Genome-wide association studies of seven agronomic traits under two sowing conditions in bread wheat

Genome-wide association study for seedling heat tolerance under two temperature conditions in bread wheat (Triticum aestivum L.)

BACKGROUND

As the greenhouse effect intensifies, global temperatures are steadily increasing, posing a challenge to bread wheat (Triticum aestivum L.) production. It is imperative to comprehend the mechanism of high temperature tolerance in wheat and implement breeding programs to identify and develop heat-tolerant wheat germplasm and cultivars.

RESULTS

To identify quantitative trait loci (QTL) related to heat stress tolerance (HST) at seedling stage in wheat, a panel of 253 wheat accessions which were re-sequenced used to conduct genome-wide association studies (GWAS) using the factored spectrally transformed linear mixed models (FaST-LMM). For most accessions, the growth of seedlings was found to be inhibited under heat stress. Analysis of the phenotypic data revealed that under heat stress conditions, the main root length, total root length, and shoot length of seedlings decreased by 47.46%, 49.29%, and 15.19%, respectively, compared to those in normal conditions. However, 17 varieties were identified as heat stress tolerant germplasm. Through GWAS analysis, a total of 115 QTLs were detected under both heat stress and normal conditions. Furthermore, 15 stable QTL-clusters associated with heat response were identified. By combining gene expression, haplotype analysis, and gene annotation information within the physical intervals of the 15 QTL-clusters, two novel candidate genes, TraesCS4B03G0152700/TaWRKY74-B and TraesCS4B03G0501400/TaSnRK3.15-B, were responsive to temperature and identified as potential regulators of HST in wheat at the seedling stage.

CONCLUSIONS

This study conducted a detailed genetic analysis and successfully identified two genes potentially associated with HST in wheat at the seedling stage, laying a foundation to further dissect the regulatory mechanism underlying HST in wheat under high temperature conditions. Our finding could serve as genomic landmarks for wheat breeding aimed at improving adaptation to heat stress in the face of climate change.

Deciphering genetic basis of developmental and agronomic traits by integrating high-throughput optical phenotyping and genome-wide association studies in wheat

Dissecting the genetic basis of complex traits such as dynamic growth and yield potential is a major challenge in crops. Monitoring the growth throughout growing season in a large wheat population to uncover the temporal genetic controls for plant growth and yield-related traits has so far not been explored. In this study, a diverse wheat panel composed of 288 lines was monitored by a non-invasive and high-throughput phenotyping platform to collect growth traits from seedling to grain filling stage and their relationship with yield-related traits was further explored. Whole genome re-sequencing of the panel provided 12.64 million markers for a high-resolution genome-wide association analysis using 190 image-based traits and 17 agronomic traits. A total of 8327 marker-trait associations were detected and clustered into 1605 quantitative trait loci (QTLs) including a number of known genes or QTLs. We identified 277 pleiotropic QTLs controlling multiple traits at different growth stages which revealed temporal dynamics of QTLs action on plant development and yield production in wheat. A candidate gene related to plant growth that was detected by image traits was further validated. Particularly, our study demonstrated that the yield-related traits are largely predictable using models developed based on i-traits and provide possibility for high-throughput early selection, thus to accelerate breeding process. Our study explored the genetic architecture of growth and yield-related traits by combining high-throughput phenotyping and genotyping, which further unravelled the complex and stage-specific contributions of genetic loci to optimize growth and yield in wheat.

Unravelling the Genetic Basis of Moisture Deficit Stress Tolerance in Wheat for Seedling Vigour-Related Traits and Root Traits Using Genome-Wide Association Study

A key abiotic stress that negatively affects seed germination, plant development, and crop yield is moisture deficit stress. Achieving higher vigour and uniform germination under stress conditions is essential for crop establishment and productivity and to enhance the yield. Hence, revealing wheat's capacity to withstand moisture deficit stress during seed germination and early growth stages is fundamental in improving its overall performance. However, the genetic regulation of moisture deficit stress tolerance during the seed germination phase remains largely unexplored. In this study, a total of 193 wheat genotypes were subjected to simulated moisture deficit stress using PEG-6000 (-0.4 MPa) during the seed germination stage. The induced moisture deficit stress significantly reduced various seedling-vigour-related traits. The genetic regions linked to these traits were found using a genome-wide association study (GWAS). The analysis identified 235 MTAs with a significance -log10(p) value of >4. After applying the Bonferroni correction, the study identified 47 unique single nucleotide polymorphisms (SNPs) that are linked to candidate genes important for the trait of interest. The current study emphasises the effectiveness of genome-wide association studies (GWAS) in identifying promising candidate genes, improving wheat seedling vigour and root traits, and offering essential information for the development of wheat cultivars tolerant to moisture deficit stress.

Genome-wide association study of maize resistance to Pythium aristosporum stalk rot

Stalk rot, a severe and widespread soil-borne disease in maize, globally reduces yield and quality. Recent documentation reveals that Pythium aristosporum has emerged as one of the dominant causal agents of maize stalk rot. However, a previous study of maize stalk rot disease resistance mechanisms and breeding had mainly focused on other pathogens, neglecting P. aristosporum. To mitigate crop loss, resistance breeding is the most economical and effective strategy against this disease. This study involved characterizing resistance in 295 inbred lines using the drilling inoculation method and genotyping them via sequencing. By combining with population structure, disease resistance phenotype, and genome-wide association study (GWAS), we identified 39 significant single-nucleotide polymorphisms (SNPs) associated with P. aristosporum stalk rot resistance by utilizing six statistical methods. Bioinformatics analysis of these SNPs revealed 69 potential resistance genes, among which Zm00001d051313 was finally evaluated for its roles in host defense response to P. aristosporum infection. Through virus-induced gene silencing (VIGS) verification and physiological index determination, we found that transient silencing of Zm00001d051313 promoted P. aristosporum infection, indicating a positive regulatory role of this gene in maize's antifungal defense mechanism. Therefore, these findings will help advance our current understanding of the underlying mechanisms of maize defense to Pythium stalk rot.

Grain yield and adaptation of spring wheat to Norwegian growing conditions is driven by allele frequency changes at key adaptive loci discovered by genome-wide association mapping

KEY MESSAGE

Adaptation to the Norwegian environment is associated with polymorphisms in the Vrn-A1 locus. Historical selection for grain yield in Nordic wheat is associated with TaGS5-3A and TaCol-5 loci. Grain yields in Norwegian spring wheat increased by 18 kg ha-1 per year between 1972 and 2019 due to introduction of new varieties. These gains were associated with increments in the number of grains per spike and extended length of the vegetative period. However, little is known about the genetic background of this progress. To fill this gap, we conducted genome-wide association study on a panel consisting of both adapted (historical and current varieties and lines in the Nordics) and important not adapted accessions used as parents in the Norwegian wheat breeding program. The study concerned grain yield, plant height, and heading and maturity dates, and detected 12 associated loci, later validated using independent sets of recent breeding lines. Adaptation to the Norwegian cropping conditions was found to be associated with the Vrn-A1 locus, and a previously undescribed locus on chromosome 1B associated with heading date. Two loci associated with grain yield, corresponding to the TaGS5-3A and TaCol-5 loci, indicated historical selection pressure for high grain yield. A locus on chromosome 2A explained the tallness of the oldest accessions. We investigated the origins of the beneficial alleles associated with the wheat breeding progress in the Norwegian material, tracing them back to crosses with Swedish, German, or CIMMYT lines. This study contributes to the understanding of wheat adaptation to the Norwegian growing conditions, sheds light on the genetic basis of historical wheat improvement and aids future breeding efforts by discovering loci associated with important agronomic traits in 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.

Association mapping identifies loci and candidate genes for grain-related traits in spring wheat in response to heat stress

Heat stress is a limiting factor in wheat production along with global warming. Development of heat-tolerant wheat varieties and generation of suitable pre-breeding materials are the major goals in current wheat breeding programs. Our understanding on the genetic basis of thermotolerance remains sparse. In this study, we genotyped a collection of 211 core spring wheat accessions and conducted field trials to evaluate the grain-related traits under heat stress and non-stress conditions in two different locations for three consecutive years. Based on SNP datasets and grain-related traits, we performed genome-wide association study (GWAS) to detect stable loci related to thermotolerance. Thirty-three quantitative trait loci (QTL) were identified, nine of them are the same loci as previous studies, and 24 are potentially novel loci. Functional candidate genes at these QTL are predicted and proved to be relevant to heat stress and grain-related traits such as TaELF3-A1 (1A) for earliness per se (Eps), TaHSFA1-B1 (5B) influencing heat tolerance and TaVIN2-A1 (6A) for grain size. Functional markers of TaELF3-A1 were detected and converted to KASP markers, with their function and genetic diversity being analyzed in the natural populations. In addition, our results unveiled favor alleles controlling agronomic traits and/or heat stress tolerance. In summary, we provide insights into heritable correlation between yield and heat stress tolerance, which will accelerate the development of new cultivars with high and stable yield of wheat in the future.

