Genetic analyses and prediction for lodging­related traits in a diverse Iranian hexaploid wheat collection.

Lodging is one of the most important limiting environmental factors for achieving the maximum yield and quality of grains in cereals, including wheat. However, little is known about the genetic foundation underlying lodging resistance (LR) in wheat. In this study, 208 landraces and 90 cultivars were phenotyped in two cropping seasons (2018-2019 and 2019-2020) for 19 LR-related traits. A genome-wide association study (GWAS) and genomics prediction were carried out to dissect the genomic regions of LR. The number of significant marker pairs (MPs) was highest for genome B in both landraces (427,017) and cultivars (37,359). The strongest linkage disequilibrium (LD) between marker pairs was found on chromosome 4A (0.318). For stem lodging-related traits, 465, 497, and 478 marker-trait associations (MTAs) and 45 candidate genes were identified in year 1, year 2, and pooled. Gene ontology exhibited genomic region on Chr. 2B, 6B, and 7B control lodging. Most of these genes have key roles in defense response, calcium ion transmembrane transport, carbohydrate metabolic process, nitrogen compound metabolic process, and some genes harbor unknown functions that, all together may respond to lodging as a complex network. The module associated with starch and sucrose biosynthesis was highlighted. Regarding genomic prediction, the GBLUP model performed better than BRR and RRBLUP. This suggests that GBLUP would be a good tool for wheat genome selection. As a result of these findings, it has been possible to identify pivotal QTLs and genes that could be used to improve stem lodging resistance in Triticum aestivum L.

Genetic diversity, linkage disequilibrium, and population structure of tetraploid wheat landraces originating from Europe and Asia.

BACKGROUND: Durum wheat is one of the most important crops, especially in the Mediterranean region. Insight into the genetic diversity of germplasm can improve the breeding program management in various traits. This study was done using single nucleotide polymorphisms (SNP) markers to characterize the genetic distinctiveness and differentiation of tetraploid wheat landraces collected from nine European and Asian countries. A sum of 23,334 polymorphic SNPs was detected in 126 tetraploid wheat landraces in relation to the reference genome. RESULTS: The number of identified SNPs was 11,613 and 11,721 in A and B genomes, respectively. The highest and lowest diversity was on 6B and 6 A chromosomes, respectively. Structure analysis classified the landraces into two distinct subpopulations (K = 2). Evaluating the principal coordinate analysis (PCoA) and weighted pair-group method using arithmetic averages (WPGMA) clustering results demonstrated that landraces (99.2%) are categorized into one of the two chief subpopulations. Therefore, the grouping pattern did not clearly show the presence of a clear pattern of relationships between genetic diversity and their geographical derivation. Part of this result could be due to the historical exchange between different germplasms. Although the result did not separate landraces based on their region of origin, the landraces collected from Iran were classified into the same group and cluster. Analysis of molecular variance (AMOVA) also confirmed the results of population structure. Finally, Durum wheat landraces in some countries, including Turkey, Russia, Ukraine, and Afghanistan, were highly diverse, while others, including Iran and China, were low-diversity. CONCLUSION: The recent study concluded that the 126 tetraploid wheat genotypes and their GBS-SNP markers are very appropriate for quantitative trait loci (QTLs) mapping and genome-wide association studies (GWAS). The core collection comprises two distinct subpopulations. Subpopulation II genotypes are the most diverse genotypes, and if they possess desired traits, they may be used in future breeding programs. The degree of diversity in the landraces of countries can provide the ground for the improvement of new cultivars with international cooperation. linkage disequilibrium (LD) hotspot distribution across the genome was investigated, which provides useful information about the genomic regions that contain intriguing genes.

Screening of 20 species from Lamiaceae family based on phytochemical analysis, antioxidant activity and HPLC profiling.

The Lamiaceae family encompasses numerous species highly valued for their applications in medicine, food, and cosmetics. In order to screen the Lamiaceae family and discover new sources of phytochemicals and antioxidants, we comprehensively evaluated 20 species from this family, including Phlomis herba-venti, P. tuberosa, P. olivieri, P. kurdica, Nepeta sp., N. cataria, N. saccharata, Stachys sp., S. inflata, Scutellaria albida, Marrubium parviflora, Mentha pulegium, Thymus kotschyanus, Lamium album, Salvia officinalis, S. multicaulis, S. macrochlamys, S. candidissima, S. verticillata, and S. nemorosa. The aerial parts of these species were analyzed to determine their total phenolic (TPC) and flavonoid (TFC) contents, total tannin content (TTC), ascorbic acid content (AAC), antioxidant capacity (assessed by FRAP and DPPH assays), and polyphenolic components (by HPLC). The phytochemical compounds and antioxidant properties varied widely among different species. The highest concentrations of TPC (70.93 mg GAE/g DW), TFC (17.89 mg Que/g DW), TTC (6.49 mg TAE/100 g), and AAC (1.15 mg AA/g DW), as well as the greatest antioxidant activity, were observed in different Salvia species. Additionally, chlorogenic and rosmarinic acids were the primary phenolic compounds identified in the extracts from the investigated Lamiaceae family. According to Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA), three groups of species were identified, characterized by variations in phytochemical composition and antioxidant capacity. The results obtained can provide new natural sources of phytochemicals and antioxidant agents, particularly from Salvia species, for the advancement of new products in the food, agricultural, cosmetics and health industries.

Identification and estimation of lodging in bread wheat genotypes using machine learning predictive algorithms.

BACKGROUND: Lodging or stem bending decreases wheat yield quality and quantity. Thus, the traits reflected in early lodging wheat are helpful for early monitoring to some extent. In order to identify the superior genotypes and compare multiple linear regression (MLR) with support vector regression (SVR), artificial neural network (ANN), and random forest regression (RF) for predicting lodging in Iranian wheat accessions, a total of 228 wheat accessions were cultivated under field conditions in an alpha-lattice experiment, randomized incomplete block design, with two replications in two cropping seasons (2018-2019 and 2019-2020). To measure traits, a total of 20 plants were isolated from each plot and were measured using image processing. RESULTS: The lodging score index (LS) had the highest positive correlation with plant height (r = 0.78**), Number of nodes (r = 0.71**), and internode length 1 (r = 0.70**). Genotypes were classified into four groups based on heat map output. The most lodging-resistant genotypes showed a lodging index of zero or close to zero. The findings revealed that the RF algorithm provided a more accurate estimate (R2 = 0.887 and RMSE = 0.091 for training data and R2 = 0.768 and RMSE = 0.124 for testing data) of wheat lodging than the ANN and SVR algorithms, and its robustness was as good as ANN but better than SVR. CONCLUSION: Overall, it seems that the RF model can provide a helpful predictive and exploratory tool to estimate wheat lodging in the field. This work can contribute to the adoption of managerial approaches for precise and non-destructive monitoring of lodging.

Analysis of genetic diversity and genome-wide association study for drought tolerance related traits in Iranian bread wheat.

BACKGROUND: Drought is most likely the most significant abiotic stress affecting wheat yield. The discovery of drought-tolerant genotypes is a promising strategy for dealing with the world's rapidly diminishing water resources and growing population. A genome-wide association study (GWAS) was conducted on 298 Iranian bread wheat landraces and cultivars to investigate the genetic basis of yield, yield components, and drought tolerance indices in two cropping seasons (2018-2019 and 2019-2020) under rainfed and well-watered environments. RESULTS: A heatmap display of hierarchical clustering divided cultivars and landraces into four categories, with high-yielding and drought-tolerant genotypes clustering in the same group. The results of the principal component analysis (PCA) demonstrated that selecting genotypes based on the mean productivity (MP), geometric mean productivity (GMP), harmonic mean (HM), and stress tolerance index (STI) can help achieve high-yield genotypes in the environment. Genome B had the highest number of significant marker pairs in linkage disequilibrium (LD) for both landraces (427,017) and cultivars (370,359). Similar to cultivars, marker pairs on chromosome 4A represented the strongest LD (r2 = 0.32). However, the genomes D, A, and B have the highest LD, respectively. The single-locus mixed linear model (MLM) and multi-locus random-SNP-effect mixed linear model (mrMLM) identified 1711 and 1254 significant marker-trait association (MTAs) (-log10 P > 3) for all traits, respectively. A total of 874 common quantitative trait nucleotides (QTNs) were simultaneously discovered by both MLM and mrMLM methods. Gene ontology revealed that 11, 18, 6, and 11 MTAs were found in protein-coding regions (PCRs) for spike weight (SW), thousand kernel weight (TKW), grain number per spike (GN), and grain yield (GY), respectively. CONCLUSION: The results identified rich regions of quantitative trait loci (QTL) on Ch. 4A and 5A suggest that these chromosomes are important for drought tolerance and could be used in wheat breeding programs. Furthermore, the findings indicated that landraces studied in Iranian bread wheat germplasm possess valuable alleles, that are responsive to water-limited conditions. This GWAS experiment is one of the few types of research conducted on drought tolerance that can be exploited in the genome-mediated development of novel varieties of wheat.

Identification of novel putative alleles related to important agronomic traits of wheat using robust strategies in GWAS.

Principal component analysis (PCA) is widely used in various genetics studies. In this study, the role of classical PCA (cPCA) and robust PCA (rPCA) was evaluated explicitly in genome-wide association studies (GWAS). We evaluated 294 wheat genotypes under well-watered and rain-fed, focusing on spike traits. First, we showed that some phenotypic and genotypic observations could be outliers based on cPCA and different rPCA algorithms (Proj, Grid, Hubert, and Locantore). Hubert's method provided a better approach to identifying outliers, which helped to understand the nature of these samples. These outliers led to the deviation of the heritability of traits from the actual value. Then, we performed GWAS with 36,000 single nucleotide polymorphisms (SNPs) based on the traditional approach and two robust strategies. In the conventional approach and using the first three components of cPCA as population structure, 184 and 139 marker-trait associations (MTAs) were identified for five traits in well-watered and rain-fed environments, respectively. In the first robust strategy and when rPCA was used as population structure in GWAS, we observed that the Hubert and Grid methods identified new MTAs, especially for yield and spike weight on chromosomes 7A and 6B. In the second strategy, we followed the classical and robust principal component-based GWAS, where the first two PCs obtained from phenotypic variables were used instead of traits. In the recent strategy, despite the similarity between the methods, some new MTAs were identified that can be considered pleiotropic. Hubert's method provided a better linear combination of traits because it had the most MTAs in common with the traditional approach. Newly identified SNPs, including rs19833 (5B) and rs48316 (2B), were annotated with important genes with vital biological processes and molecular functions. The approaches presented in this study can reduce the misleading GWAS results caused by the adverse effect of outlier observations.

Exogenous 24-epibrassinolide ameliorates tolerance to high-temperature by adjusting the biosynthesis of pigments, enzymatic, non-enzymatic antioxidants, and diosgenin content in fenugreek.

High-temperature stress is widely considered a main plant-growth-limiting factor. The positive effects of 24-epibrassinolide (EBR) as analogs of brassinosteroids (BRs) in modulating abiotic stresses have led this hormone to be referred to as a growth regulator in plants. The current study highlights the influence of EBR on enhancing tolerance to high-temperature and altering the diosgenin content in fenugreek. Different amounts of EBR (4, 8, and 16 µM), harvesting times (6, and 24 h), as well as temperature regimes (23 °C, and 42 °C) were, used as treatments. EBR application under normal temperature and high-temperature stress resulted in decreased malondialdehyde content and electrolyte leakage percentage, while the activity of antioxidant enzymes improved significantly. Exogenous EBR application possibly contributes to activating the nitric oxide, H2O2, and ABA-dependent pathways, enhancing the biosynthesis of abscisic acid and auxin, and regulating the signal transduction pathways, which raises fenugreek tolerance to high-temperature. The SQS (eightfold), SEP (2.8-fold), CAS (11-fold), SMT (17-fold), and SQS (sixfold) expression, considerably increased following EBR application (8 µM) compared to the control. Compared to the control, when the short-term (6 h) high-temperature stress was accompanied by EBR (8 µM), a sixfold increase in diosgenin content was achieved. Our findings highlight the potential role of exogenous 24-epibrassinolide in mitigating the high-temperature stress in fenugreek by stimulating the biosynthesis processes of enzymatic and non-enzymatic antioxidants, chlorophylls, and diosgenin. In conclusion, the current results could be of utmost importance in breeding or biotechnology-based programs of fenugreek and also in the researches related to the engineering of the biosynthesis pathway of diosgenin in this valuable plant.

Exploring genomic regions involved in bread wheat resistance to leaf rust at seedling/adult stages by using GWAS analysis.

BACKGROUND: Global wheat productivity is seriously challenged by a range of rust pathogens, especially leaf rust derived from Puccinia triticina. Since the most efficient approach to control leaf rust is genetic resistance, many efforts have been made to uncover resistance genes; however, it demands an ongoing exploration for effective resistance sources because of the advent of novel virulent races. Thus, the current study was focused on detecting leaf rust resistance-related genomic loci against the P. triticina prevalent races by GWAS in a set of Iranian cultivars and landraces. RESULTS: Evaluation of 320 Iranian bread wheat cultivars and landraces against four prevalent rust pathotypes of P. triticina (LR-99-2, LR-98-12, LR-98-22, and LR-97-12) indicated the diversity in wheat accessions responses to P. triticina. From GWAS results, 80 leaf rust resistance QTLs were located in the surrounding known QTLs/genes on almost chromosomes, except for 1D, 3D, 4D, and 7D. Of these, six MTAs (rs20781/rs20782 associated with resistance to LR-97-12; rs49543/rs52026 for LR-98-22; rs44885/rs44886 for LR-98-22/LR-98-1/LR-99-2) were found on genomic regions where no resistance genes previously reported, suggesting new loci conferring resistance to leaf rust. The GBLUP genomic prediction model appeared better than RR-BLUP and BRR, reflecting that GBLUP is a potent model for genomic selection in wheat accessions. CONCLUSIONS: Overall, the newly identified MTAs as well as the highly resistant accessions in the recent work provide an opportunity towards improving leaf rust resistance.

Biostimulants alleviate water deficit stress and enhance essential oil productivity: a case study with savory.

Water deficit stress exposure frequently constrains plant and agri-food production globally. Biostimulants (BSs) can be considered a new tool in mitigating water deficit stress. This study aimed to understand how BSs influence water deficit stress perceived by savory plants (Satureja hortensis L.), an important herb used for nutritional and herbal purposes in the Middle East. Three BS treatments, including bio-fertilizers, humic acid and foliar application of amino acid (AA), were implemented. Each treatment was applied to savory plants using three irrigation regimes (low, moderate and severe water deficit stress FC100, FC75 and FC50, respectively). Foliar application of AA increased dry matter yield, essential oil (EO) content and EO yield by 22%, 31% and 57%, respectively. The greatest EO yields resulted from the moderate (FC75) and severe water deficit stress (FC50) treatments treated with AA. Primary EO constituents included carvacrol (39-43%), gamma-terpinene (27-37%), alpha-terpinene (4-7%) and p-cymene (2-5%). Foliar application of AA enhanced carvacrol, gamma-terpinene, alpha-terpinene and p-cymene content by 6%, 19%, 46% and 18%, respectively. Physiological characteristics were increased with increasing water shortage and application of AA. Moreover, the maximum activities of superoxide dismutase (3.17 unit mg-1 min-1), peroxidase (2.60 unit mg-1 min-1) and catalase (3.08 unit mg-1 min-1) were obtained from plants subjected to severe water deficit stress (FC50) and treated with AA. We conclude that foliar application of AA under water deficit stress conditions would improve EO quantity and quality in savory.

Genome-wide association study to identify genomic loci associated with early vigor in bread wheat under simulated water deficit complemented with quantitative trait loci meta-analysis.

A genome-wide association study (GWAS) was used to identify associated loci with early vigor under simulated water deficit and grain yield under field drought in a diverse collection of Iranian bread wheat landraces. In addition, a meta-quantitative trait loci (MQTL) analysis was used to further expand our approach by retrieving already published quantitative trait loci (QTL) from recombinant inbred lines, double haploids, back-crosses, and F2 mapping populations. In the current study, around 16%, 14%, and 16% of SNPs were in significant linkage disequilibrium (LD) in the A, B, and D genomes, respectively, and varied between 5.44% (4A) and 21.85% (6A). Three main subgroups were identified among the landraces with different degrees of admixture, and population structure was further explored through principal component analysis. Our GWAS identified 54 marker-trait associations (MTAs) that were located across the wheat genome but with the highest number found in the B sub-genome. The gene ontology (GO) analysis of MTAs revealed that around 75% were located within or closed to protein-coding genes. In the MQTL analysis, 23 MQTLs, from a total of 215 QTLs, were identified and successfully projected onto the reference map. MQT-YLD4, MQT-YLD9, MQT-YLD13, MQT-YLD17, MQT-YLD18, MQT-YLD19, and MQTL-RL1 contributed to the highest number of projected QTLs and were therefore regarded as the most reliable and stable QTLs under water deficit conditions. These MQTLs greatly facilitate the identification of putative candidate genes underlying at each MQTL interval due to the reduced confidence of intervals associated with MQTLs. These findings provide important information on the genetic basis of early vigor traits and grain yield under water deficit conditions and set the foundation for future investigations into adaptation to water deficit in bread wheat.

Genome-wide association mapping and genomic prediction of agronomical traits and breeding values in Iranian wheat under rain-fed and well-watered conditions.

BACKGROUND: The markers detected by genome-wide association study (GWAS) make it possible to dissect genetic structure and diversity at many loci. This can enable a wheat breeder to reveal and used genomic loci controlling drought tolerance. This study was focused on determining the population structure of Iranian 208 wheat landraces and 90 cultivars via genotyping-by-sequencing (GBS) and also on detecting marker-trait associations (MTAs) by GWAS and genomic prediction (GS) of wheat agronomic traits for drought-tolerance breeding. GWASs were conducted using both the original phenotypes (pGWAS) and estimated breeding values (eGWAS). The bayesian ridge regression (BRR), genomic best linear unbiased prediction (gBLUP), and ridge regression-best linear unbiased prediction (rrBLUP) approaches were used to estimate breeding values and estimate prediction accuracies in genomic selection. RESULTS: Population structure analysis using 2,174,975 SNPs revealed four genetically distinct sub-populations from wheat accessions. D-Genome harbored the lowest number of significant marker pairs and the highest linkage disequilibrium (LD), reflecting different evolutionary histories of wheat genomes. From pGWAS, BRR, gBLUP, and rrBLUP, 284, 363, 359 and 295 significant MTAs were found under normal and 195, 365, 362 and 302 under stress conditions, respectively. The gBLUP with the most similarity (80.98 and 71.28% in well-watered and rain-fed environments, correspondingly) with the pGWAS method in the terms of discovered significant SNPs, suggesting the potential of gBLUP in uncovering SNPs. Results from gene ontology revealed that 29 and 30 SNPs in the imputed dataset were located in protein-coding regions for well-watered and rain-fed conditions, respectively. gBLUP model revealed genetic effects better than other models, suggesting a suitable tool for genome selection in wheat. CONCLUSION: We illustrate that Iranian landraces of bread wheat contain novel alleles that are adaptive to drought stress environments. gBLUP model can be helpful for fine mapping and cloning of the relevant QTLs and genes, and for carrying out trait introgression and marker-assisted selection in both normal and drought environments in wheat collections.

