; Nakamura, T.; Nakamura, C.; Takumi, S. Differential Regulation of Transcript Accumulation and Alternative Splicing of a DREB2 Homolog under Abiotic Stress Conditions in Common Wheat. Genes Genet. Syst. 2006, 81, 77–91. [Google Scholar] [CrossRef] [PubMed]
  14. Abdalrahman, M.; EL-defrawy, M.M.; Dawood, M.; Börner, A. Genetic Variation in Peduncle Traits and Their Association with Spike Traits under Normal and Drought Conditions in Spring Wheat. In Proceedings of the Cereal Molecular Breeding and Genetics—International Symposium, Assuit, Egypt, 9 September 2022. [Google Scholar]
  15. Pour-Aboughadareh, A.; Yousefian, M.; Moradkhani, H.; Moghaddam Vahed, M.; Poczai, P.; Siddique, K.H.M. IPASTIC: An Online Toolkit to Estimate Plant Abiotic Stress Indices. Appl. Plant Sci. 2019, 7, e11278. [Google Scholar] [CrossRef]
  16. Utz, H.F. PLABSTAT A Computer Program for Statistical Analysis of Plant Breeding Experiments Version 3A-Pre of 2005-08-16; Institute of Plant Breeding, Seed Science and Population Genetics, University of Hohenheim: Stuttgart, Germany, 1986. [Google Scholar]
  17. Thermo Scientific. GeneJET Plant Genomic DNA Purification Mini Kit #K0791, #K0792; Thermo Scientific: Waltham, MA, USA, 2016. [Google Scholar]
  18. Ahmed, A.A.M.; Dawood, M.F.A.; Elfarash, A.; Mohamed, E.A.; Hussein, M.Y.; Börner, A.; Sallam, A. Genetic and Morpho-Physiological Analyses of the Tolerance and Recovery Mechanisms in Seedling Stage Spring Wheat under Drought Stress. Front. Genet. 2022, 13, 1010272. [Google Scholar] [CrossRef] [PubMed]
  19. Liu, M.; Wang, Z.; Xiao, H.; Yang, Y. Characterization of TaDREB1 in Wheat Genotypes with Different Seed Germination under Osmotic Stress. Hereditas 2018, 155, 26. [Google Scholar] [CrossRef] [PubMed]
  20. Bilal, M.; Iqbal, I.; Mehmood Rana, R.; Ur Rehman, S.; Haidery, Q.; Ahmad, F.; Ijaz, A.; Muhammad Imran Umar, H. A Comprehensive Review of Effects of Water Stress and Tolerance in Wheat (Triticuma estivum L.). Trop. Plant Res. 2015, 3, 271–275. [Google Scholar]
  21. Qaseem, M.F.; Qureshi, R.; Shaheen, H. Effects of Pre-Anthesis Drought, Heat and Their Combination on the Growth, Yield and Physiology of Diverse Wheat (Triticum aestivum L.) Genotypes Varying in Sensitivity to Heat and Drought Stress. Sci. Rep. 2019, 9, 6955. [Google Scholar] [CrossRef]
  22. Liu, H.; Searle, I.R.; Mather, D.E.; Able, A.J.; Able, J.A. Morphological, Physiological and Yield Responses of Durum Wheat to Pre-Anthesis Water-Deficit Stress Are Genotype Dependent. Crop Pasture Sci. 2015, 66, 1024–1038. [Google Scholar] [CrossRef]
  23. Barnabás, B.; Jäger, K.; Fehér, A. The Effect of Drought and Heat Stress on Reproductive Processes in Cereals. Plant Cell Environ. 2008, 31, 11–38. [Google Scholar] [CrossRef]
  24. Kiliç, H.; Yağbasanlar, T. The Effect of Drought Stress on Grain Yield, Yield Components and Some Quality Traits of Durum Wheat (Triticum turgidum ssp. durum) Cultivars. Not. Bot. Horti Agrobot. Cluj-Napoca 2010, 38, 164–170. [Google Scholar] [CrossRef]