GWAS scans of cereal cyst nematode (Heterodera avenae) resistance in Indian wheat germplasm

Significant yield losses in major cereal-growing regions around the world have been linked to cereal cyst nematodes (Heterodera spp.). Identifying and deploying natural sources of resistance is of utmost importance due to increasing concerns associated with chemical methods over the years. We screened 141 diverse wheat genotypes collected from pan-Indian wheat cultivation states for nematode resistance over two years, alongside two resistant (Raj MR1, W7984 (M6)) and two susceptible (WH147, Opata M85) checks. We performed genome-wide association analysis using four single-locus models (GLM, MLM, CMLM, and ECMLM) and three multi-locus models (Blink, FarmCPU, and MLMM). Single locus models identified nine significant MTAs (-log10 (P) > 3.0) on chromosomes 2A, 3B, and 4B whereas, multi-locus models identified 11 significant MTAs on chromosomes 1B, 2A, 3B, 3D and 4B. Single and multi-locus models identified nine common significant MTAs. Candidate gene analysis identified 33 genes like F-box-like domain superfamily, Cytochrome P450 superfamily, Leucine-rich repeat, cysteine-containing subtype Zinc finger RING/FYVE/PHD-type, etc., having a putative role in disease resistance. Such genetic resources can help to reduce the impact of this disease on wheat production. Additionally, these results can be used to design new strategies for controlling the spread of H. avenae, such as the development of resistant varieties or the use of resistant cultivars. Finally, the obtained results can also be used to identify new sources of resistance to this pathogen and develop novel control methods.

Foliar application of silicon-based nanoparticles improve the adaptability of maize (Zea mays L.) in cadmium contaminated soils

Heavy metals (HMs) especially cadmium (Cd) absorbed by the roots of crop plants like maize have emerged as one of the most serious threats by causing stunted plant growth along with disturbing the photosynthetic machinery and nutrient homeostasis process. A trial was conducted for inducing Cd stress tolerance in maize by exogenous application of silicon nanoparticles (SiNPs) using five doses of SiNPs (0, 100, 200, 300, and 400 ppm) and three levels of Cd (0, 15, and 30 ppm) for maize hybrid (SF-9515). The response variables included morphological traits and biochemical parameters of maize. The results indicated that Cd level of 30 ppm remained the most drastic for maize plants by recording the minimum traits such as shoot length (39.35 cm), shoot fresh weight (9.52 g) and shoot dry weight (3.20 g), leaf pigments such as chlorophyll a (0.55 mg/g FW), chlorophyll b (0.27 mg/g FW), total contents (0.84 mg/g FW), and carotenoid contents (0.19 µg/g FW). Additionally, the same Cd level disrupted biochemical traits such as TSP (4.85 mg/g FW), TP (252.94 nmol/g FW), TSAA (18.92 µmol g^-1 FW), TSS (0.85 mg/g FW), and antioxidant activities such as POD (99.39 min^-1 g^-1 FW), CAT (81.58 min^-1 g^-1 FW), APX (2.04 min^-1 g^-1 FW), and SOD (172.79 min^-1 g^-1 FW). However, a higher level of Cd resulted in greater root length (87.63 cm), root fresh weight (16.43 g), and root dry weight (6.14 g) along with higher Cd concentration in the root (2.52 µg/g^-1) and shoot (0.48 µg/g^-1). The silicon nanoparticles (Si NPs) treatment significantly increased all measured attributes of maize. The highest value was noted of all the parameters such as chlorophyll a (0.91 mg/g FW), chlorophyll b (0.57 mg/g FW), total chlorophyll contents (1.48 mg/g FW), total carotenoid contents (0.40 µg/g FW), TSP (6.12 mg/g FW), TP (384.56 nmol/g FW), TSAA (24.64 µmol g^-1 FW), TSS (1.87 mg/g FW), POD (166.10 min^-1 g^-1 FW), CAT (149.54 min^-1 g^-1 FW), APX (3.49 min^-1 g^-1 FW), and SOD (225.57 min^-1 g^-1 FW). Based on recorded findings, it might be inferred that higher levels of Cd tend to drastically reduce morpho-physiological traits of maize and foliage-applied silver nanoparticles hold the potential to ameliorate the adverse effect of Cd stress on maize.

Marker-trait association analyses revealed major novel QTLs for grain yield and related traits in durum wheat

The growing global demand for wheat for food is rising due to the influence of population growth and climate change. The dissection of complex traits by employing a genome-wide association study (GWAS) allows the identification of DNA markers associated with complex traits to improve the productivity of crops. We used GWAS with 10,045 single nucleotide polymorphism (SNP) markers to search for genomic regions associated with grain yield and related traits based on diverse panels of Ethiopian durum wheat. In Ethiopia, multi-environment trials of the genotypes were carried out at five locations. The genotyping was conducted using the 25k Illumina Wheat SNP array to explore population structure, linkage disequilibrium (LD), and marker-trait associations (MTAs). For GWAS, the multi-locus Fixed and Random Model Circulating Probability Unification (FarmCPU) model was applied. Broad-sense heritability estimates were high, ranging from 0.63 (for grain yield) to 0.97 (for thousand-kernel weight). The population structure based on principal component analysis, and model-based cluster analysis revealed two genetically distinct clusters with limited admixtures. The LD among SNPs declined within the range of 2.02-10.04 Mbp with an average of 4.28 Mbp. The GWAS scan based on the mean performance of the genotypes across the environments identified 44 significant MTAs across the chromosomes. Twenty-six of these MTAs are novel, whereas the remaining 18 were previously reported and confirmed in this study. We also identified candidate genes for the novel loci potentially regulating the traits. Hence, this study highlights the significance of the Ethiopian durum wheat gene pool for improving durum wheat globally. Furthermore, a breeding strategy focusing on accumulating favorable alleles at these loci could improve durum wheat production in the East African highlands and elsewhere.

Genetics of spot blotch resistance in bread wheat (Triticum aestivum L.) using five models for GWAS

Genetic architecture of resistance to spot blotch in wheat was examined using a Genome-Wide Association Study (GWAS) involving an association panel comprising 303 diverse genotypes. The association panel was evaluated at two different locations in India including Banaras Hindu University (BHU), Varanasi (Uttar Pradesh), and Borlaug Institute for South Asia (BISA), Pusa, Samastipur (Bihar) for two consecutive years (2017-2018 and 2018-2019), thus making four environments (E1, BHU 2017-18; E2, BHU 2018-19; E3, PUSA, 2017-18; E4, PUSA, 2018-19). The panel was genotyped for 12,196 SNPs based on DArT-seq (outsourced to DArT Ltd by CIMMYT); these SNPs included 5,400 SNPs, which could not be assigned to individual chromosomes and were therefore, described as unassigned by the vendor. Phenotypic data was recorded on the following three disease-related traits: (i) Area Under Disease Progress Curve (AUDPC), (ii) Incubation Period (IP), and (iii) Lesion Number (LN). GWAS was conducted using each of five different models, which included two single-locus models (CMLM and SUPER) and three multi-locus models (MLMM, FarmCPU, and BLINK). This exercise gave 306 MTAs, but only 89 MTAs (33 for AUDPC, 30 for IP and 26 for LN) including a solitary MTA detected using all the five models and 88 identified using four of the five models (barring SUPER) were considered to be important. These were used for further analysis, which included identification of candidate genes (CGs) and their annotation. A majority of these MTAs were novel. Only 70 of the 89 MTAs were assigned to individual chromosomes; the remaining 19 MTAs belonged to unassigned SNPs, for which chromosomes were not known. Seven MTAs were selected on the basis of minimum P value, number of models, number of environments and location on chromosomes with respect to QTLs reported earlier. These 7 MTAs, which included five main effect MTAs and two for epistatic interactions, were considered to be important for marker-assisted selection (MAS). The present study thus improved our understanding of the genetics of resistance against spot blotch in wheat and provided seven MTAs, which may be used for MAS after due validation.

Genetic dissection of marker trait associations for grain micro-nutrients and thousand grain weight under heat and drought stress conditions in wheat

Introduction

Wheat is grown and consumed worldwide, making it an important staple food crop for both its calorific and nutritional content. In places where wheat is used as a staple food, suboptimal micronutrient content levels, especially of grain iron (Fe) and zinc (Zn), can lead to malnutrition. Grain nutrient content is influenced by abiotic stresses, such as drought and heat stress. The best method for addressing micronutrient deficiencies is the biofortification of food crops. The prerequisites for marker-assisted varietal development are the identification of the genomic region responsible for high grain iron and zinc contents and an understanding of their genetics.