Genome-Wide Association Study (GWAS) and genome prediction of seedling salt tolerance in bread wheat (Triticum aestivum L.).

BACKGROUND: Salinity tolerance in wheat is imperative for improving crop genetic capacity in response to the expanding phenomenon of soil salinization. However, little is known about the genetic foundation underlying salinity tolerance at the seedling growth stage of wheat. Herein, a GWAS analysis was carried out by the random-SNP-effect mixed linear model (mrMLM) multi-locus model to uncover candidate genes responsible for salt tolerance at the seedling stage in 298 Iranian bread wheat accessions, including 208 landraces and 90 cultivars. RESULTS: A total of 29 functional marker-trait associations (MTAs) were detected under salinity, 100 mM NaCl (sodium chloride). Of these, seven single nucleotide polymorphisms (SNPs) including rs54146, rs257, rs37983, rs18682, rs55629, rs15183, and rs63185 with R2 ≥ 10% were found to be linked with relative water content, root fresh weight, root dry weight, root volume, shoot high, proline, and shoot potassium (K+), respectively. Further, a total of 27 candidate genes were functionally annotated to be involved in response to the saline environment. Most of these genes have key roles in photosynthesis, response to abscisic acid, cell redox homeostasis, sucrose and carbohydrate metabolism, ubiquitination, transmembrane transport, chromatin silencing, and some genes harbored unknown functions that all together may respond to salinity as a complex network. For genomic prediction (GP), the genomic best linear unbiased prediction (GBLUP) model reflected genetic effects better than both bayesian ridge regression (BRR) and ridge regression-best linear unbiased prediction (RRBLUP), suggesting GBLUP as a favorable tool for wheat genomic selection. CONCLUSION: The SNPs and candidate genes identified in the current work can be used potentially for developing salt-tolerant varieties at the seedling growth stage by marker-assisted selection.

Genome-wide association mapping for wheat morphometric seed traits in Iranian landraces and cultivars under rain-fed and well-watered conditions.

Seed traits in bread wheat are valuable to breeders and farmers, thus it is important exploring putative QTLs responsible for key traits to be used in breeding programs. GWAS was carried out using 298 bread wheat landraces and cultivars from Iran to uncover the genetic basis of seed characteristics in both rain-fed and well-watered environments. The analyses of linkage disequilibrium (LD) between marker pairs showed that the largest number of significant LDs in landraces (427,017) and cultivars (370,359) was recorded in genome B, and the strongest LD was identified on chromosome 4A (0.318). LD decay was higher in the B and A genomes, compared to the D genome. Mapping by using mrMLM (LOD > 3) and MLM (0.05/m, Bonferroni) led to 246 and 67 marker-trait associations (MTAs) under rain-fed, as well as 257 and 74 MTAs under well-watered conditions, respectively. The study found that 3VmrMLM correctly detected all types of loci and estimated their effects in an unbiased manner, with high power and accuracy and a low false positive rate, which led to the identification of 140 MTAs (LOD > 3) in all environments. Gene ontology revealed that 10 and 10 MTAs were found in protein-coding regions for rain-fed and well-watered conditions, respectively. The findings suggest that landraces studied in Iranian bread wheat germplasm possess valuable alleles, which are responsive to water-limited conditions. MTAs uncovered in this study can be exploited in the genome-mediated development of novel wheat cultivars.

Melatonin confers fenugreek tolerance to salinity stress by stimulating the biosynthesis processes of enzymatic, non-enzymatic antioxidants, and diosgenin content.

Salinity-induced stress is widely considered a main plant-growth-limiting factor. The positive effects of melatonin in modulating abiotic stresses have led this hormone to be referred to as a growth regulator in plants. This study aims to show how melatonin protects fenugreek against the negative effects of salt stress. Different amounts of melatonin (30, 60, and 90 ppm), salinity stress (150 mM and 300 mM), and the use of both salinity and melatonin were used as treatments. The results showed that applying different melatonin levels to salinity-treated fenugreek plants effectively prevented the degradation of chlorophyll a, chlorophyll b, total chlorophyll, and carotenoid contents compared with salinity treatment without melatonin application. Besides, melatonin increases the biosynthesis of enzymatic and non-enzymatic antioxidants, thereby adjusting the content of reactive oxygen species, free radicals, electrolyte leakage, and malondialdehyde content. It was observed that applying melatonin increased the activity of potassium-carrying channels leading to the maintenance of ionic homeostasis and increased intracellular water content under salinity stress. The results revealed that melatonin activates the defense signaling pathways in fenugreek through the nitric oxide, auxin, and abscisic acid-dependent pathways. Melatonin, in a similar vein, increased the expression of genes involved in the biosynthesis pathway of diosgenin, a highly important steroidal sapogenin in medical and food industries, and hence the diosgenin content. When 150 mM salinity stress and 60 ppm melatonin were coupled, the diosgenin concentration rose by more than 5.5 times compared to the control condition. In conclusion, our findings demonstrate the potential of melatonin to enhance the plant tolerance to salinity stress by stimulating biochemical and physiological changes.

Genome-wide association mapping and genomic prediction for pre­harvest sprouting resistance, low α-amylase and seed color in Iranian bread wheat.

BACKGROUND: Pre-harvest sprouting (PHS) refers to a phenomenon, in which the physiologically mature seeds are germinated on the spike before or during the harvesting practice owing to high humidity or prolonged period of rainfall. Pre-harvest sprouting (PHS) remarkably decreases seed quality and yield in wheat; hence it is imperative to uncover genomic regions responsible for PHS tolerance to be used in wheat breeding. A genome-wide association study (GWAS) was carried out using 298 bread wheat landraces and varieties from Iran to dissect the genomic regions of PHS tolerance in a well-irrigated environment. Three different approaches (RRBLUP, GBLUP and BRR) were followed to estimate prediction accuracies in wheat genomic selection. RESULTS: Genomes B, A, and D harbored the largest number of significant marker pairs (MPs) in both landraces (427,017, 328,006, 92,702 MPs) and varieties (370,359, 266,708, 63,924 MPs), respectively. However, the LD levels were found the opposite, i.e., genomes D, A, and B have the highest LD, respectively. Association mapping by using GLM and MLM models resulted in 572 and 598 marker-trait associations (MTAs) for imputed SNPs (- log10 P > 3), respectively. Gene ontology exhibited that the pleitropic MPs located on 1A control seed color, α-Amy activity, and PHS. RRBLUP model indicated genetic effects better than GBLUP and BRR, offering a favorable tool for wheat genomic selection. CONCLUSIONS: Gene ontology exhibited that the pleitropic MPs located on 1A can control seed color, α-Amy activity, and PHS. The verified markers in the current work can provide an opportunity to clone the underlying QTLs/genes, fine mapping, and genome-assisted selection.Our observations uncovered key MTAs related to seed color, α-Amy activity, and PHS that can be exploited in the genome-mediated development of novel varieties in wheat.

The effect of exogenously applied plant growth regulators and zinc on some physiological characteristics and essential oil constituents of Moldavian balm (Dracocephalum moldavica L.) under water stress.

Cost-effective exogenous application of some antioxidant, viz. salicylic acid (SA) and ascorbic acid (AA), and essential micronutrient elements like Zn might alleviate the harmful impacts of drought stress. Here, we evaluated the interaction of foliar-sprayed SA (1 mM), AA (10 mM), and Zn (3 g L-1) and irrigation regime (normal irrigation, moderate water stress, and severe water stress) by assaying an array of agronomic, physiological, analytical and biochemical parameters of Moldavian balm (Dracocephalum moldavica L.). Accordingly, the SA and AA treatments reduced the harmful effects of moderate and severe drought stress. Well-watered plants applied with Zn had the highest biomass yield (4642.5 kg ha-1). Severe water stress decreased plant biomass, essential oil (EO) content, EO yield, relative water content, and chlorophyll a content by 37.6%, 23.3%, 47.5%, 35.3%, and 53%, respectively, relative to normal irrigation. Plants treated with Zn under moderate drought stress had the highest EO content. Moderate and severe water stress increased enzymatic antioxidant (catalase, superoxide dismutase, and peroxidase) activities and total soluble sugars and proline contents. In terms of EO composition, SA-treated plants under moderate water stress contained the most geraniol (22.8%) and geranial (26.3%), while Zn-treated plants under severe water stress contained the most geranyl acetate (48.2%). This study demonstrated that foliar application of Zn and SA significantly improves EO productivity and quality in Moldavian balm under moderate water stress. The relevant findings were supported by heatmap clustering, revealing that irrigation regime had main effect on the essential oil compounds and biochemical and physiological parameters. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12298-021-01084-1.

Characterization of Dynamic Regulatory Gene and Protein Networks in Wheat Roots Upon Perceiving Water Deficit Through Comparative Transcriptomics Survey.

A well-developed root system benefits host plants by optimizing water absorption and nutrient uptake and thereby increases plant productivity. In this study we have characterized the root transcriptome using RNA-seq and subsequential functional analysis in a set of drought tolerant and susceptible genotypes. The goal of the study was to elucidate and characterize water deficit-responsive genes in wheat landraces that had been through long-term field and biochemical screening for drought tolerance. The results confirm genotype differences in water-deficit tolerance in line with earlier results from field trials. The transcriptomics survey highlighted a total of 14,187 differentially expressed genes (DEGs) that responded to water deficit. The characterization of these genes shows that all chromosomes contribute to water-deficit tolerance, but to different degrees, and the B genome showed higher involvement than the A and D genomes. The DEGs were mainly mapped to flavonoid, phenylpropanoid, and diterpenoid biosynthesis pathways, as well as glutathione metabolism and hormone signaling. Furthermore, extracellular region, apoplast, cell periphery, and external encapsulating structure were the main water deficit-responsive cellular components in roots. A total of 1,377 DEGs were also predicted to function as transcription factors (TFs) from different families regulating downstream cascades. TFs from the AP2/ERF-ERF, MYB-related, B3, WRKY, Tify, and NAC families were the main genotype-specific regulatory factors. To further characterize the dynamic biosynthetic pathways, protein-protein interaction (PPI) networks were constructed using significant KEGG proteins and putative TFs. In PPIs, enzymes from the CYP450, TaABA8OH2, PAL, and GST families play important roles in water-deficit tolerance in connection with MYB13-1, MADS-box, and NAC transcription factors.

Dissection of the genetic basis of genotype-by-environment interactions for grain yield and main agronomic traits in Iranian bread wheat landraces and cultivars.

Understanding the genetic basis of performance stability is essential to maintain productivity, especially under severe conditions. In the present study, 268 Iranian bread wheat landraces and cultivars were evaluated in four well-watered and two rain-fed conditions for different traits. According to breeding programs, cultivars were in a group with a high mean and stability in terms of GY, GN, and SW traits, while in terms of PH, they had a low mean and high stability. The stability of cultivars and landraces was related to dynamic and static stability, respectively. The highest number of marker pairs and lowest LD decay distance in both cultivars and landraces was observed on the B genome. Population structure differentiated indigenous cultivars and landraces, and the GWAS results for each were almost different despite the commonalities. Chromosomes 1B, 3B, 7B, 2A, and 4A had markers with pleiotropic effects on the stability of different traits. Due to two rain-fed environments, the Gene Ontology (GO) confirmed the accuracy of the results. The identified markers in this study can be helpful in breeding high-performance and stable genotypes and future breeding programs such as fine mapping and cloning.