  25. Paknejad, F.; Nasri, M.; Moghadam, H.T.; Zahedi, H.; Alahmadi, M.J. Effects of Drought Stress on Chlorophyll Fluorescence Parameters, Chlorophyll Content and Grain Yield of Wheat Cultivars. J. Biol. Sci. 2007, 7, 841–847. [Google Scholar] [CrossRef]
  26. Sallam, A.; Mourad, A.M.I.; Hussain, W.; Stephen Baenziger, P. Genetic Variation in Drought Tolerance at Seedling Stage and Grain Yield in Low Rainfall Environments in Wheat (Triticum aestivum L.). Euphytica 2018, 214, 169. [Google Scholar] [CrossRef]
  27. Reynolds, M.P.; Pierre, C.S.; Saad, A.S.I.; Vargas, M.; Condon, A.G. Evaluating Potential Genetic Gains in Wheat Associated with Stress-Adaptive Trait Expression in Elite Genetic Resources under Drought and Heat Stress. Crop Sci. 2007, 47, S-172–S-189. [Google Scholar] [CrossRef]
  28. Mourad, A.M.I.; Amin, A.E.-E.A.Z.; Dawood, M.F.A. Genetic Variation in Kernel Traits under Lead and Tin Stresses in Spring Wheat Diverse Collection. Environ. Exp. Bot. 2021, 192, 104646. [Google Scholar] [CrossRef]
  29. Hasseb, N.M.; Sallam, A.; Karam, M.A.; Gao, L.; Wang, R.R.C.; Moursi, Y.S. High-LD SNP Markers Exhibiting Pleiotropic Effects on Salt Tolerance at Germination and Seedlings Stages in Spring Wheat. Plant Mol. Biol. 2022, 108, 585–603. [Google Scholar] [CrossRef]
  30. Sallam, A.; Awadalla, R.A.; Elshamy, M.M.; Börner, A.; Heikal, Y.M. Genome-Wide Analysis for Root and Leaf Architecture Traits Associated with Drought Tolerance at the Seedling Stage in a Highly Ecologically Diverse Wheat Population. Comput. Struct. Biotechnol. J. 2024, 23, 870–882. [Google Scholar] [CrossRef] [PubMed]
  31. Niu, X.; Luo, T.; Zhao, H.; Su, Y.; Ji, W.; Li, H. Identification of Wheat DREB Genes and Functional Characterization of TaDREB3 in Response to Abiotic Stresses. Gene 2020, 740, 144514. [Google Scholar] [CrossRef]
  32. Huang, X.; Song, X.; Chen, R.; Zhang, B.; Li, C.; Liang, Y.; Qiu, L.; Fan, Y.; Zhou, Z.; Zhou, H.; et al. Genome-Wide Analysis of the DREB Subfamily in Saccharum spontaneum Reveals Their Functional Divergence During Cold and Drought Stresses. Front. Genet. 2020, 10, 1326. [Google Scholar] [CrossRef]
  33. Eltaher, S.; Hashem, M.; Ahmed, A.A.M.; Baenziger, P.S.; Börner, A.; Sallam, A. Effectiveness of TaDreb-B1 and 1-FEH W3 KASP Markers in Spring and Winter Wheat Populations for Marker-Assisted Selection to Improve Drought Tolerance. Int. J. Mol. Sci. 2023, 24, 8986. [Google Scholar] [CrossRef]
  34. Zhao, J.-Y.; Lu, Z.-W.; Sun, Y.; Fang, Z.-W.; Chen, J.; Zhou, Y.-B.; Chen, M.; Ma, Y.-Z.; Xu, Z.-S.; Min, D.-H. The Ankyrin-Repeat Gene GmANK114 Confers Drought and Salt Tolerance in Arabidopsis and Soybean. Front. Plant Sci. 2020, 11, 584167. [Google Scholar] [CrossRef]
  35. Kaur, A.; Madhu; Upadhyay, S.K. EF-Hand Domain-Containing Proteins: Diversity and Role in Plants. In Cation Transporters in Plants; Elsevier: Amsterdam, The Netherlands, 2022; pp. 185–203. [Google Scholar]