Methods

A total of 193 diverse wheat genotypes were evaluated under drought and heat stress conditions across the years at the Indian Agricultural Research Institute (IARI), New Delhi, under timely sown irrigated (IR), restricted irrigated (RI) and late sown (LS) conditions. Grain iron content (GFeC) and grain zinc content (GZnC) were estimated from both the control and treatment groups. Genotyping of all the lines under study was carried out with the single nucleotide polymorphisms (SNPs) from Breeder's 35K Axiom Array.

Result and Discussion

Three subgroups were observed in the association panel based on both principal component analysis (PCA) and dendrogram analysis. A large whole-genome linkage disequilibrium (LD) block size of 3.49 Mb was observed. A genome-wide association study identified 16 unique stringent marker trait associations for GFeC, GZnC, and 1000-grain weight (TGW). In silico analysis demonstrated the presence of 28 potential candidate genes in the flanking region of 16 linked SNPs, such as synaptotagmin-like mitochondrial-lipid-binding domain, HAUS augmin-like complex, di-copper center-containing domain, protein kinase, chaperonin Cpn60, zinc finger, NUDIX hydrolase, etc. Expression levels of these genes in vegetative tissues and grain were also found. Utilization of identified markers in marker-assisted breeding may lead to the rapid development of biofortified wheat genotypes to combat malnutrition.

A Haplotype-Based GWAS Identified Trait-Improving QTL Alleles Controlling Agronomic Traits under Contrasting Nitrogen Fertilization Treatments in the MAGIC Wheat Population WM-800

The multi-parent-advanced-generation-intercross (MAGIC) population WM-800 was developed by intercrossing eight modern winter wheat cultivars to enhance the genetic diversity present in breeding populations. We cultivated WM-800 during two seasons in seven environments under two contrasting nitrogen fertilization treatments. WM-800 lines exhibited highly significant differences between treatments, as well as high heritabilities among the seven agronomic traits studied. The highest-yielding WM-line achieved an average yield increase of 4.40 dt/ha (5.2%) compared to the best founder cultivar Tobak. The subsequent genome-wide-association-study (GWAS), which was based on haplotypes, located QTL for seven agronomic traits including grain yield. In total, 40, 51, and 46 QTL were detected under low, high, and across nitrogen treatments, respectively. For example, the effect of QYLD_3A could be associated with the haplotype allele of cultivar Julius increasing yield by an average of 4.47 dt/ha (5.2%). A novel QTL on chromosome 2B exhibited pleiotropic effects, acting simultaneously on three-grain yield components (ears-per-square-meter, grains-per-ear, and thousand-grain-weight) and plant-height. These effects may be explained by a member of the nitrate-transporter-1 (NRT1)/peptide-family, TaNPF5.34, located 1.05 Mb apart. The WM-800 lines and favorable QTL haplotypes, associated with yield improvements, are currently implemented in wheat breeding programs to develop advanced nitrogen-use efficient wheat cultivars.

Genome-Wide Association Analysis for Hybrid Breeding in Wheat

Disclosure of markers that are significantly associated with plant traits can help develop new varieties with desirable properties. This study determined the genome-wide associations based on DArTseq markers for six agronomic traits assessed in eight environments for wheat. Moreover, the association study for heterosis and analysis of the effects of markers grouped by linkage disequilibrium were performed based on mean values over all experiments. All results were validated using data from post-registration trials. GWAS revealed 1273 single nucleotide polymorphisms with biologically significant effects. Most polymorphisms were predicted to be modifiers of protein translation, with only two having a more pronounced effect. Markers significantly associated with the considered set of features were clustered within chromosomes based on linkage disequilibrium in 327 LD blocks. A GWAS for heterosis revealed 1261 markers with significant effects.

Genome-wide association study of agronomic traits related to nitrogen use efficiency in wheat

GWAS identified 347 QTLs associated with eight traits related to nitrogen use efficiency in a 389-count wheat panel. Four novel candidate transcription factor genes were verified using qRT-PCR. Nitrogen is an essential nutrient for plants that determines crop yield. Improving nitrogen use efficiency (NUE) should considerably increase wheat yield and reduce the use of nitrogen fertilisers. However, knowledge on the genetic basis of NUE during wheat maturity is limited. In this study, a diversity panel incorporating 389 wheat accessions was phenotyped for eight NUE-related agronomic traits across five different environments. A total of 347 quantitative trait loci (QTLs) for low nitrogen tolerance indices (ratio of agronomic characters under low and high nitrogen conditions) were identified through a genome-wide association study utilising 397,384 single nucleotide polymorphisms (SNPs) within the MLM (Q + K) model, including 11 stable QTLs. Furthermore, 69 candidate genes were predicted for low nitrogen tolerance indices of best linear unbiased predictions values of the eight studied agronomic traits, and four novel candidate transcription factors (TraesCS5A02G237500 for qFsnR5A.2, TraesCS5B02G384500 and TraesCS5B02G384600 for qSLR5B.1, and TraesCS3B02G068800 for qTKWR3B.1) showed differing expression patterns in contrasting low-nitrogen-tolerant wheat genotypes. Moreover, the number of favourable marker alleles calculated using NUE that were significantly related to SNP in accessions decreased over the decades, indicating a decline in the NUE of the 389 wheat varieties. These findings denote promising NUE markers that could be useful in breeding high-NUE wheat varieties, and the candidate genes could further detail the NUE-related regulation network in wheat.

Genetic dissection of quantitative traits loci identifies new genes for gelatinization parameters of starch and amylose-lipid complex (Resistant starch 5) in bread wheat

Starch is a major component of cereal grains such as wheat. Physicochemical and functional properties of starch affect end-use food quality and nutrients. To improve cultivars that preserve superior starch quality, the genetic foundation of the wheat starch and amylose-lipid complex (ALc, Resistant starch type 5) gelatinization are needed. This genome-wide association (GWA) mapping used 192 wheat genotypes (previously reported) to generate SNPs using an enhanced version of sequencing termed ddRAD on the Illumina Hi-seq X platform and 3696 high-quality influential SNPs were filtered out. The heterozygosity and Fst ranges in five subpopulations were 0.31-0.40 and 0.18-0.30 respectively. Nucleotide diversity and PIC ranged from 0.21 (6A) to 0.32 (2A) and 0.29 (6A) to 0.39 (4D) respectively. The Shannon waiver index was 1.7 and the whole-genome LD decay was 22 Mb at r² = 0.38. Following FDR, 23 and 8 SNPs showed association with starch properties in the year 2017 and 2018, respectively while 93 and 20 SNPs were associated with ALc gelatinization in the year 2017 and 2018 respectively. The identified potential new genes (GSK3-alpha, RING-type domain-containing protein, Tetratricopeptide repeat, Hexosyltransferase, GLP, SNF1, and WRKY transcription factor) within LD range (∼16 Kb to ∼15 Mb), BLUP value, and cis and trans-position of SNPs network provide valuable information for the future wheat breeding strategy for the improvement of the starch quality trait.

Genome-Wide Association Study in Bread Wheat Identifies Genomic Regions Associated with Grain Yield and Quality under Contrasting Water Availability

The objectives of this study were to identify genetic loci in the bread wheat genome that would influence yield stability and quality under water stress, and to identify accessions that can be recommended for cultivation in dry and hot regions. We performed a genome-wide association study (GWAS) using a panel of 232 wheat accessions spanning diverse ecogeographic regions. Plants were evaluated in the Israeli Northern Negev, under two environments: water-limited (D; 250 mm) and well-watered (W; 450 mm) conditions; they were genotyped with ~71,500 SNPs derived from exome capture sequencing. Of the 14 phenotypic traits evaluated, 12 had significantly lower values under D compared to W conditions, while the values for two traits were higher under D. High heritability (H² = 0.5–0.9) was observed for grain yield, spike weight, number of grains per spike, peduncle length, and plant height. Days to heading and grain yield could be partitioned based on accession origins. GWAS identified 154 marker-trait associations (MTAs) for yield and quality-related traits, 82 under D and 72 under W, and identified potential candidate genes. We identified 24 accessions showing high and/or stable yields under D conditions that can be recommended for cultivation in regions under the threat of global climate change.

Genome-wide association study for grain yield and component traits in bread wheat (Triticum aestivum L.)

Genomic regions governing days to heading (DH), grain filling duration (GFD), grain number per spike (GNPS), grain weight per spike (GWPS), plant height (PH), and grain yield (GY) were investigated in a set of 280 diverse bread wheat genotypes. The genome-wide association studies (GWAS) panel was genotyped using a 35K Axiom Array and phenotyped in five environments. The GWAS analysis showed a total of 27 Bonferroni-corrected marker-trait associations (MTAs) on 15 chromosomes representing all three wheat subgenomes. The GFD showed the highest MTAs (8), followed by GWPS (7), GY (4), GNPS (3), PH (3), and DH (2). Furthermore, 20 MTAs were identified with more than 10% phenotypic variation. A total of five stable MTAs (AX-95024590, AX-94425015, AX-95210025 AX-94539354, and AX-94978133) were identified in more than one environment and associated with the expression of DH, GFD, GNPS, and GY. Similarly, two novel pleiotropic genomic regions with associated MTAs i.e. AX-94978133 (4D) and AX-94539354 (6A) harboring co-localized QTLs governing two or more traits were also identified. In silico analysis revealed that the SNPs were located on important putative candidate genes such as F-box-like domain superfamily, Lateral organ boundaries, LOB, Thioredoxin-like superfamily Glutathione S-transferase, RNA-binding domain superfamily, UDP-glycosyltransferase family, Serine/threonine-protein kinase, Expansin, Patatin, Exocyst complex component Exo70, DUF1618 domain, Protein kinase domain involved in the regulation of grain size, grain number, growth and development, grain filling duration, and abiotic stress tolerance. The identified novel MTAs will be validated to estimate their effects in different genetic backgrounds for subsequent use in marker-assisted selection (MAS).

Genome-wide association mapping for component traits of drought and heat tolerance in wheat

Identification of marker trait association is a prerequisite for marker-assisted breeding. To find markers linked with traits under heat and drought stress in bread wheat (Triticum aestivum L.), we performed a genome-wide association study (GWAS). GWAS mapping panel used in this study consists of advanced breeding lines from the IARI stress breeding programme produced by pairwise and complex crosses. Phenotyping was done at multi locations namely New Delhi, Karnal, Indore, Jharkhand and Pune with augmented-RCBD design under different moisture and heat stress regimes, namely timely sown irrigated (IR), timely sown restricted irrigated (RI) and late sown (LS) conditions. Yield and its component traits, viz., Days to Heading (DH), Days to Maturity (DM), Normalized Difference Vegetation Index (NDVI), Chlorophyll Content (SPAD), Canopy temperature (CT), Plant Height (PH), Thousand grain weight (TGW), Grain weight per spike (GWPS), Plot Yield (PLTY) and Biomass (BMS) were phenotyped. Analysis of variance and descriptive statistics revealed significant differences among the studied traits. Genotyping was done using the 35k SNP Wheat Breeder's Genotyping Array. Population structure and diversity analysis using filtered 10,546 markers revealed two subpopulations with sufficient diversity. A large whole genome LD block size of 7.15 MB was obtained at half LD decay value. Genome-wide association search identified 57 unique markers associated with various traits across the locations. Twenty-three markers were identified to be stable, among them nine pleiotropic markers were also identified. In silico search of the identified markers against the IWGSC ref genome revealed the presence of a majority of the SNPs at or near the gene coding region. These SNPs can be used for marker-assisted transfer of genes/QTLs after validation to develop climate-resilient cultivars.

Genotyping-by-Sequencing Based Molecular Genetic Diversity of Pakistani Bread Wheat (Triticum aestivum L.) Accessions

Spring wheat (Triticum aestivum L.) is one of the most imperative staple food crops, with an annual production of 765 million tons globally to feed ∼40% world population. Genetic diversity in available germplasm is crucial for sustainable wheat improvement to ensure global food security. A diversity panel of 184 Pakistani wheat accessions was genotyped using 123,596 high-quality single nucleotide polymorphism (SNP) markers generated by genotyping-by-sequencing with 42% of the SNPs mapped on B, 36% on A, and 22% on D sub-genomes of wheat. Chromosome 2B contains the most SNPs (9,126), whereas 4D has the least (2,660) markers. The mean polymorphic information content, genetic diversity, and major allele frequency of the population were 0.157, 0.1844, and 0.87, respectively. Analysis of molecular variance revealed a higher genetic diversity (80%) within the sub-population than among the sub-populations (20%). The genome-wide linkage disequilibrium was 0.34 Mbp for the whole wheat genome. Among the three subgenomes, A has the highest LD decay value (0.29 Mbp), followed by B (0.2 Mbp) and D (0.07 Mbp) genomes, respectively. The results of population structure, principal coordinate analysis, phylogenetic tree, and kinship analysis also divided the whole population into three clusters comprising 31, 33, and 120 accessions in group 1, group 2, and group 3, respectively. All groups were dominated by the local wheat accessions. Estimation of genetic diversity will be a baseline for the selection of breeding parents for mutations and the genome-wide association and marker-assisted selection studies.

Genome-wide Association Study for Starch Pasting Properties in Chinese Spring Wheat

In order to understand the genetic basis of starch pasting viscosity characteristics of Chinese spring wheat, we assessed the genetic variation of RVA parameters determined by the Rapid Visco Analyser in a panel of 192 Chinese spring wheat accessions grown in Er’shi, Shihezi and Zhaosu during 2012 and 2013 cropping seasons. A genome-wide association study with 47,362 single nucleotide polymorphism (SNP) markers was conducted to detect marker-trait associations using mixed linear model. Phenotypic variations of RVA parameters ranged from 1.6 to 30.7% and broad-sense heritabilities ranged from 0.62 to 0.91. Forty-one SNP markers at 25 loci were significantly associated with seven RVA traits in at least two environments; among these, 20 SNPs were located in coding sequences (CDS) of 18 annotation genes, which can lead to discovering novel genes underpinning starch gelatinization in spring wheat. Haplotype analysis revealed one block for breakdown (BD) on chromosome 3B and two blocks for pasting temperature (T) on chromosome 7B. Cultivars with superior haplotypes at these loci showed better starch pasting viscosity than the average of all cultivars surveyed. The identified loci and associated markers provide valuable sources for future functional characterization and genetic improvement of starch quality in wheat.

Omics: a tool for resilient rice genetic improvement strategies

Rice is pivotal pyramid of about half of the world population. Bearing small genome size and worldwide utmost food crop rice has been known as ideal cereal crop for genome research. Currently, decreasing water table and soil fatigue are big challenges and intense consequences in changing climate. Whole sequenced genome of rice sized 389 Mb of which 95% is covered with excellent mapping order. Sequenced rice genome helps in molecular biology and transcriptomics of cereals as it provides whole genome sequence of indica and japonica sub species. Through rice genome sequencing and functional genomics, QTLs or genes, genetic variability and halophyte blocks for agronomic characters were identified which have proved much more useful in molecular breeding and direct selection. There are different numbers of genes or QTLs identified for yield related traits i.e., 6 QTLs/genes for plant architecture, 6 for panicle characteristics, 4 for grain number, 1 gene/QTL for tiller, HGW, grain filling and shattering. QTLS/genes for grain quality, biotic stresses and for abiotic stresses are 7, 23 and 13 respectively. Low yield, inferior quality and susceptibility to biotic and abiotic stresses of a crop is due to narrow genetic background of new evolving rice verities. Wild rice provides genetic resources for improvement of these characters, molecular and genomics tool at different stages can overcome these stresses and improve yield and quality of rice crop.

GWAS for main effects and epistatic interactions for grain morphology traits in wheat

In the present study in wheat, GWAS was conducted for identification of marker trait associations (MTAs) for the following six grain morphology traits: (1) grain cross-sectional area (GCSA), (2) grain perimeter (GP), (3) grain length (GL), (4) grain width (GWid), (5) grain length-width ratio (GLWR) and (6) grain form-density (GFD). The data were recorded on a subset of spring wheat reference set (SWRS) comprising 225 diverse genotypes, which were genotyped using 10,904 SNPs and phenotyped for two consecutive years (2017-2018, 2018-2019). GWAS was conducted using five different models including two single-locus models (CMLM, SUPER), one multi-locus model (FarmCPU), one multi-trait model (mvLMM) and a model for Q x Q epistatic interactions. False discovery rate (FDR) [P value -log10(p) ≥ 5] and Bonferroni correction [P value -log10(p) ≥ 6] (corrected p value < 0.05) were applied to eliminate false positives due to multiple testing. This exercise gave 88 main effect and 29 epistatic MTAs after FDR and 13 main effect and 6 epistatic MTAs after Bonferroni corrections. MTAs obtained after Bonferroni corrections were further utilized for identification of 55 candidate genes (CGs). In silico expression analysis of CGs in different tissues at different parts of the seed at different developmental stages was also carried out. MTAs and CGs identified during the present study are useful addition to available resources for MAS to supplement wheat breeding programmes after due validation and also for future strategic basic research.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12298-022-01164-w.