  36. Anwar, A.; Wang, K.; Wang, J.; Shi, L.; Du, L.; Ye, X. Expression of Arabidopsis Ornithine Aminotransferase (AtOAT) Encoded Gene Enhances Multiple Abiotic Stress Tolerances in Wheat. Plant Cell Rep. 2021, 40, 1155–1170. [Google Scholar] [CrossRef] [PubMed]
  37. Sornaraj, P.; Luang, S.; Lopato, S.; Hrmova, M. Basic Leucine Zipper (BZIP) Transcription Factors Involved in Abiotic Stresses: A Molecular Model of a Wheat BZIP Factor and Implications of Its Structure in Function. Biochim. Biophys. Acta (BBA)—General. Subj. 2016, 1860, 46–56. [Google Scholar] [CrossRef] [PubMed]
  38. Liu, Z.; Xin, M.; Qin, J.; Peng, H.; Ni, Z.; Yao, Y.; Sun, Q. Temporal Transcriptome Profiling Reveals Expression Partitioning of Homeologous Genes Contributing to Heat and Drought Acclimation in Wheat (Triticum aestivum L.). BMC Plant Biol. 2015, 15, 152. [Google Scholar] [CrossRef] [PubMed]
Genes 15 01119 g001
Figure 1. The reduction due to drought of studied traits in both seasons (a), and average of sum ranks (ASR) of all stress indices for each genotype in two seasons (b). SPL: spike length, NSPS: number of spikes per spike, GNPS: grain number per spike, GYPS: grain yield per spike.
Figure 1. The reduction due to drought of studied traits in both seasons (a), and average of sum ranks (ASR) of all stress indices for each genotype in two seasons (b). SPL: spike length, NSPS: number of spikes per spike, GNPS: grain number per spike, GYPS: grain yield per spike.
Genes 15 01119 g001
Genes 15 01119 g002aGenes 15 01119 g002b
Figure 2. Agarose gel electrophoresis of DREB genes used in this study. Names of genotypes are supplied in Supplementary Table S1.
Figure 2. Agarose gel electrophoresis of DREB genes used in this study. Names of genotypes are supplied in Supplementary Table S1.
Genes 15 01119 g002aGenes 15 01119 g002b
Genes 15 01119 g003
Figure 3. The position of the detected genes among the seven genotypes by PCR on wheat chromosomes.
Figure 3. The position of the detected genes among the seven genotypes by PCR on wheat chromosomes.
Genes 15 01119 g003
Genes 15 01119 g004
Figure 4. Number of genes and the average of ASR (two growing seasons) for each genotype (a) and the numbers of different genes found between genotypes (b).
Figure 4. Number of genes and the average of ASR (two growing seasons) for each genotype (a) and the numbers of different genes found between genotypes (b).
Genes 15 01119 g004
Table 1. Analysis of variance for scored traits under both conditions in two seasons (2020/2021 and 2021/2022).
Table 1. Analysis of variance for scored traits under both conditions in two seasons (2020/2021 and 2021/2022).
SourceDFSPLNSPSGNPSGYPS
Y121.875 **5.59 *1739.85 **3.21 *
T10.0960.018251.070.23
R112.99 *2.162420.13 **2.11 *
G6243.93 **45.64 **1570.55 **3.14 **
GY67.04 **2.52 *145.80.182
GT61.111.98120.250.143
GRTY340.48102.211.111.77
Year (Y), treatment (T), replication (R), and genotype (G). *, ** Significant at the 0.05 and 0.01 levels of probability, respectively. DF: degree of freedom, SPL: spike length, NSPS: number of spikelets/spike, GNPS: grain number/spike, GYPS: grain yield per spike.