Physiological and molecular insights on wheat responses to heat stress

Increasing temperature is a key component of global climate change, affecting crop growth and productivity worldwide. Wheat is a major cereal crop grown in various parts of the globe, which is affected severely by heat stress. The morphological parameters affected include germination, seedling establishment, source-sink activity, leaf area, shoot and root growth. The physiological parameters such as photosynthesis, respiration, leaf senescence, water and nutrient relation are also affected by heat. At the cellular level, heat stress leads to the generation of reactive oxygen species that disrupt the membrane system of thylakoid, chloroplast and plasma membrane. The deactivation of the photosystem, reduction in photosynthesis and inactivation of rubisco affect the production of photoassimilates and their allocation. This ultimately affects anthesis, grain filling, size, number and maturity of wheat grains, which hamper crop productivity. The interplay of various systems comprising antioxidants and hormones plays a crucial role in imparting heat stress tolerance in wheat. Thus, implementation of various omics technologies could foster in-depth insights on heat stress effects, eventually devising heat stress mitigation strategies by conventional and modern breeding to develop heat-tolerant wheat varieties. This review provides an integrative view of heat stress responses in wheat and also discusses approaches to develop heat-tolerant wheat varieties.

Comparative Genomic Analysis of Quantitative Trait Loci Associated With Micronutrient Contents, Grain Quality, and Agronomic Traits in Wheat (Triticum aestivum L.)

Comparative genomics and meta-quantitative trait loci (MQTLs) analysis are important tools for the identification of reliable and stable QTLs and functional genes controlling quantitative traits. We conducted a meta-analysis to identify the most stable QTLs for grain yield (GY), grain quality traits, and micronutrient contents in wheat. A total of 735 QTLs retrieved from 27 independent mapping populations reported in the last 13 years were used for the meta-analysis. The results showed that 449 QTLs were successfully projected onto the genetic consensus map which condensed to 100 MQTLs distributed on wheat chromosomes. This consolidation of MQTLs resulted in a three-fold reduction in the confidence interval (CI) compared with the CI for the initial QTLs. Projection of QTLs revealed that the majority of QTLs and MQTLs were in the non-telomeric regions of chromosomes. The majority of micronutrient MQTLs were located on the A and D genomes. The QTLs of thousand kernel weight (TKW) were frequently associated with QTLs for GY and grain protein content (GPC) with co-localization occurring at 55 and 63%, respectively. The co- localization of QTLs for GY and grain Fe was found to be 52% and for QTLs of grain Fe and Zn, it was found to be 66%. The genomic collinearity within Poaceae allowed us to identify 16 orthologous MQTLs (OrMQTLs) in wheat, rice, and maize. Annotation of promising candidate genes (CGs) located in the genomic intervals of the stable MQTLs indicated that several CGs (e.g., TraesCS2A02G141400, TraesCS3B02G040900, TraesCS4D02G323700, TraesCS3B02G077100, and TraesCS4D02G290900) had effects on micronutrients contents, yield, and yield-related traits. The mapping refinements leading to the identification of these CGs provide an opportunity to understand the genetic mechanisms driving quantitative variation for these traits and apply this information for crop improvement programs.

Weed competitive ability in wheat: a peek through in its functional significance, present status and future prospects

Weed competitive ability of a crop is one of the most widely explored aspects in the current scenario of aftermaths of synthetic herbicides such as herbicide resistant weeds emergence, residue accumulation in trophic levels; increased demands of organic produce, global climatic shifts, and other environmental issues. Further weed infestations are known to cause much more economic losses relative to crop attacks by pests. To understand the basic characteristics and underlying processes governing the competitive ability of a crop is therefore prudent, particularly in staples such as wheat. We discuss here an overview of the existing attributes of wheat-weed environment, the significance of crop competitiveness and various associated above-ground and below-ground traits (pertaining to early seed vigor and early seedling germination) discerned through biological, classical genetics and high throughput omics toolbox to provide numerous resources in terms of genome and transcriptome sequences, potential QTLs, genetic variation, molecular markers, association mapping studies, and others. Competitiveness is a cumulative response manifested as morphological, physiological, biochemical or allelochemical response ultimately driven through genetic architecture of a crop and its interaction with environment. Development of wheat competitive cultivar thus requires interdisciplinary approaches and germplasm screening to identify potential donors for competitiveness is an attractive and feasible alternative. For which utilization of landraces and other wild species, already proven to house sufficient genetic heterogeneity, thus poses a competitive advantage. Further, the availability of novel breeding techniques such as rapid generation advance could speed up the development of competitive wheat ideotype.

Genome-Wide Association Study Reveals Novel Genetic Loci for Quantitative Resistance to Septoria Tritici Blotch in Wheat (Triticum aestivum L.)

Septoria tritici blotch, caused by the fungus Zymoseptoria titici, poses serious and persistent challenges to wheat cultivation in Ethiopia and worldwide. Deploying resistant cultivars is a major component of controlling septoria tritici blotch (STB). Thus, the objective of this study was to elucidate the genomic architecture of STB resistance in an association panel of 178 bread wheat genotypes. The association panel was phenotyped for STB resistance, phenology, yield, and yield-related traits in three locations for 2 years. The panel was also genotyped for single nucleotide polymorphism (SNP) markers using the genotyping-by-sequencing (GBS) method, and a total of 7,776 polymorphic SNPs were used in the subsequent analyses. Marker-trait associations were also computed using a genome association and prediction integrated tool (GAPIT). The study then found that the broad-sense heritability for STB resistance ranged from 0.58 to 0.97 and 0.72 to 0.81 at the individual and across-environment levels, respectively, indicating the presence of STB resistance alleles in the association panel. Population structure and principal component analyses detected two sub-groups with greater degrees of admixture. A linkage disequilibrium (LD) analysis in 338,125 marker pairs also detected the existence of significant (p ≤ 0.01) linkage in 27.6% of the marker pairs. Specifically, in all chromosomes, the LD between SNPs declined within 2.26-105.62 Mbp, with an overall mean of 31.44 Mbp. Furthermore, the association analysis identified 53 loci that were significantly (false discovery rate, FDR, <0.05) associated with STB resistance, further pointing to 33 putative quantitative trait loci (QTLs). Most of these shared similar chromosomes with already published Septoria resistance genes, which were distributed across chromosomes 1B, 1D, 2A, 2B, 2D, 3A,3 B, 3D, 4A, 5A, 5B, 6A, 7A, 7B, and 7D. However, five of the putative QTLs identified on chromosomes 1A, 5D, and 6B appeared to be novel. Dissecting the detected loci on IWGSC RefSeq Annotation v2.1 revealed the existence of disease resistance-associated genes in the identified QTL regions that are involved in plant defense responses. These putative QTLs explained 2.7-13.2% of the total phenotypic variation. Seven of the QTLs (R ² = 2.7-10.8%) for STB resistance also co-localized with marker-trait associations (MTAs) for agronomic traits. Overall, this analysis reported on putative QTLs for adult plant resistance to STB and some important agronomic traits. The reported and novel QTLs have been identified previously, indicating the potential to improve STB resistance by pyramiding QTLs by marker-assisted selection.

Understanding the Effects of Growing Seasons, Genotypes, and Their Interactions on the Anthesis Date of Wheat Sown in North China

Simple Summary

Wheat anthesis date is an important turning point for wheat from vegetative growth stage to reproductive growth stage, which is crucial for wheat to adapt to environment and increase grain yield. In this study, a panel of adaptive wheat varieties including historical varieties from the 1940s and current varieties was used to understand the contribution of growing season, genotypes and their interaction effects to anthesis date. Based on our results, we can conclude that growing seasons contributed tremendously to the anthesis date of wheat. In future wheat breeding, more consideration should be given to growing seasons, and the gene combination with the strongest adaptability to the growing seasons should be selected.

Abstract

Quantitative studies on the effects of growing season, genotype (including photoperiod genes and vernalization genes), and their interaction (GGI) on the anthesis date of winter wheat (Triticum aestivum L.) are helpful to provide a scientific reference for selecting or developing adaptive varieties in target environments. In this study, we collected 100 winter wheat varieties with ecological adaptability in North China and identified the anthesis date under field conditions for three consecutive years from 2016 to 2019 with mapped photoperiod and vernalization alleles. Our results showed that the number of the photoperiod-insensitive Ppd-D1a allele increased with variety replacement, while the haplotype Ppd-A1b + Ppd-D1b + vrn-D1 (A4B2) decreased from the 1940s to 2000s. The anthesis date of A4B2 was significantly delayed due to the photoperiod-insensitive alleles Ppd-A1b and Ppd-D1b. The additive main effect and multiplicative interaction (AMMI) model and GGI biplot analysis were used for data analysis. A large portion of the total variation was explained by growing seasons (66.3%), while genotypes and GGIs explained 21.9% and 10.1% of the anthesis dates, respectively. The varieties from the 1940s and before had a great influence on the anthesis date, suggesting these germplasms tend to avoid premature anthesis and could facilitate the development of phenological resilient varieties.

Identification of genetic loci associated with major agronomic traits of wheat (Triticum aestivum L.) based on genome-wide association analysis

BACKGROUND

Bread wheat (Triticum aestivum L.) is one of the most widely consumed cereal crops, but its complex genome makes it difficult to investigate the genetic effect on important agronomic traits. Genome-wide association (GWA) analysis is a useful method to identify genetic loci controlling complex phenotypic traits. With the RNA-sequencing based gene expression analysis, putative candidate genes governing important agronomic trait can be suggested and also molecular markers can be developed.

RESULTS

We observed major quantitative agronomic traits of wheat; the winter survival rate (WSR), days to heading (DTH), days to maturity (DTM), stem length (SL), spike length (SPL), awn length (AL), liter weight (LW), thousand kernel weight (TKW), and the number of seeds per spike (SPS), of 287 wheat accessions from diverse country origins. A significant correlation was observed between the observed traits, and the wheat genotypes were divided into three subpopulations according to the population structure analysis. The best linear unbiased prediction (BLUP) values of the genotypic effect for each trait under different environments were predicted, and these were used for GWA analysis based on a mixed linear model (MLM). A total of 254 highly significant marker-trait associations (MTAs) were identified, and 28 candidate genes closely located to the significant markers were predicted by searching the wheat reference genome and RNAseq data. Further, it was shown that the phenotypic traits were significantly affected by the accumulation of favorable or unfavorable alleles.

CONCLUSIONS

From this study, newly identified MTA and putative agronomically useful genes will help to study molecular mechanism of each phenotypic trait. Further, the agronomically favorable alleles found in this study can be used to develop wheats with superior agronomic traits.

Meta-analysis of genome-wide association studies reveal common loci controlling agronomic and quality traits in a wide range of normal and heat stressed environments

Several stable QTL were detected using metaGWAS analysis for different agronomic and quality traits under 26 normal and heat stressed environments. Heat stress, exacerbated by global warming, has a negative influence on wheat production worldwide and climate resilient cultivars can help mitigate these impacts. Selection decisions should therefore depend on multi-environment experiments representing a range of temperatures at critical stages of development. Here, we applied a meta-genome wide association analysis (metaGWAS) approach to detect stable QTL with significant effects across multiple environments. The metaGWAS was applied to 11 traits scored in 26 trials that were sown at optimal or late times of sowing (TOS1 and TOS2, respectively) at five locations. A total of 2571 unique wheat genotypes (13,959 genotypes across all environments) were included and the analysis conducted on TOS1, TOS2 and both times of sowing combined (TOS1&2). The germplasm was genotyped using a 90 k Infinium chip and imputed to exome sequence level, resulting in 341,195 single nucleotide polymorphisms (SNPs). The average accuracy across all imputed SNPs was high (92.4%). The three metaGWAS analyses revealed 107 QTL for the 11 traits, of which 16 were detected in all three analyses and 23 were detected in TOS1&2 only. The remaining QTL were detected in either TOS1 or TOS2 with or without TOS1&2, reflecting the complex interactions between the environments and the detected QTL. Eight QTL were associated with grain yield and seven with multiple traits. The identified QTL provide an important resource for gene enrichment and fine mapping to further understand the mechanisms of gene × environment interaction under both heat stressed and unstressed conditions.

Single-trait, multi-locus and multi-trait GWAS using four different models for yield traits in bread wheat

A genome-wide association study (GWAS) for 10 yield and yield component traits was conducted using an association panel comprising 225 diverse spring wheat genotypes. The panel was genotyped using 10,904 SNPs and evaluated for three years (2016-2019), which constituted three environments (E1, E2 and E3). Heritability for different traits ranged from 29.21 to 97.69%. Marker-trait associations (MTAs) were identified for each trait using data from each environment separately and also using BLUP values. Four different models were used, which included three single trait models (CMLM, FarmCPU, SUPER) and one multi-trait model (mvLMM). Hundreds of MTAs were obtained using each model, but after Bonferroni correction, only 6 MTAs for 3 traits were available using CMLM, and 21 MTAs for 4 traits were available using FarmCPU; none of the 525 MTAs obtained using SUPER could qualify after Bonferroni correction. Using BLUP, 20 MTAs were available, five of which also figured among MTAs identified for individual environments. Using mvLMM model, after Bonferroni correction, 38 multi-trait MTAs, for 15 different trait combinations were available. Epistatic interactions involving 28 pairs of MTAs were also available for seven of the 10 traits; no epistatic interactions were available for GNPS, PH, and BYPP. As many as 164 putative candidate genes (CGs) were identified using all the 50 MTAs (CMLM, 3; FarmCPU, 9; mvLMM, 6, epistasis, 21 and BLUP, 11 MTAs), which ranged from 20 (CMLM) to 66 (epistasis) CGs. In-silico expression analysis of CGs was also conducted in different tissues at different developmental stages. The information generated through the present study proved useful for developing a better understanding of the genetics of each of the 10 traits; the study also provided novel markers for marker-assisted selection (MAS) to be utilized for the development of wheat cultivars with improved agronomic traits.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01240-1.

Genome-wide association analysis of Mexican bread wheat landraces for resistance to yellow and stem rust

Deploying under-utilized landraces in wheat breeding has been advocated to accelerate genetic gains in current era of genomics assisted breeding. Mexican bread wheat landraces (Creole wheats) represent an important resource for the discovery of novel alleles including disease resistance. A core set of 1,098 Mexican landraces was subjected to multi-location testing for rust diseases in India, Mexico and Kenya. The landrace core set showed a continuous variation for yellow (YR) and stem rust (SR) disease severity. Principal component analysis differentiated Mexican landraces into three groups based on their respective collection sites. Linkage disequilibrium (LD) decay varied from 10 to 32 Mb across chromosomes with an averge of 23Mb across whole genome. Genome-wide association analysis revealed marker-trait associations for YR resistance in India and Mexico as well as for SR resistance in Kenya. In addition, significant additive-additive interaction effects were observed for both YR and SR resistance including genomic regions on chromosomes 1BL and 3BS, which co-locate with pleiotropic genes Yr29/Lr46/Sr58/Pm39/Ltn2 and Sr2/Yr30/Lr27, respectively. Study reports novel genomic associations for YR (chromosomes 1AL, 2BS, and 3BL) and SR (chromosomes 2AL, 4DS, and 5DS). The novel findings in Creole wheat landraces can be efficiently utilized for the wheat genetic improvement.

Genome-Wide Association Study of Morpho-Physiological Traits in Aegilops tauschii to Broaden Wheat Genetic Diversity

Aegilops tauschii, the D-genome donor of bread wheat, is a storehouse of genetic diversity that can be used for wheat improvement. This species consists of two main lineages (TauL1 and TauL2) and one minor lineage (TauL3). Its morpho-physiological diversity is large, with adaptations to a wide ecological range. Identification of allelic diversity in Ae. tauschii is of utmost importance for efficient breeding and widening of the genetic base of wheat. This study aimed at identifying markers or genes associated with morpho-physiological traits in Ae. tauschii, and at understanding the difference in genetic diversity between the two main lineages. We performed genome-wide association studies of 11 morpho-physiological traits of 343 Ae. tauschii accessions representing the entire range of habitats using 34,829 DArTseq markers. We observed a wide range of morpho-physiological variation among all accessions. We identified 23 marker-trait associations (MTAs) in all accessions, 15 specific to TauL1 and eight specific to TauL2, suggesting independent evolution in each lineage. Some of the MTAs could be novel and have not been reported in bread wheat. The markers or genes identified in this study will help reveal the genes controlling the morpho-physiological traits in Ae. tauschii, and thus in bread wheat even if the plant morphology is different.

Genome-Wide Association Study of Tan Spot Resistance in a Hexaploid Wheat Collection From Kazakhstan

Tan spot, caused by Pyrenophora tritici-repentis, is a serious foliar disease of wheat in Kazakhstan with reported yield losses as high as 50% during epidemic years. Here, we report the evaluation of a collection of 191 hexaploid spring and winter wheat lines for tan spot resistance and its underlying genetic architecture using genome-wide association study (GWAS). Our wheat collection comprised candidate varieties from Kazakhstan, Russia, and CIMMYT. It was genotyped using the DArTseq technology and phenotyped for resistance to tan spot at seedling and adult plant stages in Kazakhstan. DArTseq SNPs revealed high genetic diversity (average polymorphic information content = 0.33) in the panel and genome-wide linkage disequilibrium decay at 22 Mb (threshold r² = 0.1). Principal component analysis revealed a clear separation of Eurasian germplasm from CIMMYT and IWWIP lines. GWAS identified 34 marker-trait associations (MTA) for resistance to tan spot and the amount of phenotypic variation explained by these MTA ranged from 4% to 13.7%. Our results suggest the existence of novel valuable resistant alleles on chromosomes 3BS, and 5DL and 6AL for resistance to Race 1 and Race 5, respectively, in addition to known genes tsn1 and tsc2. On chromosome 6AL, a genomic region spanning 3 Mb was identified conferring resistance to both Race 1 and Race 5. Epistatic interaction of associated loci was revealed on chromosomes 1B, 5B, 7B, 5A, and 6A contributing to additional variation of 3.2–11.7%. Twenty-five lines with the best allele combinations of SNPs associated with resistance to both races have been identified as candidates for future variety release and breeding. The results of the present study will be further validated in other independent genetic backgrounds to be able to use markers in breeding.

Genome-wide association study of six quality-related traits in common wheat (Triticum aestivum L.) under two sowing conditions

We identified genomic regions associated with six quality-related traits in wheat under two sowing conditions and analyzed the effects of multienvironment-significant SNPs on the stability of these traits. Grain quality affects the nutritional and commercial value of wheat (Triticum aestivum L.) and is a critical factor influencing consumer preferences for specific wheat varieties. Climate change is predicted to increase environmental stress and thereby reduce wheat quality. Here, we performed a genotyping assay involving the use of the wheat 90 K array in a genome-wide association study of six quality-related traits in 486 wheat accessions under two sowing conditions (normal and late sowing) over 4 years. We identified 64 stable quantitative trait loci (QTL), including 10 for grain protein content, 9 for wet gluten content, 4 for grain starch content, 14 for water absorption, 15 for dough stability time and 12 for grain hardness in wheat under two sowing conditions. These QTL harbored 175 single nucleotide polymorphisms (SNPs), explaining approximately 3-13% of the phenotypic variation in multiple environments. Some QTL on chromosomes 6A and 5D were associated with multiple traits simultaneously, and two (QNGPC.cau-6A, QNGH.cau-5D) harbored known genes, such as NAM-A1 for grain protein content and Pinb for grain hardness, whereas other QTL could facilitate gene discovery. Forty-three SNPs that were detected under late or both normal and late sowing conditions appear to be related to phenotypic stability. The effects of these SNP alleles were confirmed in the association population. The results of this study will be useful for further dissecting the genetic basis of quality-related traits in wheat and developing new wheat cultivars with desirable alleles to improve the stability of grain quality.

Genome-wide association study identifies QTL for thousand grain weight in winter wheat under normal- and late-sown stressed environments

GWAS identified stable loci for TGW and stress tolerance in winter wheat based on two sowing conditions, which will provide opportunities for developing new cultivars with high yield and yield stability. Wheat is an important food crop widely cultivated in the world. Breeding new varieties with high yields and superior adaptability is the main goal of modern wheat breeding program. In order to determine the marker-trait associations (MATs), a set of 688 diverse winter wheat accessions were subjected to genome-wide association study (GWAS) using the wheat 90K array. Field trials under normal-sown (NS) and late-sown (LS) conditions were conducted for thousand grain weight (TGW) and stress susceptibility index (SSI) at three different sites across two consecutive years. A total of 179 (NS) and 158 (LS) MATs corresponded with TGW; of these, 16 and 6 stable MATs for TGW_NS and TGW_LS were identified on chromosomes 1B, 2B, 3A, 3B, 5A, 5B, 5D, 6B, and 7D across at least three environments. Notably, a QTL hot spot controlling TGW under NS and LS conditions was found on chromosome 5A (140-142 cM). Moreover, 8 of 228 stable MATs on chromosomes 4B, 5A, and 5D for SSI were detected. A haplotype block associated with TGW and SSI was located on chromosome 5A at 91 cM, nearby the vernalization gene VRN-A1. Additionally, analysis of wheat varieties from the different eras revealed that the grain weight and stress tolerance are not improved concurrently. Overall, our results provide promising alleles controlling grain weight and stress tolerance (particularly for thermotolerance) for wheat breeders, which can be used in marker-assisted selection for improving grain yield and yield stability in wheat.

A GBS-based GWAS analysis of adaptability and yield traits in bread wheat (Triticum aestivum L.)

Wheat is a foremost food grain of Pakistan and occupies a vital position in agricultural policies of the country. Wheat demand will be increased by 60% by 2050 which is a serious concern to meet this demand. Conventional breeding approaches are not enough to meet the demand of growing human population. It is paramount to integrate underutilized genetic diversity into wheat gene pool through efficient and accurate breeding tools and technology. In this study, we present the genetic analysis of a 312 diverse pre-breeding lines using DArT-seq SNPs seeking to elucidate the genetic components of emergence percentage, heading time, plant height, lodging, thousand kernel weight, and yield (Yd) which resulted in detection of 201 significant (p value < 10^-3) and 61 highly significant associations (p value < 1.45 × 10^-4). More importantly, chromosomes 1B and 2A carried loci linked to Yd in two different seasons, and an increase of up to 8.20% is possible in Yd by positive allele mining. We identified seven lines with > 4 positive alleles for Yd whose pedigree carried Aegilops squarrosa as one of the parents providing evidence that Aegilops species, apart from imparting resistance against biotic stresses, may also provide alleles for yield enhancement.

High-Resolution Genome-wide Association Study Identifies Genomic Regions and Candidate Genes for Important Agronomic Traits in Wheat

Wheat (Triticum aestivum) is a major staple food crop worldwide. Genetic dissection of important agronomic traits is essential for continuous improvement of wheat yield to meet the demand of the world's growing population. We conducted a large-scale genome-wide association study (GWAS) using a panel of 768 wheat cultivars that were genotyped with 327 609 single-nucleotide polymorphisms generated by genotyping-by-sequencing and detected 395 quantitative trait loci (QTLs) for 12 traits under 7 environments. Among them, 273 QTLs were delimited to ≤1.0-Mb intervals and 7 of them are either known genes (Rht-D, Vrn-B1, and Vrn-D1) that have been cloned or known QTLs (TaGA2ox8, APO1, TaSus1-7B, and Rht12) that were previously mapped. Eight putative candidate genes were identified for three QTLs that enhance spike seed setting and grain size using gene expression data and were validated in three bi-parental populations. Protein sequence analysis identified 33 putative wheat orthologs that have high identity with rice genes in QTLs affecting similar traits. Large r² values for additive effects observed among the QTLs for most traits indicated that the phenotypes of these identified QTLs were highly predictable. Results from this study demonstrated that significantly increasing GWAS population size and marker density greatly improves detection and identification of candidate genes underlying a QTL, solidifying the foundation for large-scale QTL fine mapping, candidate gene validation, and developing functional markers for genomics-based breeding in wheat.

Multi-locus genome-wide association studies reveal novel genomic regions associated with vegetative stage salt tolerance in bread wheat (Triticum aestivum L.)

Soil salinity is one of the typical abiotic stresses affecting sustainability of wheat production worldwide. In the present study, we performed a 35 K SNP genotyping assay on association panel of 135 diverse wheat genotypes evaluated for vegetative stage tolerance in hydroponics. Association analyses using five multi-locus GWAS models revealed 42 reliable QTNs for 10 salt tolerance associated traits. Among these 42 reliable QTNs, 9, 17 and 16 QTNs were associated with physiological, biomass and shoot ionic traits respectively. Novel major QTNs were identified for chlorophyll content, shoot fresh weight, seedling total biomass, Na⁺ and K⁺ concentration and Na⁺/K⁺ ratio in shoots. Further, 10 major QTNs showed significant effect on the corresponding salt tolerance traits. Gene ontology analysis of the associated genomic regions identified 58 candidate genes. The information generated in this study will be of potential value for improvement of salt tolerance of wheat cultivars using marker assisted selection.

Appraising the Genetic Architecture of Kernel Traits in Hexaploid Wheat Using GWAS

Kernel morphology is one of the major yield traits of wheat, the genetic architecture of which is always important in crop breeding. In this study, we performed a genome-wide association study (GWAS) to appraise the genetic architecture of the kernel traits of 319 wheat accessions using 22,905 single nucleotide polymorphism (SNP) markers from a wheat 90K SNP array. As a result, 111 and 104 significant SNPs for Kernel traits were detected using four multi-locus GWAS models (mrMLM, FASTmrMLM, FASTmrEMMA, and pLARmEB) and three single-locus models (FarmCPU, MLM, and MLMM), respectively. Among the 111 SNPs detected by the multi-locus models, 24 SNPs were simultaneously detected across multiple models, including seven for kernel length, six for kernel width, six for kernels per spike, and five for thousand kernel weight. Interestingly, the five most stable SNPs (RAC875_29540_391, Kukri_07961_503, tplb0034e07_1581, BS00074341_51, and BobWhite_049_3064) were simultaneously detected by at least three multi-locus models. Integrating these newly developed multi-locus GWAS models to unravel the genetic architecture of kernel traits, the mrMLM approach detected the maximum number of SNPs. Furthermore, a total of 41 putative candidate genes were predicted to likely be involved in the genetic architecture underlining kernel traits. These findings can facilitate a better understanding of the complex genetic mechanisms of kernel traits and may lead to the genetic improvement of grain yield in wheat.

Insights into the Genetic Architecture of Bran Friability and Water Retention Capacity, Two Important Traits for Whole Grain End-Use Quality in Winter Wheat

Bran friability (particle size distribution after milling) and water retention capacity (WRC) impact wheat bran functionality in whole grain milling and baking applications. The goal of this study was to identify genomic regions and underlying genes that may be responsible for these traits. The Hard Winter Wheat Association Mapping Panel, which comprised 299 lines from breeding programs in the Great Plains region of the US, was used in a genome-wide association study. Bran friability ranged from 34.5% to 65.9% (median, 51.1%) and WRC ranged from 159% to 458% (median, 331%). Two single-nucleotide polymorphisms (SNPs) on chromosome 5D were significantly associated with bran friability, accounting for 11-12% of the phenotypic variation. One of these SNPs was located within the Puroindoline-b gene, which is known for influencing endosperm texture. Two SNPs on chromosome 4A were tentatively associated with WRC, accounting for 4.6% and 4.4% of phenotypic variation. The favorable alleles at the SNP sites were present in only 15% (friability) and 34% (WRC) of lines, indicating a need to develop new germplasm for these whole-grain end-use quality traits. Validation of these findings in independent populations will be useful for breeding winter wheat cultivars with improved functionality for whole grain food applications.

MBKbase for rice: an integrated omics knowledgebase for molecular breeding in rice

To date, large amounts of genomic and phenotypic data have been accumulated in the fields of crop genetics and genomic research, and the data are increasing very quickly. However, the bottleneck to using big data in breeding is integrating the data and developing tools for revealing the relationship between genotypes and phenotypes. Here, we report a rice sub-database of an integrated omics knowledgebase (MBKbase-rice, www.mbkbase.org/rice), which integrates rice germplasm information, multiple reference genomes with a united set of gene loci, population sequencing data, phenotypic data, known alleles and gene expression data. In addition to basic data search functions, MBKbase provides advanced web tools for genotype searches at the population level and for visually displaying the relationship between genotypes and phenotypes. Furthermore, the database also provides online tools for comparing two samples by their genotypes and finding target germplasms by genotype or phenotype information, as well as for analyzing the user submitted SNP or sequence data to find important alleles in the germplasm. A soybean sub-database is planned for release in 3 months and wheat and maize will be added in 1–2 years. The data and tools integrated in MBKbase will facilitate research in crop functional genomics and molecular breeding.

Root Growth Adaptation to Climate Change in Crops

Climate change is threatening crop productivity worldwide and new solutions to adapt crops to these environmental changes are urgently needed. Elevated temperatures driven by climate change affect developmental and physiological plant processes that, ultimately, impact on crop yield and quality. Plant roots are responsible for water and nutrients uptake, but changes in soil temperatures alters this process limiting crop growth. With the predicted variable climatic forecast, the development of an efficient root system better adapted to changing soil and environmental conditions is crucial for enhancing crop productivity. Root traits associated with improved adaptation to rising temperatures are increasingly being analyzed to obtain more suitable crop varieties. In this review, we will summarize the current knowledge about the effect of increasing temperatures on root growth and their impact on crop yield. First, we will describe the main alterations in root architecture that different crops undergo in response to warmer soils. Then, we will outline the main coordinated physiological and metabolic changes taking place in roots and aerial parts that modulate the global response of the plant to increased temperatures. We will discuss on some of the main regulatory mechanisms controlling root adaptation to warmer soils, including the activation of heat and oxidative pathways to prevent damage of root cells and disruption of root growth; the interplay between hormonal regulatory pathways and the global changes on gene expression and protein homeostasis. We will also consider that in the field, increasing temperatures are usually associated with other abiotic and biotic stresses such as drought, salinity, nutrient deficiencies, and pathogen infections. We will present recent advances on how the root system is able to integrate and respond to complex and different stimuli in order to adapt to an increasingly changing environment. Finally, we will discuss the new prospects and challenges in this field as well as the more promising pathways for future research.

Genetics of yield, abiotic stress tolerance and biofortification in wheat (Triticum aestivum L.)

A review of the available literature on genetics of yield and its component traits, tolerance to abiotic stresses and biofortification should prove useful for future research in wheat in the genomics era. The work reviewed in this article mainly covers the available information on genetics of some important quantitative traits including yield and its components, tolerance to abiotic stresses (heat, drought, salinity and pre-harvest sprouting = PHS) and biofortification (Fe/Zn and phytate contents with HarvestPlus Program) in wheat. Major emphasis is laid on the recent literature on QTL interval mapping and genome-wide association studies, giving lists of known QTL and marker-trait associations. Candidate genes for different traits and the cloned and characterized genes for yield traits along with the molecular mechanism are also described. For each trait, an account of the present status of marker-assisted selection has also been included. The details of available results have largely been presented in the form of tables; some of these tables are included as supplementary files.

Gains through selection for grain yield in a winter wheat breeding program

Increased genetic gain for complex traits in plant breeding programs can be achieved through different selection strategies. The objective of this study was to compare potential gains for grain yield in a winter wheat breeding program through estimating response to selection R values across several selection approaches including phenotypic (PS), marker-based (MS), genomic (GS), and a combination of PS and GS (PS+GS). Ten populations of Washington State University (WSU) winter wheat breeding lines including a diversity panel and F5 and double haploid lines evaluated from 2015 to 2019 growing seasons for grain yield in Lind and Pullman, WA, USA were used in the study. Selection was conducted by selecting the top 20% of lines based on observed yield (PS strategy), genomic estimated breeding values (GS), presence of yield "enhancing" alleles of the most significant single nucleotide polymorphism (SNP) markers identified from genome-wide association mapping (MS), and high observed yield and estimated breeding values (PS+GS). Overall, PS compared to other individual selection strategies (MS and GS) showed the highest mean response (R = 0.61) within the same environment. When combined with GS, a 23% improvement in R for yield was observed, indicating that gains could be improved by complementing traditional PS with GS within the same environment. Validating selection strategies in different environments resulted in low to negative R values indicating the effects of genotype-by-environment interactions for grain yield. MS was not successful in terms of R relative to the other selection approaches; using this strategy resulted in a significant (P < 0.05) decrease in response to selection compared with the other approaches. An integrated PS+GS approach could result in optimal genetic gain within the same environment, whereas a PS strategy might be a viable option for grain yield validated in different environments. Altogether, we demonstrated that gains through increased response to selection for yield could be achieved in the WSU winter wheat breeding program by implementing different selection strategies either exclusively or in combination.

Morphological and Genetic Diversity within Salt Tolerance Detection in Eighteen Wheat Genotypes

Salinity is a major obstacle to wheat production worldwide. Salt-affected soils could be used by improving salt-tolerant genotypes depending upon the genetic variation and salt stress response of adapted and donor wheat germplasm. We used a comprehensive set of morpho-physiological and biochemical parameters and simple sequence repeat (SSR) marker technique with multivariate analysis to accurately demonstrate the phenotypic and genetic variation of 18 wheat genotypes under salinity stress. All genotypes were evaluated without NaCl as a control and with 150 mM NaCl, until the onset of symptoms of death in the sensitive plant (after 43 days of salinity treatment). The results showed that the relative change of the genetic variation was high for all parameters, heritability (> 60%), and genetic gain (> 20%). Stepwise regression analysis, noting the importance of the root dry matter, relative turgidity, and their respective contributions to the shoot dry matter, indicated their relevance in improving and evaluating the salt-tolerant genotypes of breeding programs. The relative change of the genotypes in terms of the relative turgidity and shoot dry matter during salt stress was verified using clustering methods. For cluster analysis, the genotypes were classified into three groups: tolerant, intermediate, and sensitive, representing five, six, and seven genotypes, respectively. The morphological and genetic distances were significantly correlated based on the Mantel test. Of the 23 SSR markers that showed polymorphism, 17 were associated with almost all examined parameters. Therefore, based on the observed molecular marker-phenotypic trait association, the markers were highly useful in detecting tolerant and sensitive genotypes. Thus, it considers a helpful tool for salt tolerance through marker-assisted selection.