Table 2. Minimum (Min), maximum (Max), mean, and combining correlation of each trait scored in the study under normal (N) and drought stress conditions (D) in the two seasons.
Table 2. Minimum (Min), maximum (Max), mean, and combining correlation of each trait scored in the study under normal (N) and drought stress conditions (D) in the two seasons.
ItemYearNormalDrought
SPLNSPSGNPSGYPSSPLNSPSGNPSGYPS
Minimum2020/20217.6723693.077.672356.333.37
2021/20227.6721.67603.45825582.99
Maximum2020/20212931.67119.336.5620.6730.33100.675.46
2021/202226.6733.671497.7720.6731110.675.48
Mean2020/202114.1727.7987.834.713.0227.1278.254.18
2021/202214.1927.7991.314.7812.8327.1978.64.35
SPL: spike length, NSPS: number of spikelets/spike, GNPS: grain number/spike, GYPS: grain yield per spike.
Table 3. Correlations between morphological traits under drought stress at the adult stages.
Table 3. Correlations between morphological traits under drought stress at the adult stages.
ControlDrought
SPLNSPSNSPSGYPSSPLNSPSNSPSGYPS
0.98 **0.92 **0.85 **0.72 **0.99 **0.89 **0.83 **0.98 **
** Significant at the 0.01 level of probability. SPL: spike length, NSPS: number of spikelets/spike, GNPS: grain number/spike, GYPS: grain yield per spike.
Table 4. The average rank of the calculated indices for each genotype in each trait.
Table 4. The average rank of the calculated indices for each genotype in each trait.
Season2020/20212021/2022Average
GenotypeSPLNSPSGNPSGYPSSPLNSPSGNPSGYPS
Giza-3643.86.544.45.86.13.84.8
Omara 0023.92.75.75.44.22.85.45.94.5
GIMMIZA1124.73.84.22.34.231.63.225
Omara 0073.44.22.41.43.43.42.73.13
Sohag-53.86.41.425.14.41.62.93.45
PI4690725.544.55.43.84.44.85.44.725
PI5252415.423.75.64.82.74.45.34.2375
SPL: spike length, NSPS: number of spikelets/spike, GNPS: grain number/spike, GYPS: grain yield per spike.
Table 5. The total number of drought genes present in each of the seven drought-tolerant genotypes.
Table 5. The total number of drought genes present in each of the seven drought-tolerant genotypes.
No. of GenotypesGenotypeCountryBIN1NIM1RHD2OATOBF5PEPR1EDS1DREB1-A1DREB1-A2 DREB1-D DREB1-D2Total
1Giza-36Egypt010001101004
2Omara 002Egypt011111111019
3GIMMIZA11Egypt011011110017
4Omara 007Egypt111111100119
5Sohag-5Egypt010001110004
6PI469072Greece110001100004
7PI525241Morocco001011100015
Total 26424773214
Where, the positive sign (1) indicates the presence of the gene, while the negative sign (0) indicates the absence of the gene or indicates that the genotype does not contain this gene.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Sallam, A.; El-Defrawy, M.M.H.; Dawood, M.F.A.; Hashem, M. Screening Wheat Genotypes for Specific Genes Linked to Drought Tolerance. Genes 2024, 15, 1119. https://doi.org/10.3390/genes15091119

AMA Style

Sallam A, El-Defrawy MMH, Dawood MFA, Hashem M. Screening Wheat Genotypes for Specific Genes Linked to Drought Tolerance. Genes. 2024; 15(9):1119. https://doi.org/10.3390/genes15091119

Chicago/Turabian Style

Sallam, Ahmed, Mohamed M. H. El-Defrawy, Mona F. A. Dawood, and Mostafa Hashem. 2024. "Screening Wheat Genotypes for Specific Genes Linked to Drought Tolerance" Genes 15, no. 9: 1119. https://doi.org/10.3390/genes15091119

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop