Genome-wide association analysis of agronomic traits in wheat under drought-stressed and non-stressed conditions

Genome-wide scanning to identify and validate single nucleotide polymorphism markers associated with drought tolerance in spring wheat seedlings

Unlike other growth stages of wheat, very few studies on drought tolerance have been done at the seedling stage, and this is due to the complexity and sensitivity of this stage to drought stress resulting from climate change. As a result, the drought tolerance of wheat seedlings is poorly understood and very few genes associated with drought tolerance at this stage were identified. To address this challenge, a set of 172 spring wheat genotypes representing 20 different countries was evaluated under drought stress at the seedling stage. Drought stress was applied on all tested genotypes by water withholding for 13 days. Two types of traits, namely morphological and physiological traits were scored on the leaves of all tested genotypes. Genome-wide association study (GWAS) is one of the effective genetic analysis methods that was used to identify target single nucleotide polymorphism (SNP) markers and candidate genes for later use in marker-assisted selection. The tested plant materials were genotyped using 25k Infinium iSelect array (25K) (herein after it will be identified as 25K) (for 172 genotypes) and genotyping-by-sequencing (GBS) (for 103 genotypes), respectively. The results of genotyping revealed 21,093 25K and 11,362 GBS-SNPs, which were used to perform GWAS analysis for all scored traits. The results of GWAS revealed that 131 and 55 significant SNPs were controlling morphological and physiological traits, respectively. Moreover, a total of eight and seven SNP markers were found to be associated with more than one morphological and physiological trait under drought stress, respectively. Remarkably, 10 significant SNPs found in this study were previously reported for their association with drought tolerance in wheat. Out of the 10 validated SNP markers, four SNPs were associated with drought at the seedling stage, while the remaining six SNPs were associated with drought stress at the reproductive stage. Moreover, the results of gene enrichment revealed 18 and six pathways as highly significant biological and molecular pathways, respectively. The selection based on drought-tolerant alleles revealed 15 genotypes with the highest number of different drought-tolerant alleles. These genotypes can be used as candidate parents in future breeding programs to produce highly drought-tolerant genotypes with high genetic diversity. Our findings in this study provide novel markers and useful information on the genetic basis of drought tolerance at early growth stages.

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.

Reviewing the essential roles of remote phenotyping, GWAS and explainable AI in practical marker-assisted selection for drought-tolerant winter wheat breeding

Marker-assisted selection (MAS) plays a crucial role in crop breeding improving the speed and precision of conventional breeding programmes by quickly and reliably identifying and selecting plants with desired traits. However, the efficacy of MAS depends on several prerequisites, with precise phenotyping being a key aspect of any plant breeding programme. Recent advancements in high-throughput remote phenotyping, facilitated by unmanned aerial vehicles coupled to machine learning, offer a non-destructive and efficient alternative to traditional, time-consuming, and labour-intensive methods. Furthermore, MAS relies on knowledge of marker-trait associations, commonly obtained through genome-wide association studies (GWAS), to understand complex traits such as drought tolerance, including yield components and phenology. However, GWAS has limitations that artificial intelligence (AI) has been shown to partially overcome. Additionally, AI and its explainable variants, which ensure transparency and interpretability, are increasingly being used as recognised problem-solving tools throughout the breeding process. Given these rapid technological advancements, this review provides an overview of state-of-the-art methods and processes underlying each MAS, from phenotyping, genotyping and association analyses to the integration of explainable AI along the entire workflow. In this context, we specifically address the challenges and importance of breeding winter wheat for greater drought tolerance with stable yields, as regional droughts during critical developmental stages pose a threat to winter wheat production. Finally, we explore the transition from scientific progress to practical implementation and discuss ways to bridge the gap between cutting-edge developments and breeders, expediting MAS-based winter wheat breeding for drought tolerance.

Novel SNP markers and other stress-related genomic regions associated with nitrogen use efficiency in cassava

Cassava productivity is constrained by low soil nitrogen, which is predominant in most cassava-growing regions in the tropics and subtropical agroecology. Improving the low nitrogen tolerance of cassava has become an important breeding objective. The current study aimed to develop cassava varieties with improved nitrogen use efficiency by identifying genomic regions and candidate genes linked to nitrogen use efficiency in cassava. A genome-wide association study (GWAS) was performed using the Genome Association and Prediction Integrated Tool (GAPIT). A panel of 265 diverse cassava genotypes was phenotyped for 10 physiological and agronomic traits under optimum and low-nitrogen regimes. Whole-genome genotyping of these cassava cloneswas performed using the Diversity Arrays Technology (DArTseq) sequencing platform. A total of 68,814 single nucleotide polymorphisms (SNPs) were identified, which were spread across the entire 18 chromosomes of the cassava genome, of which 52 SNPs at various densities were found to be associated with nitrogen use efficiency in cassava and other yield-related traits. The putative genes identified through GWAS, especially those with significant associated SNP markers for NUE and related traits have the potential, if deployed appropriately, to develop cassava varieties with improved nitrogen use efficiency, which would translate to a reduction in the economic and environmental cost of cassava production.

Breeding for water-use efficiency in wheat: progress, challenges and prospects

Drought poses a significant challenge to wheat production globally, leading to substantial yield losses and affecting various agronomic and physiological traits. The genetic route offers potential solutions to improve water-use efficiency (WUE) in wheat and mitigate the negative impacts of drought stress. Breeding for drought tolerance involves selecting desirable plants such as efficient water usage, deep root systems, delayed senescence, and late wilting point. Biomarkers, automated and high-throughput techniques, and QTL genes are crucial in enhancing breeding strategies and developing wheat varieties with improved resilience to water scarcity. Moreover, the role of root system architecture (RSA) in water-use efficiency is vital, as roots play a key role in nutrient and water uptake. Genetic engineering techniques offer promising avenues to introduce desirable RSA traits in wheat to enhance drought tolerance. These technologies enable targeted modifications in DNA sequences, facilitating the development of drought-tolerant wheat germplasm. The article highlighted the techniques that could play a role in mitigating drought stress in wheat.

Genomic approaches to enhance adaptive plasticity to cope with soil constraints amidst climate change in wheat

Climate change is varying the availability of resources, soil physicochemical properties, and rainfall events, which collectively determines soil physical and chemical properties. Soil constraints-acidity (pH < 6), salinity (pH ≤ 8.5), sodicity, and dispersion (pH > 8.5)-are major causes of wheat yield loss in arid and semiarid cropping systems. To cope with changing environments, plants employ adaptive strategies such as phenotypic plasticity, a key multifaceted trait, to promote shifts in phenotypes. Adaptive strategies for constrained soils are complex, determined by key functional traits and genotype × environment × management interactions. The understanding of the molecular basis of stress tolerance is particularly challenging for plasticity traits. Advances in sequencing and high-throughput genomics technologies have identified functional alleles in gene-rich regions, haplotypes, candidate genes, mechanisms, and in silico gene expression profiles at various growth developmental stages. Our review focuses on favorable alleles for enhanced gene expression, quantitative trait loci, and epigenetic regulation of plant responses to soil constraints, including heavy metal stress and nutrient limitations. A strategy is then described for quantitative traits in wheat by investigating significant alleles and functional characterization of variants, followed by gene validation using advanced genomic tools, and marker development for molecular breeding and genome editing. Moreover, the review highlights the progress of gene editing in wheat, multiplex gene editing, and novel alleles for smart control of gene expression. Application of these advanced genomic technologies to enhance plasticity traits along with soil management practices will be an effective tool to build yield, stability, and sustainability on constrained soils in the face of climate change.

Heat and Wheat: Adaptation strategies with respect to heat shock proteins and antioxidant potential; an era of climate change

Extreme changes in weather including heat-wave and high-temperature fluctuations are predicted to increase in intensity and duration due to climate change. Wheat being a major staple crop is under severe threat of heat stress especially during the grain-filling stage. Widespread food insecurity underscores the critical need to comprehend crop responses to forthcoming climatic shifts, pivotal for devising adaptive strategies ensuring sustainable crop productivity. This review addresses insights concerning antioxidant, physiological, molecular impacts, tolerance mechanisms, and nanotechnology-based strategies and how wheat copes with heat stress at the reproductive stage. In this study stress resilience strategies were documented for sustainable grain production under heat stress at reproductive stage. Additionally, the mechanisms of heat resilience including gene expression, nanomaterials that trigger transcription factors, (HSPs) during stress, and physiological and antioxidant traits were explored. The most reliable method to improve plant resilience to heat stress must include nano-biotechnology-based strategies, such as the adoption of nano-fertilizers in climate-smart practices and the use of advanced molecular approaches. Notably, the novel resistance genes through advanced molecular approach and nanomaterials exhibit promise for incorporation into wheat cultivars, conferring resilience against imminent adverse environmental conditions. This review will help scientific communities in thermo-tolerance wheat cultivars and new emerging strategies to mitigate the deleterious impact of heat stress.

Association mapping in bambara groundnut [Vigna subterranea (L.) Verdc.] reveals loci associated with agro-morphological traits

BACKGROUND

Genome-wide association studies (GWAS) are important for the acceleration of crop improvement through knowledge of marker-trait association (MTA). This report used DArT SNP markers to successfully perform GWAS on agro-morphological traits using 270 bambara groundnut [Vigna subterranea (L.) Verdc.] landraces sourced from diverse origins. The study aimed to identify marker traits association for nine agronomic traits using GWAS and their candidate genes. The experiment was conducted at two different locations laid out in alpha lattice design. The cowpea [Vigna unguiculata (L.) Walp.] reference genome (i.e. legume genome most closely related to bambara groundnut) assisted in the identification of candidate genes.

RESULTS

The analyses showed that linkage disequilibrium was found to decay rapidly with an average genetic distance of 148 kb. The broadsense heritability was relatively high and ranged from 48.39% (terminal leaf length) to 79.39% (number of pods per plant). The GWAS identified a total of 27 significant marker-trait associations (MTAs) for the nine studied traits explaining 5.27% to 24.86% of phenotypic variations. Among studied traits, the highest number of MTAs was obtained from seed coat colour (6) followed by days to flowering (5), while the least is days to maturity (1), explaining 5.76% to 11.03%, 14.5% to 19.49%, and 11.66% phenotypic variations, respectively. Also, a total of 17 candidate genes were identified, varying in number for different traits; seed coat colour (6), days to flowering (3), terminal leaf length (2), terminal leaf width (2), number of seed per pod (2), pod width (1) and days to maturity (1).

CONCLUSION

These results revealed the prospect of GWAS in identification of SNP variations associated with agronomic traits in bambara groundnut. Also, its present new opportunity to explore GWAS and marker assisted strategies in breeding of bambara groundnut for acceleration of the crop improvement.

Genome-Wide Association Study of Asian and European Common Wheat Accessions for Yield-Related Traits and Stripe Rust Resistance

Identifying novel loci of yield-related traits and resistance to stripe rust (caused by Puccinia striiformis f. sp. tritici) in wheat will help in breeding wheat that can meet projected demands in diverse environmental and agricultural practices. We performed a genome-wide association study with 24,767 single nucleotide polymorphisms (SNPs) in 180 wheat accessions that originated in 16 Asian or European countries between latitudes 30°N and 45°N. We detected seven accessions with desirable yield-related traits and 42 accessions that showed stable, high degrees of stripe rust resistance in multienvironment field assessments. A marker-trait association analysis of yield-related traits detected 18 quantitative trait loci (QTLs) in at least two test environments and two QTLs related to stripe rust resistance in at least three test environments. Five of these QTLs were identified as potentially novel QTLs by comparing their physical locations with those of known QTLs in the Chinese Spring (CS) reference genome RefSeq v1.1 published by the International Wheat Genome Sequencing Consortium; two were for spike length, one was for grain number per spike, one was for spike number, and one was for stripe rust resistance at the adult plant stage. We also identified 14 candidate genes associated with the five novel QTLs. These QTLs and candidate genes will provide breeders with new germplasm and can be used to conduct marker-assisted selection in breeding wheat with improved yield and stripe rust resistance.

Genome-wide association studies for phenological and agronomic traits in mungbean (Vigna radiata L. Wilczek)

Mungbean (Vigna radiata L. Wilczek) is one of the important warm-season food legumes, contributing substantially to nutritional security and environmental sustainability. The genetic complexity of yield-associated agronomic traits in mungbean is not well understood. To dissect the genetic basis of phenological and agronomic traits, we evaluated 153 diverse mungbean genotypes for two phenological (days to heading and days to maturity) and eight agronomic traits (leaf nitrogen status using SPAD, plant height, number of primary branches, pod length, number of pods per plant, seeds per pod, 100-seed weight, and yield per plant) under two environmental conditions. A wide array of phenotypic variability was apparent among the studied genotypes for all the studied traits. The broad sense of heritability of traits ranged from 0.31 to 0.95 and 0.21 to 0.94 at the Delhi and Ludhiana locations, respectively. A total of 55,634 genome-wide single nucleotide polymorphisms (SNPs) were obtained by the genotyping-by-sequencing method, of which 15,926 SNPs were retained for genome-wide association studies (GWAS). GWAS with Bayesian information and linkage-disequilibrium iteratively nested keyway (BLINK) model identified 50 SNPs significantly associated with phenological and agronomic traits. In total, 12 SNPs were found to be significantly associated with phenological traits across environments, explaining 7%-18.5% of phenotypic variability, and 38 SNPs were significantly associated with agronomic traits, explaining 4.7%-27.6% of the phenotypic variability. The maximum number of SNPs (15) were located on chromosome 1, followed by seven SNPs each on chromosomes 2 and 8. The BLAST search identified 19 putative candidate genes that were involved in light signaling, nitrogen responses, phosphorus (P) transport and remobilization, photosynthesis, respiration, metabolic pathways, and regulating growth and development. Digital expression analysis of 19 genes revealed significantly higher expression of 12 genes, viz. VRADI01G08170, VRADI11G09170, VRADI02G00450, VRADI01G00700, VRADI07G14240, VRADI03G06030, VRADI02G14230, VRADI08G01540, VRADI09G02590, VRADI08G00110, VRADI02G14240, and VRADI02G00430 in the roots, cotyledons, seeds, leaves, shoot apical meristems, and flowers. The identified SNPs and putative candidate genes provide valuable genetic information for fostering genomic studies and marker-assisted breeding programs that improve yield and agronomic traits in mungbean.

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.

Genome-wide association mapping of genomic regions associated with drought stress tolerance at seedling and reproductive stages in bread wheat

Understanding the genetic architecture of drought stress tolerance in bread wheat at seedling and reproductive stages is crucial for developing drought-tolerant varieties. In the present study, 192 diverse wheat genotypes, a subset from the Wheat Associated Mapping Initiative (WAMI) panel, were evaluated at the seedling stage in a hydroponics system for chlorophyll content (CL), shoot length (SLT), shoot weight (SWT), root length (RLT), and root weight (RWT) under both drought and optimum conditions. Following that, a genome-wide association study (GWAS) was carried out using the phenotypic data recorded during the hydroponics experiment as well as data available from previously conducted multi-location field trials under optimal and drought stress conditions. The panel had previously been genotyped using the Infinium iSelect 90K SNP array with 26,814 polymorphic markers. Using single as well as multi-locus models, GWAS identified 94 significant marker-trait associations (MTAs) or SNPs associated with traits recorded at the seedling stage and 451 for traits recorded at the reproductive stage. The significant SNPs included several novel, significant, and promising MTAs for different traits. The average LD decay distance for the whole genome was approximately 0.48 Mbp, ranging from 0.07 Mbp (chromosome 6D) to 4.14 Mbp (chromosome 2A). Furthermore, several promising SNPs revealed significant differences among haplotypes for traits such as RLT, RWT, SLT, SWT, and GY under drought stress. Functional annotation and in silico expression analysis revealed important putative candidate genes underlying the identified stable genomic regions such as protein kinases, O-methyltransferases, GroES-like superfamily proteins, NAD-dependent dehydratases, etc. The findings of the present study may be useful for improving yield potential, and stability under drought stress conditions.

Genome-wide association analysis of spike and kernel traits in the U.S. hard winter wheat

A better understanding of the genetic control of spike and kernel traits that have higher heritability can help in the development of high-yielding wheat varieties. Here, we identified the marker-trait associations (MTAs) for various spike- and kernel-related traits in winter wheat (Triticum aestivum L.) through genome-wide association studies (GWAS). An association mapping panel comprising 297 hard winter wheat accessions from the U.S. Great Plains was evaluated for eight spike- and kernel-related traits in three different environments. A GWAS using 15,590 single-nucleotide polymorphisms (SNPs) identified a total of 53 MTAs for seven spike- and kernel-related traits, where the highest number of MTAs were identified for spike length (16) followed by the number of spikelets per spike (15) and spikelet density (11). Out of 53 MTAs, 14 were considered to represent stable quantitative trait loci (QTL) as they were identified in multiple environments. Five multi-trait MTAs were identified for various traits including the number of spikelets per spike (NSPS), spikelet density (SD), kernel width (KW), and kernel area (KA) that could facilitate the pyramiding of yield-contributing traits. Further, a significant additive effect of accumulated favorable alleles on the phenotype of four spike-related traits suggested that breeding lines and cultivars with a higher number of favorable alleles could be a valuable resource for breeders to improve yield-related traits. This study improves the understanding of the genetic basis of yield-related traits in hard winter wheat and provides reliable molecular markers that will facilitate marker-assisted selection (MAS) in wheat breeding programs.

Genome-Wide association analysis of phenotypic traits in Bambara groundnut under drought-stressed and non-stressed conditions based on DArTseq SNP

INTRODUCTION

Bambara groundnut (BG) (Vigna subterranea [L.] Verdc) is an indigenous, resilient, but underutilized leguminous crop that occurs mostly as genetically heterogeneous landraces with limited information on the drought tolerant attributes. This study elucidates the associations between sequencing-based diversity array technology (DArTseq) and phenotypic character as well as differing indices related to drought tolerance in one hundred accessions of Bambara groundnut.

METHODS

The field experiments were conducted at IITA research stations in Kano and Ibadan between 2016 and 2018 planting seasons. The experiments were arranged in randomised complete block design with three replications, under the different water regimes. The phenotypic traits evaluated was further to construct the dendrogram. Genome-wide association mapping was conducted based on 5927 DArTs loci with < 20% missing data.

RESULTS AND DISCUSSIONS

The genome wide association study predicted drought tolerance in Bambara accessions for geometric mean productivity (GMP) and stress tolerance index (STI). TVSu-423 had the highest GMP and STI values (28.50, 2.40), while TVSu-2017 had the lowest at GMP (1.74) and STI (0.01) respectively. The relative water content (%) was significantly higher for accessions; TVSu-266 (60.35, 61.49), TVSu-2 (58.29, 53.94), and TVSu-411 (55.17, 58.92) in 2016/2017 and 2017/2018, respectively. The phenotypic characters studied delineated the accessions into two major clusters and five distinct sub-clusters, indicating variations across all the geographical locations. The 5,927 DArTseq genomic markers in association with STI further grouped the 100 accessions into two main clusters. TVSu-1897 from Botswana (Southern Africa) was in the first cluster, while the remaining 99 accessions from Western, Central, and Eastern Africa made up the second cluster. The eight significant Quantitative Trait Loci (QTLs) (24346377|F|0-22:A>G-22:A>G, 24384105|F|0-56:A>G33 :A> G, 24385643|F|0-53:G>C-53:G>C, 24385696|F|0-43:A>G-43:A>G, 4177257|F|0-44:A>T-44:A>T, 4182070|F|0-66:G>A-66:G>A, 4183483|F|0-24:G>A-24:G>A, 4183904|F|0-11:C>T-11:C>T) identified with Bonferroni threshold was in association with STI, indicative of variations under the drought-stressed condition. The observation of consistent SNPs in the 2016 and 2017 planting seasons, as well as in combination with the 2016 and 2017 planting seasons, led to the designation of these QTLs as significant. The drought selected accessions could form basis for hybridization breeding. The identified quantitative trait loci could be useful in marker-assisted selection in drought molecular breeding programs.

Genome-wide association mapping for component traits of drought tolerance in dry beans (Phaseolus vulgaris L.)

Understanding the genetic basis of traits of economic importance under drought stressed and well-watered conditions is important in enhancing genetic gains in dry beans (Phaseolus vulgaris L.). This research aims to: (i) identify markers associated with agronomic and physiological traits for drought tolerance and (ii) identify drought-related putative candidate genes within the mapped genomic regions. An andean and middle-american diversity panel (AMDP) comprising of 185 genotypes was screened in the field under drought stressed and well-watered conditions for two successive seasons. Agronomic and physiological traits, viz., days to 50% flowering (DFW), plant height (PH), days to physiological maturity (DPM), grain yield (GYD), 100-seed weight (SW), leaf temperature (LT), leaf chlorophyll content (LCC) and stomatal conductance (SC) were phenotyped. Principal component and association analysis were conducted using the filtered 9370 Diversity Arrays Technology sequencing (DArTseq) markers. The mean PH, GYD, SW, DPM, LCC and SC of the panel was reduced by 12.1, 29.6, 10.3, 12.6, 28.5 and 62.0%, respectively under drought stressed conditions. Population structure analysis revealed two sub-populations, which corresponded to the andean and middle-american gene pools. Markers explained 0.08-0.10, 0.22-0.23, 0.29-0.32, 0.43-0.44, 0.65-0.66 and 0.69-0.70 of the total phenotypic variability (R2) for SC, LT, PH, GYD, SW and DFW, respectively under drought stressed conditions. For well-watered conditions, R2 varied from 0.08 (LT) to 0.70 (DPM). Overall, 68 significant (p < 10-03) marker-trait associations (MTAs) and 22 putative candidate genes were identified across drought stressed and well-watered conditions. Most of the identified genes had known biological functions related to regulating the response to drought stress. The findings provide new insights into the genetic architecture of drought stress tolerance in common bean. The findings also provide potential candidate SNPs and putative genes that can be utilized in gene discovery and marker-assisted breeding for drought tolerance after validation.

Genome-Wide Association Study Revealed SNP Alleles Associated with Seed Size Traits in African Yam Bean (Sphenostylis stenocarpa (Hochst ex. A. Rich.) Harms)

Seed size is an important yield and quality-determining trait in higher plants and is also crucial to their evolutionary fitness. In African yam bean (AYB), seed size varies widely among different accessions. However, the genetic basis of such variation has not been adequately documented. A genome-wide marker-trait association study was conducted to identify genomic regions associated with four seed size traits (seed length, seed width, seed thickness, and 100-seed weight) in a panel of 195 AYB accessions. A total of 5416 SNP markers were generated from the diversity array technology sequence (DArTseq) genotype-by-sequencing (GBS)- approach, in which 2491 SNPs were retained after SNP quality control and used for marker-trait association analysis. Significant phenotypic variation was observed for the traits. Broad-sense heritability ranged from 50.0% (seed width) to 66.4% (seed length). The relationships among the traits were positive and significant. Genome-wide association study (GWAS) using the general linear model (GLM) and the mixed linear model (MLM) approaches identified 12 SNP markers significantly associated with seed size traits across the six test environments. The 12 makers explained 6.5-10.8% of the phenotypic variation. Two markers (29420334|F|0-52:C>G-52:C>G and 29420736|F|0-57:G>T-57:G>T) with pleiotropic effects associated with seed width and seed thickness were found. A candidate gene search identified five significant markers (100026424|F|0-37:C>T-37:C>T, 100041049|F|0-42:G>C-42:G>C, 100034480|F|0-31:C>A-31:C>A, 29420365|F|0-55:C>G-55:C>G, and 29420736|F|0-57:G>T-57:G>T) located close to 43 putative genes whose encoding protein products are known to regulate seed size traits. This study revealed significant makers not previously reported for seed size in AYB and could provide useful information for genomic-assisted breeding in AYB.

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 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.

Genetic and morpho-physiological analyses of the tolerance and recovery mechanisms in seedling stage spring wheat under drought stress

Drought is one of the complex abiotic stresses that affect the growth and production of wheat in arid and semiarid countries. In this study, a set of 172 diverse spring wheat genotypes from 20 different countries were assessed under drought stress at the seedling stage. Besides seedling length, two types of traits were recorded, namely: tolerance traits (days to wilting, leaf wilting, and the sum of leaf wilting), and recovery traits (days to regrowth, regrowth biomass, and drought survival rate). In addition, tolerance index, recovery index, and drought tolerance index (DTI) were estimated to select the most drought tolerant genotypes. Moreover, leaf protein content (P), amino acid (AM), proline content (PRO), glucose (G), fructose (F), and total soluble carbohydrates (TSC) were measured under control and drought conditions to study the changes in each physiological trait due to drought stress. All genotypes showed a high significant genetic variation in all the physio-morphological traits scored under drought stress. High phenotypic and genotypic correlations were found among all seedling morphological traits. Among the studied indices, the drought tolerance index (DTI) had the highest phenotypic and genotypic correlations with all tolerance and recovery traits. The broad-sense heritability (H²) estimates were high for morphological traits (83.85–92.27), while the physiological traits ranged from 96.41 to 98.68 under the control conditions and from 97.13 to 99.99 under drought stress. The averages of the physiological traits (proteins, amino acids, proline, glucose, fructose, and total soluble carbohydrates) denoted under drought stress were higher than those recorded under well-watered conditions except for proteins. In this regard, amino acids, glucose, and total soluble carbohydrates had a significant correlation with all morphological traits. The selection for drought tolerance revealed 10 tolerant genotypes from different countries (8 genotypes from Egypt, one from Morocco, and one from the United States). These selected genotypes were screened for the presence of nine specific TaDREB1 alleles. Six primers were polymorphic among the selected genotypes. Genetic diversity among the selected genotypes was investigated using 21,450 SNP markers. The results of the study shed light on the different mechanisms for drought tolerance that wheat plants use to tolerate and survive under drought stress. The genetic analysis performed in this study suggested the most suitable genotypes for selective breeding at the seedling stage under water deficit.

Genetic networks underlying salinity tolerance in wheat uncovered with genome-wide analyses and selective sweeps

A genetic framework underpinning salinity tolerance at reproductive stage was revealed by genome-wide SNP markers and major adaptability genes in synthetic-derived wheats, and trait-associated loci were used to predict phenotypes. Using wild relatives of crops to identify genes related to improved productivity and resilience to climate extremes is a prioritized area of crop genetic improvement. High salinity is a widespread crop production constraint, and development of salt-tolerant cultivars is a sustainable solution. We evaluated a panel of 294 wheat accessions comprising synthetic-derived wheat lines (SYN-DERs) and modern bread wheat advanced lines under control and high salinity conditions at two locations. The GWAS analysis revealed a quantitative genetic framework of more than 200 loci with minor effect underlying salinity tolerance at reproductive stage. The significant trait-associated SNPs were used to predict phenotypes using a GBLUP model, and the prediction accuracy (r²) ranged between 0.57 and 0.74. The r² values for flag leaf weight, days to flowering, biomass, and number of spikes per plant were all above 0.70, validating the phenotypic effects of the loci discovered in this study. Furthermore, the germplasm sets were compared to identify selection sweeps associated with salt tolerance loci in SYN-DERs. Six loci associated with salinity tolerance were found to be differentially selected in the SYN-DERs (12.4 Mb on chromosome (chr)1B, 7.1 Mb on chr2A, 11.2 Mb on chr2D, 200 Mb on chr3D, 600 Mb on chr6B, and 700.9 Mb on chr7B). A total of 228 reported markers and genes, including 17 well-characterized genes, were uncovered using GWAS and EigenGWAS. A linkage disequilibrium (LD) block on chr5A, including the Vrn-A1 gene at 575 Mb and its homeologs on chr5D, were strongly associated with multiple yield-related traits and flowering time under salinity stress conditions. The diversity panel was screened with more than 68 kompetitive allele-specific PCR (KASP) markers of functional genes in wheat, and the pleiotropic effects of superior alleles of Rht-1, TaGASR-A1, and TaCwi-A1 were revealed under salinity stress. To effectively utilize the extensive genetic information obtained from the GWAS analysis, a genetic interaction network was constructed to reveal correlations among the investigated traits. The genetic network data combined with GWAS, selective sweeps, and the functional gene survey provided a quantitative genetic framework for identifying differentially retained loci associated with salinity tolerance in wheat.

Association Analysis for Some Biochemical Traits in Wild Relatives of Wheat under Drought Stress Conditions

In the present study, we estimated genetic diversity and population structure in 186 accessions of Triticum and Aegilops species using 24 simple sequence repeat markers (SSR). Furthermore, an association analysis was performed for antioxidant activities, including guaiacol peroxidase (GPX), ascorbate peroxidase (APX), peroxidase (POX), catalase (CAT), and dry matter (DM) under two control and drought stress conditions. Our findings showed that drought treatment significantly decreased DM, whereas activities of all antioxidant enzymes were increased compared to the control conditions. The results of correlation analysis indicated that, under drought stress conditions, all biochemical traits had a positive and significant association with each other and with dry matter. In the molecular section, the results of the analysis of molecular variance (AMOVA) indicated that the molecular variation within species is more than within them. The dendrogram obtained by cluster analysis showed that grouping the investigated accessions was in accordance with their genomic constitutions. The results of association analysis revealed 8 and 9 significant marker–trait associations (MTA) under control and drought stress conditions, respectively. Among identified MTAs, two associations were simultaneously found in both growing conditions. Moreover, several SSR markers were associated with multiple traits across both conditions. In conclusion, our results could provide worthwhile information regarding marker-assisted selection for the activity of antioxidant enzymes in future breeding programs.

Genetic Improvement of Wheat for Drought Tolerance: Progress, Challenges and Opportunities

Wheat production and productivity are challenged by recurrent droughts associated with climate change globally. Drought and heat stress resilient cultivars can alleviate yield loss in marginal production agro-ecologies. The ability of some crop genotypes to thrive and yield in drought conditions is attributable to the inherent genetic variation and environmental adaptation, presenting opportunities to develop drought-tolerant varieties. Understanding the underlying genetic, physiological, biochemical, and environmental mechanisms and their interactions is key critical opportunity for drought tolerance improvement. Therefore, the objective of this review is to document the progress, challenges, and opportunities in breeding for drought tolerance in wheat. The paper outlines the following key aspects: (1) challenges associated with breeding for adaptation to drought-prone environments, (2) opportunities such as genetic variation in wheat for drought tolerance, selection methods, the interplay between above-ground phenotypic traits and root attributes in drought adaptation and drought-responsive attributes and (3) approaches, technologies and innovations in drought tolerance breeding. In the end, the paper summarises genetic gains and perspectives in drought tolerance breeding in wheat. The review will serve as baseline information for wheat breeders and agronomists to guide the development and deployment of drought-adapted and high-performing new-generation wheat varieties.

Genome-Wide Association Study Identifies Two Loci for Stripe Rust Resistance in a Durum Wheat Panel from Iran

Stripe rust (Puccinia striiformis f. sp. tritici (Pst)) is one of the most devastating fungal diseases of durum wheat (Triticum turgidum L. var. durum Desf.). Races of Pst with new virulence combinations are emerging more regularly on wheat-growing continents, which challenges wheat breeding for resistance. This study aimed to identify and characterize resistance to Pst races based on a genome-wide association study. GWAS is an approach to analyze the associations between a genome-wide set of single-nucleotide polymorphisms (SNPs) and target phenotypic traits. A total of 139 durum wheat accessions from Iran were evaluated at the seedling stage against isolates Pstv-37 and Pstv-40 of Pst and then genotyped using a 15K SNP chip. In total, 230 significant associations were identified across 14 chromosomes, of which 30 were associated with resistance to both isolates. Furthermore, 17 durum wheat landraces showed an immune response against both Pst isolates. The SNP markers and resistant accessions identified in this study may be useful in programs breeding durum wheat for stripe rust resistance.

Combined GWAS and Transcriptome Analyses Provide New Insights Into the Response Mechanisms of Sunflower Against Drought Stress

Sunflower is one of the most important oil crops in the world, and drought stress can severely limit its production and quality. To understand the underlying mechanism of drought tolerance, and identify candidate genes for drought tolerance breeding, we conducted a combined genome-wide association studies (GWAS) and RNA-seq analysis. A total of 226 sunflower inbred lines were collected from different regions of China and other countries. Eight phenotypic traits were evaluated under control and drought stress conditions. Genotyping was performed using a Specific-Locus Amplified Fragment Sequencing (SLAF-seq) approach. A total of 934.08 M paired-end reads were generated, with an average Q30 of 91.97%. Based on the 243,291 polymorphic SLAF tags, a total of 94,162 high-quality SNPs were identified. Subsequent analysis of linkage disequilibrium (LD) and population structure in the 226 accessions was carried out based on the 94,162 high-quality SNPs. The average LD decay across the genome was 20 kb. Admixture analysis indicated that the entire population most likely originated from 11 ancestors. GWAS was performed using three methods (MLM, FarmCPU, and BLINK) simultaneously. A total of 80 SNPs showed significant associations with the 8 traits (p < 1.062 × 10-6). Next, a total of 118 candidate genes were found. To obtain more reliable candidate genes, RNA-seq analysis was subsequently performed. An inbred line with the highest drought tolerance was selected according to phenotypic traits. RNA was extracted from leaves at 0, 7, and 14 days of drought treatment. A total of 18,922 differentially expressed genes were obtained. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis showed up-regulated genes were mainly enriched in the branched-chain amino acid catabolic process, while the down-regulated genes were mainly enriched in the photosynthesis-related process. Six DEGs were randomly selected from all DEGs for validation; these genes showed similar patterns in RNA-seq and RT-qPCR analysis, with a correlation coefficient of 0.8167. Through the integration of the genome-wide association study and the RNA-sequencing, 14 candidate genes were identified. Four of them (LOC110885273, LOC110872899, LOC110891369, LOC110920644) were abscisic acid related protein kinases and transcription factors. These genes may play an important role in sunflower drought response and will be used for further study. Our findings provide new insights into the response mechanisms of sunflowers against drought stress and contribute to further genetic breeding.

Genome-wide association mapping of bread wheat genotypes for sustainable food security and yield potential under limited water conditions

Determining the genetic basis of yield and water deficient tolerance in wheat is vital for wheat breeding programs. Herein, a genome-wide association study (GWAS) was performed for water deficient and yield-related attributes on wheat genotypes with high-density Illumina 90K Infinium SNP array. Major yield and drought-related attributes were phenotyped on a panel of Pakistani and foreign accessions grown in non-stressed and water deficient stressed environments during two crop cycles. Among all accessions, highly significant variations were shown in studied environments for examined characters. Water deficient conditions, reduced the wheat yield and had strong and positive correlation among relative water content and grain yield per plant. Population structure analyses based on 90,000 SNP data, classify the accessions into 4 sub-populations. Marker-trait association analyses (MTA) revealed that 134 significant SNPs were linked with yield and drought tolerance attributes. Pleotropic loci RAC875_s117925_244 and RAC875_c16333_340 located on chromosome 5A and 2A respectively, were significantly linked with relative water contents (RWC), cell membrane thermo-stability (CMT), grain per spike (GPS), spikelet per spike (SPS) and grain yield per plant (GYP). The markers Ra_c58279_684, BobWhite_c23828_341 and IAAV3414 located on chromosomes 2A, 6B and 7B respectively, showed pleotropic effects for RWC, GPS and GYP under both environments. The current experiment not only validated several MTAs reported in other studies but also discovered novel MTAs which significant under drought-stressed conditions. A total of 171 candidate genes were recognized that could be cloned and functionally characterized for the respective associated traits. For RWC and CMT, total 11 and 3 associated SNPs were mapped on coding DNA sequence (CDS) of the identified candidate genes. Isolation and characterization of the candidate genes herein mapped SNPs will be useful in discovering novel genes underpinning drought tolerance in bread wheat to fulfill the wheat demand and sustainable food security under limited water conditions.

SNP-Based Genome-Wide Association Mapping of Pollen Viability Under Heat Stress in Tropical Zea mays L. Inbred Lines

Global environmental changes with more extreme episodes of heat waves are major threats to agricultural productivity. Heat stress in spring affects the reproductive stage of maize, resulting in tassel blast, pollen abortion, poor pollination, reduced seed set, barren ears and ultimately yield loss. As an aneamophelous crop, maize has a propensity for pollen abortion under heat stress conditions. To overcome the existing challenges of heat stress and pollen abortion, this study utilized a broad genetic base of maize germplasm to identify superior alleles to be utilized in breeding programs. A panel of 375 inbred lines was morpho-physiologically screened under normal and heat stress conditions in two locations across two consecutive planting seasons, 2017 and 2018. The exposure of pollen to high temperature showed drastic decline in pollen germination percentage. The average pollen germination percentage (PGP) at 35 and 45°C was 40.3% and 9.7%, respectively, an average decline of 30.6%. A subset of 275 inbred lines were sequenced using tunable genotyping by sequencing, resulting in 170,098 single nucleotide polymorphisms (SNPs) after filtration. Genome wide association of PGP in a subset of 122 inbred lines resulted in ten SNPs associated with PGP35°C (p ≤ 10−5), nine with PGP45°C (p ≤ 10−6–10−8) and ten SNPs associated with PGP ratio (p ≤ 10−5). No SNPs were found to be in common across PGP traits. The number of favorable alleles possessed by each inbred line for PGP35°C, PGP45°C, and the PGP ratio ranged between 4 and 10, 3–13 and 5–13, respectively. In contrast, the number of negative alleles for these traits ranged between 2 and 8, 3–13 and 3–13, respectively. Genetic mapping of yield (adjusted weight per plant, AWP−1) and flowering time (anthesis-silking interval, ASI) in 275 lines revealed five common SNPs: three shared for AWP−1 between normal and heat stress conditions, one for ASI between conditions, and one SNP, CM007648.1-86615409, was associated with both ASI and AWP−1. Variety selection can be performed based on these favorable alleles for various traits. These marker trait associations identified in the diversity panel can be utilized in breeding programs to improve heat stress tolerance in maize.

Identification and mapping of QTL associated with some traits related for drought tolerance in wheat using SSR markers

Background

Wheat is the most important crop around the world. Drought stresses affect wheat production and their characterization. Most of the traits that are affected by drought are quantitative traits, so detection of the quantitative trait’s loci (QTLs) related to these traits is very important for breeder and wheat producers. In this trend, 285 F2 individuals from crosses between four bread wheat genotypes (Triticum aestivum L.), i.e., Sakha93, Sids1, Sakha94, and Gemmiza9, were used for identified QTLs associated with plant height (PH) and leaf wilting (LW). Single marker analysis and composite interval mapping (CIM) were used.

Results

A total of 116 QTLs loci were detected which covered 19 chromosomes out of the 21 chromosomes of wheat. PH and LW had 74 and 42 QTLs loci, respectively. On the other hand, chromosome 7A showed to bear the highest number of QTLs loci (15 loci). While chromosome 1A beard the highest number of QTLs loci related to PH (10 loci), chromosome 2B and 7A beard the highest number of QTLs related LW. We highly recommend our finding to help breeders in wheat breeding programs to improve plant height and leaf wilting.

Conclusion

Our investigation concluded that SSR markers have high efficiency in the identification of QTLs related to abiotic stress; also the CIM method had more advanced priority for QTLs mapping.

Identification of QTLs for Grain Protein Content in Russian Spring Wheat Varieties

Most modern breeding programs aim to develop wheat (T. aestivum L.) varieties with a high grain protein content (GPC) due to its greater milling and cooking quality, and improved grain price. Here, we used a genome-wide association study (GWAS) to map single nucleotide polymorphisms (SNPs) associated with GPC in 93 spring bread wheat varieties developed by eight Russian Breeding Centers. The varieties were evaluated for GPC, grain weight per spike (GWS), and thousand-kernel weight (TKW) at six environments, and genotyped with 9351 polymorphic SNPs and two SNPs associated with the NAM-A1 gene. GPC varied from 9.8 to 20.0%, depending on the genotype and environment. Nearly 52% of the genotypes had a GPC > 14.5%, which is the threshold value for entry into high-class wheat varieties. Broad-sense heritability for GPC was moderate (0.42), which is due to the significant effect of environment and genotype × environment interactions. GWAS performed on mean GPC evaluated across six environments identified eleven significant marker-trait associations, of which nine were physically mapped on chromosome 6A. Screening of wheat varieties for allelic variants of the NAM-A1 gene indicated that 60% of the varieties contained the NAM-A1c allele, followed by 33% for NAM-A1d, and 5% for NAM-A1a alleles. Varieties with the NAM-A1d allele showed significantly (p < 0.01) smaller GPC than those with NAM-A1c and NAM-A1a. However, no significant differences between NAM-A1 alleles were observed for both GWS and TKW.

Identification of Quantitative Trait Loci Hotspots Affecting Agronomic Traits and High-Throughput Vegetation Indices in Rainfed Wheat

Understanding the genetic basis of agronomic traits is essential for wheat breeding programs to develop new cultivars with enhanced grain yield under climate change conditions. The use of high-throughput phenotyping (HTP) technologies for the assessment of agronomic performance through drought-adaptive traits opens new possibilities in plant breeding. HTP together with a genome-wide association study (GWAS) mapping approach can be a useful method to dissect the genetic control of complex traits in wheat to enhance grain yield under drought stress. This study aimed to identify molecular markers associated with agronomic and remotely sensed vegetation index (VI)-related traits under rainfed conditions in bread wheat and to use an in silico candidate gene (CG) approach to search for upregulated CGs under abiotic stress. The plant material consisted of 170 landraces and 184 modern cultivars from the Mediterranean basin. The collection was phenotyped for agronomic and VI traits derived from multispectral images over 3 and 2 years, respectively. The GWAS identified 2,579 marker-trait associations (MTAs). The quantitative trait loci (QTL) overview index statistic detected 11 QTL hotspots involving more than one trait in at least 2 years. A CG analysis detected 12 CGs upregulated under abiotic stress in six QTL hotspots and 46 downregulated CGs in 10 QTL hotspots. The current study highlights the utility of VI to identify chromosome regions that contribute to yield and drought tolerance under rainfed Mediterranean conditions.

Regions of Chromosome 2A of Bread Wheat (Triticum aestivum L.) Associated with Variation in Physiological and Agronomical Traits under Contrasting Water Regimes

Understanding the genetic architecture of drought tolerance is of great importance for overcoming the negative impact of drought on wheat yield. Earlier, we discovered the critical role of chromosome 2A for the drought-tolerant status of wheat spring cultivar Saratovskaya 29. A set of 92 single-chromosome recombinant double haploid (SCRDH) lines were obtained in the genetic background of Saratovskaya 29. The lines carry fragments of chromosome 2A from the drought-sensitive cultivar Yanetzkis Probat. The SCRDH lines were used to identify regions on chromosome 2A associated with the manifestation of physiological and agronomical traits under distinct water supply, and to identify candidate genes that may be associated with adaptive gene networks in wheat. Genotyping was done with Illumina Infinium 15k wheat array using 590 SNP markers with 146 markers being polymorphic. In four identified regions of chromosome 2A, 53 out of 58 QTLs associated with physiological and agronomic traits under contrasting water supply were mapped. Thirty-nine candidate genes were identified, of which 18 were transcription factors. The region 73.8-78.1 cM included the largest number of QTLs and candidate genes. The variation in SNPs associated with agronomical and physiological traits revealed among the SCRDH lines may provide useful information for drought related marker-assisted breeding.

Genome-wide association study of multiple traits linked to heat tolerance in emmer-derived hexaploid wheat genotypes

Heat stress tolerance in plants is a complex trait controlled by multiple genes of minor effect which are influenced by the environment and this makes breeding and selection complicated. Emmer wheat (Triticum dicoccon Schrank) carries valuable diversity that can be used to improve the heat tolerance of modern bread wheat. A diverse set of emmer-based genotypes was developed by crossing emmer wheat with hexaploid wheat. These materials, along with their hexaploid recurrent parents and commercial cultivars, were evaluated at optimum (E1) and heat stressed (E2) sowing times in the field for three consecutive years (2014-2016). The material was genotyped using the Infinium iSelect SNP 90K SNP Assay. The phenotypic data were combined across years within each sowing time and best linear unbiased estimators calculated for each genotype in each environment. These estimates were used for GWAS analysis. Significant phenotypic and genotypic variation was observed for all traits. A total of 125 and 142 marker-trait associations (MTAs) were identified in E1 and E2, respectively. The highest number of MTAs were observed on the A genome (106), followed by the B (105) and D (56) genomes. MTAs with pleiotropic effects within and across the environments were observed. Many of the MTAs found were reported previously for various traits, and a few significant MTAs under heat stress were new and linked to emmer genome. Genomic regions identified on chromosomes 2B and 3A had a significant positive impact on grain yield under stress with a 7% allelic effect. Genomic regions on chromosomes 1A and 4B contributed 11% and 9% of the variation for thousand kernel weight (TKW) under heat stress respectively. Following fine mapping, these regions could be used for marker-assisted selection to improve heat tolerance in wheat.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01222-3.

Labelling Selective Sweeps Used in Durum Wheat Breeding from a Diverse and Structured Panel of Landraces and Cultivars

Simple Summary

Evaluation of the genetic diversity of a crop species is a critical step for breeding. Landraces are essential to avoid genetic erosion, and Mediterranean landraces are an important group of genetic resources due to their high genetic variability, adaptation to local conditions in rainfed environments, and their resilience to pests and pathogens. This study uses a genome-wide association approach employing eigenvectors to identify selective sweeps among Mediterranean durum wheat landraces and a world panel of modern cultivars.

Abstract

A panel of 387 durum wheat genotypes including Mediterranean landraces and modern cultivars was characterized with 46,161 diversity arrays technology (DArTseq) markers. Analysis of population structure uncovered the existence of five subpopulations (SP) related to the pattern of migration of durum wheat from the domestication area to the west of the Mediterranean basin (SPs 1, 2, and 3) and further improved germplasm (SPs 4 and 5). The total genetic diversity (H_T) was 0.40 with a genetic differentiation (G_ST) of 0.08 and a mean gene flow among SPs of 6.02. The lowest gene flow was detected between SP 1 (presumably the ancient genetic pool of the panel) and SPs 4 and 5. However, gene flow from SP 2 to modern cultivars was much higher. The highest gene flow was detected between SP 3 (western Mediterranean germplasm) and SP 5 (North American and European cultivars). A genome wide association study (GWAS) approach using the top ten eigenvectors as phenotypic data revealed the presence of 89 selective sweeps, represented as quantitative trait loci (QTL) hotspots, widely distributed across the durum wheat genome. A principal component analysis (PCoA) using 147 markers with −log₁₀p > 5 identified three regions located on chromosomes 2A, 2B and 3A as the main drivers for differentiation of Mediterranean landraces. Gene flow between SPs offers clues regarding the putative use of Mediterranean old durum germplasm by the breeding programs represented in the structure analysis. EigenGWAS identified selective sweeps among landraces and modern cultivars. The analysis of the corresponding genomic regions in the ‘Zavitan’, ‘Svevo’ and ‘Chinese Spring’ genomes discovered the presence of important functional genes including Ppd, Vrn, Rht, and gene models involved in important biological processes including LRR-RLK, MADS-box, NAC, and F-box.

Genetic diversity and population structure of early and extra-early maturing maize germplasm adapted to sub-Saharan Africa

BACKGROUND

Assessment and effective utilization of genetic diversity in breeding programs is crucial for sustainable genetic improvement and rapid adaptation to changing breeding objectives. During the past two decades, the commercialization of the early and extra-early maturing cultivars has contributed to rapid expansion of maize into different agro-ecologies of sub-Saharan Africa (SSA) where maize has become an important component of the agricultural economy and played a vital role in food and nutritional security. The present study aimed at understanding the population structure and genetic variability among 439 early and extra-early maize inbred lines developed from three narrow-based and twenty-seven broad-based populations by the International Iinstitute of Tropical Agriculture Maize Improvement Program (IITA-MIP). These inbreds were genotyped using 9642 DArTseq-based single nucleotide polymorphism (SNP) markers distributed uniformly throughout the maize genome.

RESULTS

About 40.8% SNP markers were found highly informative and exhibited polymorphic information content (PIC) greater than 0.25. The minor allele frequency and PIC ranged from 0.015 to 0.500 and 0.029 to 0.375, respectively. The STRUCTURE, neighbour-joining phylogenetic tree and principal coordinate analysis (PCoA) grouped the inbred lines into four major classes generally consistent with the selection history, ancestry and kernel colour of the inbreds but indicated a complex pattern of the genetic structure. The pattern of grouping of the lines based on the STRUCTURE analysis was in concordance with the results of the PCoA and suggested greater number of sub-populations (K = 10). Generally, the classification of the inbred lines into heterotic groups based on SNP markers was reasonably reliable and in agreement with defined heterotic groups of previously identified testers based on combining ability studies.

CONCLUSIONS

Complete understanding of potential heterotic groups would be difficult to portray by depending solely on molecular markers. Therefore, planned crosses involving representative testers from opposing heterotic groups would be required to refine the existing heterotic groups. It is anticipated that the present set of inbreds could contribute new beneficial alleles for population improvement, development of hybrids and lines with potential to strengthen future breeding programs. Results of this study would help breeders in formulating breeding strategies for genetic enhancement and sustainable maize production in SSA.

Exploitation of Tolerance of Wheat Kernel Weight and Shape-Related Traits from Aegilops tauschii under Heat and Combined Heat-Drought Stresses

Kernel weight and shape-related traits are inherited stably and increase wheat yield. Narrow genetic diversity limits the progress of wheat breeding. Here, we evaluated kernel weight and shape-related traits and applied genome-wide association analysis to a panel of wheat multiple synthetic derivative (MSD) lines. The MSD lines harbored genomic fragments from Aegilops tauschii. These materials were grown under optimum conditions in Japan, as well as under heat and combined heat-drought conditions in Sudan. We aimed to explore useful QTLs for kernel weight and shape-related traits under stress conditions. These can be useful for enhancing yield under stress conditions. MSD lines possessed remarkable genetic variation for all traits under all conditions, and some lines showed better performance than the background parent Norin 61. We identified 82 marker trait associations (MTAs) under the three conditions; most of them originated from the D genome. All of the favorable alleles originated from Ae. tauschii. For the first time, we identified markers on chromosome 5D associated with a candidate gene encoding a RING-type E3 ubiquitin-protein ligase and expected to have a role in regulating wheat seed size. Our study provides important knowledge for the improvement of wheat yield under optimum and stress conditions. The results emphasize the importance of Ae. tauschii as a gene reservoir for wheat breeding.

Genome-wide association study of yield and related traits in common wheat under salt-stress conditions

BACKGROUND

Soil salinization is a major threat to wheat production. It is essential to understand the genetic basis of salt tolerance for breeding and selecting new salt-tolerant cultivars that have the potential to increase wheat yield.

RESULT

In this study, a panel of 191 wheat accessions was subjected to genome wide association study (GWAS) to identify SNP markers linked with adult-stage characters. The population was genotyped by Wheat660K SNP array and eight phenotype traits were investigated under low and high salinity environments for three consecutive years. A total of 389 SNPs representing 11 QTLs were significantly associated with plant height, spike number, spike length, grain number, thousand kernels weight, yield and biological mass under different salt treatments, with the phenotypic explanation rate (R²) ranging from 9.14 to 50.45%. Of these, repetitive and pleiotropic loci on chromosomes 4A, 5A, 5B and 7A were significantly linked to yield and yield related traits such as thousand kernels weight, spike number, spike length, grain number and so on under low salinity conditions. Spike length-related loci were mainly located on chromosomes 1B, 3B, 5B and 7A under different salt treatments. Two loci on chromosome 4D and 5A were related with plant height in low and high salinity environment, respectively. Three salt-tolerant related loci were confirmed to be important in two bi-parental populations. Distribution of favorable haplotypes indicated that superior haplotypes of pleiotropic loci on group-5 chromosomes were strongly selected and had potential for increasing wheat salt tolerance. A total of 14 KASP markers were developed for nine loci associating with yield and related traits to improve the selection efficiency of wheat salt-tolerance breeding.

CONCLUSION

Utilizing a Wheat660K SNPs chip, QTLs for yield and its related traits were detected under salt treatment in a natural wheat population. Important salt-tolerant related loci were validated in RIL and DH populations. This study provided reliable molecular markers that could be crucial for marker-assisted selection in wheat salt tolerance breeding programs.

Population structure and genetic diversity analyses of common bean germplasm collections of East and Southern Africa using morphological traits and high-density SNP markers

Knowledge of genetic diversity in plant germplasm and the relationship between genetic factors and phenotypic expression is vital for crop improvement. This study's objectives were to understand the extent of genetic diversity and population structure in 60 common bean genotypes from East and Southern Africa. The common bean genotypes exhibited significant (p<0.05) levels of variability for traits such as days to flowering (DTF), days to maturity (DTM), number of pods per plant (NPP), number of seeds per pod (NSP), and grain yield per hectare in kilograms (GYD). About 47.82 per cent of the variation among the genotypes was explained by seven principal components (PC) associated with the following agronomic traits: NPP, NFF (nodes to first flower), DTF, GH (growth habit) and GYD. The SNP markers revealed mean gene diversity and polymorphic information content values of 0.38 and 0.25, respectively, which suggested the presence of considerable genetic variation among the assessed genotypes. Analysis of molecular variance showed that 51% of the genetic variation were between the gene pools, while 49% of the variation were within the gene pools. The genotypes were delineated into two distinct groups through the population structure, cluster and phylogenetic analyses. Genetically divergent genotypes such as DRK57, MW3915, NUA59, and VTTT924/4-4 with high yield and agronomic potential were identified, which may be useful for common bean improvement.

Population structure of Nepali spring wheat (Triticum aestivum L.) germplasm

BACKGROUND

Appropriate information about genetic diversity and population structure of germplasm improves the efficiency of plant breeding. The low productivity of Nepali bread wheat (Triticum aestivum L.) is a major concern particularly since Nepal is ranked the 4th most vulnerable nation globally to climate change. The genetic diversity and population structure of Nepali spring wheat have not been reported. This study aims to improve the exploitation of more diverse and under-utilized genetic resources to contribute to current and future breeding efforts for global food security.

RESULTS

We used genotyping-by-sequencing (GBS) to characterize a panel of 318 spring wheat accessions from Nepal including 166 landraces, 115 CIMMYT advanced lines, and 34 Nepali released varieties. We identified 95 K high-quality SNPs. The greatest genetic diversity was observed among the landraces, followed by CIMMYT lines, and released varieties. Though we expected only 3 groupings corresponding to these 3 seed origins, the population structure revealed two large, distinct subpopulations along with two smaller and scattered subpopulations in between, with significant admixture. This result was confirmed by principal component analysis (PCA) and UPGMA distance-based clustering. The pattern of LD decay differed between subpopulations, ranging from 60 to 150 Kb. We discuss the possibility that germplasm explorations during the 1970s-1990s may have mistakenly collected exotic germplasm instead of local landraces and/or collected materials that had already cross-hybridized since exotic germplasm was introduced starting in the 1950s.

CONCLUSION

We suggest that only a subset of wheat "landraces" in Nepal are authentic which this study has identified. Targeting these authentic landraces may accelerate local breeding programs to improve the food security of this climate-vulnerable nation. Overall, this study provides a novel understanding of the genetic diversity of wheat in Nepal and this may contribute to global wheat breeding initiatives.

Genome-Wide Association Mapping of Seedling Drought Tolerance in Winter Wheat

In the southern Great Plains of the United States, winter wheat grown for dual-purpose is often planted early, which puts it at risk for drought stress at the seedling stage in the autumn. To map quantitative trait loci (QTL) associated with seedling drought tolerance, a genome-wide association study (GWAS) was performed on a hard winter wheat association mapping panel. Two sets of plants were planted in the greenhouse initially under well-watered conditions. At the five-leaf stage, one set continued to receive the optimum amount of water, whereas watering was withdrawn from the other set (drought stress treatment) for 14 days to mimic drought stress. Large phenotypic variation was observed in leaf chlorophyll content, leaf chlorophyll fluorescence, shoot length, number of leaves per seedling, and seedling recovery. A mixed linear model analysis detected multiple significant QTL associated with seedling drought tolerance-related traits on chromosomes 1B, 2A, 2B, 2D, 3A, 3B, 3D, 4B, 5A, 5B, 6B, and 7B. Among those, 12 stable QTL responding to drought stress for various traits were identified. Shoot length and leaf chlorophyll fluorescence were good indicators in responding to drought stress because most of the drought responding QTL detected using means of these two traits were also detected in at least two experimental repeats. These stable QTL are more valuable for use in marker-assisted selection during wheat breeding. Moreover, different traits were mapped on several common chromosomes, such as 1B, 2B, 3B, and 6B, and two QTL clusters associated with three or more traits were located at 107-130 and 80-83 cM on chromosomes 2B and 6B, respectively. Furthermore, some QTL detected in this study co-localized with previously reported QTL for root and shoot traits at the seedling stage and canopy temperature at the grain-filling stage of wheat. In addition, several of the mapped chromosomes were also associated with drought tolerance during the flowering or grain-filling stage in wheat. Some significant single-nucleotide polymorphisms (SNPs) were aligned to candidate genes playing roles in plant abiotic stress responses. The SNP markers identified in this study will be further validated and used for marker-assisted breeding of seedling drought tolerance during dual-purpose wheat breeding.

Genome-wide association study of leaf rust resistance in Russian spring wheat varieties

BACKGROUND

Leaf rust (Puccinia triticina Eriks.) is one of the most dangerous diseases of common wheat worldwide. Three approaches: genome-wide association study (GWAS), marker-assisted selection (MAS) and phytopathological evaluation in field, were used for assessment of the genetic diversity of Russian spring wheat varieties on leaf rust resistance loci and for identification of associated molecular markers.

RESULTS

The collection, consisting of 100 Russian varieties of spring wheat, was evaluated over three seasons for resistance to the native population of leaf rust specific to the West Siberian region of Russia. The results indicated that most cultivars showed high susceptibility to P. triticina, with severity ratings (SR) of 60S-90S, however some cultivars showed a high level of leaf rust resistance (SR < 20MR-R). Based on the results of genome-wide association studies (GWAS) performed using the wheat 15 K genotyping array, 20 SNPs located on chromosomes 6D, 6A, 6B, 5A, 1B, 2A, 2B and 7A were revealed to be associated with leaf rust resistance. Genotyping with markers developed for known leaf rust resistance genes showed that most of the varieties contain genes Lr1, Lr3a, Lr9, Lr10, Lr17a, Lr20, Lr26 and Lr34, which are not currently effective against the pathogen. In the genome of three wheat varieties, gene Lr6Ai = 2 inherited from Th. intermedium was detected, which provides complete protection against the rust pathogen. It has been suggested that the QTL mapped to the chromosome 5AS of wheat cultivar Tulaikovskaya-zolotistaya, Tulaikovskaya-10, Samsar, and Volgouralskaya may be a new, previously undescribed locus conferring resistance to leaf rust. Obtained results also indicate that chromosome 1BL of the varieties Sonata, Otrada-Sibiri, Tertsiya, Omskaya-23, Tulaikovskaya-1, Obskaya-14, and Sirena may contain an unknown locus that provides a resistance response to local population.

CONCLUSIONS

This study provides new insights into the genetic basis of resistance to leaf rust in Russian spring wheat varieties. The SNPs significantly associated with leaf rust resistance can be used for the development and application of diagnostic markers in marker-assisted selection schemes.

Association analysis between agronomic traits and AFLP markers in a wide germplasm of proso millet (Panicum miliaceum L.) under normal and salinity stress conditions

BACKGROUND

Proso millet is a highly nutritious cereal considered an essential component of processed foods. It is also recognized with high water-use efficiency as well as short growing seasons. This research was primarily aimed at investigating the genetic diversity among genotypes based on evaluating those important traits proposed in previous researches under both normal and salinity- stress conditions. Use of Amplified fragment length polymorphism (AFLP) molecular markers as well as evaluating the association between markers and the investigated traits under both conditions was also another purpose of this research.

RESULTS

According to the phenotypic correlation coefficients, the seed yield had the highest correlation with the forage and biological yields under both conditions. By disintegrating those traits investigated under normal and salinity-stress conditions into principal component analysis, it was found that the first four principal components justified more than 59.94 and 62.48% of the whole variance, respectively. The dendrogram obtained by cluster analysis displayed three groups of genotypes under both normal and salinity- stress conditions. Then, association analyses were conducted on 143 proso millet genotypes and 15 agronomic traits as well as 514 polymorphic AFLP markers (out of 866 created bands) generated by 11 primer combinations (out of the initial 20 primer combinations) EcoRI/MseI. The results obtained by mixed linear model (MLM) indicated that under normal conditions, the M14/E10-45 and M14/E10-60 markers had strong associations with seed yield. A similar trend was also observed for M14/E10-45 and M14/E11-44 markers in relation to forage yield. On the other hand, M14/E10-14, M14/E10-64 markers (for seed yield) and M14/E10-64 marker (for forage yield), had significant and stable association in all environments under salinity-stress conditions. Moreover, a number of markers showed considerable associations and stability under both normal and salinity stress conditions.

CONCLUSIONS

According to the analysis of phenotypic data, the wide germplasm of Iranian proso millet has significant variation in terms of measured traits. It can be concluded that markers showing strong associations with traits under salinity-stress conditions are suitable candidates to be used in future marker-assisted selection (MAS) studies to improve salinity-resistance genotypes of Panicum miliaceum in arid and semiarid areas.

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.

Recent Progress in Germplasm Evaluation and Gene Mapping to Enable Breeding of Drought-Tolerant Wheat

There is a need to increase wheat productivity to meet the food demands of the ever-growing human population. However, accelerated development of high yielding varieties is hindered by drought, which is worsening due to climate change. In this context, germplasm diversity is central to the development of drought-tolerant wheat. Extensive collections of these genetic resources are conserved in national and international genebanks. In addition to phenotypic assessments, the use of advanced molecular techniques (e.g., genotype by sequencing) to identify quantitative trait loci (QTLs) for drought tolerance related traits is useful for genome- and marker-assisted selection based approaches. Therefore, to assist wheat breeders at a critical time, we searched the recent peer-reviewed literature (2011-current), first, to identify wheat germplasm observed to be useful genetic sources for drought tolerance, and second, to report QTLs associated with drought tolerance. Though many breeders limit the parents used in breeding programs to a familiar core collection, the results of this review show that larger germplasm collections have been sources of useful genes for drought tolerance in wheat. The review also demonstrates that QTLs for drought tolerance in wheat are associated with diverse physio-morphological traits, at different growth stages. Here, we also briefly discuss the potential of genome engineering/editing to improve drought tolerance in wheat. The use of CRISPR-Cas9 and other gene-editing technologies can be used to fine-tune the expression of genes controlling drought adaptive traits, while high throughput phenotyping (HTP) techniques can potentially accelerate the selection process. These efforts are empowered by wheat researcher consortia.

PANOMICS meets germplasm

Genotyping-by-sequencing has enabled approaches for genomic selection to improve yield, stress resistance and nutritional value. More and more resource studies are emerging providing 1000 and more genotypes and millions of SNPs for one species covering a hitherto inaccessible intraspecific genetic variation. The larger the databases are growing, the better statistical approaches for genomic selection will be available. However, there are clear limitations on the statistical but also on the biological part. Intraspecific genetic variation is able to explain a high proportion of the phenotypes, but a large part of phenotypic plasticity also stems from environmentally driven transcriptional, post-transcriptional, translational, post-translational, epigenetic and metabolic regulation. Moreover, regulation of the same gene can have different phenotypic outputs in different environments. Consequently, to explain and understand environment-dependent phenotypic plasticity based on the available genotype variation we have to integrate the analysis of further molecular levels reflecting the complete information flow from the gene to metabolism to phenotype. Interestingly, metabolomics platforms are already more cost-effective than NGS platforms and are decisive for the prediction of nutritional value or stress resistance. Here, we propose three fundamental pillars for future breeding strategies in the framework of Green Systems Biology: (i) combining genome selection with environment-dependent PANOMICS analysis and deep learning to improve prediction accuracy for marker-dependent trait performance; (ii) PANOMICS resolution at subtissue, cellular and subcellular level provides information about fundamental functions of selected markers; (iii) combining PANOMICS with genome editing and speed breeding tools to accelerate and enhance large-scale functional validation of trait-specific precision breeding.

PANOMICS meets germplasm

Genotyping-by-sequencing has enabled approaches for genomic selection to improve yield, stress resistance and nutritional value. More and more resource studies are emerging providing 1000 and more genotypes and millions of SNPs for one species covering a hitherto inaccessible intraspecific genetic variation. The larger the databases are growing, the better statistical approaches for genomic selection will be available. However, there are clear limitations on the statistical but also on the biological part. Intraspecific genetic variation is able to explain a high proportion of the phenotypes, but a large part of phenotypic plasticity also stems from environmentally driven transcriptional, post-transcriptional, translational, post-translational, epigenetic and metabolic regulation. Moreover, regulation of the same gene can have different phenotypic outputs in different environments. Consequently, to explain and understand environment-dependent phenotypic plasticity based on the available genotype variation we have to integrate the analysis of further molecular levels reflecting the complete information flow from the gene to metabolism to phenotype. Interestingly, metabolomics platforms are already more cost-effective than NGS platforms and are decisive for the prediction of nutritional value or stress resistance. Here, we propose three fundamental pillars for future breeding strategies in the framework of Green Systems Biology: (i) combining genome selection with environment-dependent PANOMICS analysis and deep learning to improve prediction accuracy for marker-dependent trait performance; (ii) PANOMICS resolution at subtissue, cellular and subcellular level provides information about fundamental functions of selected markers; (iii) combining PANOMICS with genome editing and speed breeding tools to accelerate and enhance large-scale functional validation of trait-specific precision breeding.

A Genome-Wide Association Study of Coleoptile Length in Different Chinese Wheat Landraces

From the perspective of wheat yield improvement, the coleoptile is vital for successful crop establishment, and long coleoptile lengths (CLs) are preferred in wheat-growing regions where deep planting is practiced. To determine the genetic basis of CL, we performed a genome-wide association study on a set of 707 Chinese wheat landraces using 18,594 single-nucleotide polymorphisms and 38,678 diversity array technology sequencing markers. We accordingly detected a total of 29 significant markers [-log₁₀ ^(P) > 4.76] distributed on chromosomes 2B, 2D, 3A, 4A, 5A, 6A, 6B, 6D, and 7B. Based on linkage disequilibrium decay distance, we identified a total of 17 quantitative trait loci associated with CL, among which QCl.sicau-6B.2, located at 508.17-509.26 Mb on chromosome 6B, was recognized as a novel major locus. We subsequently developed a high-resolution melt marker for QCl.sicau-6B.2, which was validated in an F _{2 : 3} population. Our findings provide important insights into the genetic mechanisms underlying coleoptile growth and could be applied to marker-assisted wheat selection.

Combining QTL Analysis and Genomic Predictions for Four Durum Wheat Populations Under Drought Conditions

Durum wheat is an important crop for the human diet and its consumption is gaining popularity. In order to ensure that durum wheat production maintains the pace with the increase in demand, it is necessary to raise productivity by approximately 1.5% per year. To deliver this level of annual genetic gain the incorporation of molecular strategies has been proposed as a key solution. Here, four RILs populations were used to conduct QTL discovery for grain yield (GY) and 1,000 kernel weight (TKW). A total of 576 individuals were sown at three locations in Morocco and one in Lebanon. These individuals were genotyped by sequencing with 3,202 high-confidence polymorphic markers, to derive a consensus genetic map of 2,705.7 cM, which was used to impute any missing data. Six QTLs were found to be associated with GY and independent from flowering time on chromosomes 2B, 4A, 5B, 7A and 7B, explaining a phenotypic variation (PV) ranging from 4.3 to 13.4%. The same populations were used to train genomic prediction models incorporating the relationship matrix, the genotype by environment interaction, and marker by environment interaction, to reveal significant advantages for models incorporating the marker effect. Using training populations (TP) in full sibs relationships with the validation population (VP) was shown to be the only effective strategy, with accuracies reaching 0.35–0.47 for GY. Reducing the number of markers to 10% of the whole set, and the TP size to 20% resulted in non-significant changes in accuracies. The QTLs identified were also incorporated in the models as fixed effects, showing significant accuracy gain for all four populations. Our results confirm that the prediction accuracy depends considerably on the relatedness between TP and VP, but not on the number of markers and size of TP used. Furthermore, feeding the model with information on markers associated with QTLs increased the overall accuracy.

Genome-wide association study of Striga resistance in early maturing white tropical maize inbred lines

BACKGROUND

Striga hermonthica (Benth.) parasitism militates against increased maize production and productivity in savannas of sub-Saharan Africa (SSA). Identification of Striga resistance genes is important in developing genotypes with durable resistance. So far, there is only one report on the existence of QTL for Striga resistance on chromosome 6 of maize. The objective of this study was to identify genomic regions significantly associated with grain yield and other agronomic traits under artificial Striga field infestation. A panel of 132 early-maturing maize inbreds were phenotyped for key agronomic traits under Striga-infested and Striga-free conditions. The inbred lines were also genotyped using 47,440 DArTseq markers from which 7224 markers were retained for population structure analysis and genome-wide association study (GWAS).

RESULTS

The inbred lines were grouped into two major clusters based on structure analysis as well as the neighbor-joining hierarchical clustering. A total of 24 SNPs significantly associated with grain yield, Striga damage at 8 and 10 weeks after planting (WAP), ears per plant and ear aspect under Striga infestation were detected. Under Striga-free conditions, 11 SNPs significantly associated with grain yield, number of ears per plant and ear aspect were identified. Three markers physically located close to the putative genes GRMZM2G164743 (bin 10.05), GRMZM2G060216 (bin 3.06) and GRMZM2G103085 (bin 5.07) were detected, linked to grain yield, Striga damage at 8 and 10 WAP and number of ears per plant under Striga infestation, explaining 9 to 42% of the phenotypic variance. Furthermore, the S9_154,978,426 locus on chromosome 9 was found at 2.61 Mb close to the ZmCCD1 gene known to be associated with the reduction of strigolactone production in the maize roots.

CONCLUSIONS

Presented in this study is the first report of the identification of significant loci on chromosomes 9 and 10 of maize that are closely linked to ZmCCD1 and amt5 genes, respectively and may be related to plant defense mechanisms against Striga parasitism. After validation, the identified loci could be targets for breeders for marker-assisted selection (MAS) to accelerate genetic enhancement of maize for Striga resistance in the tropics, particularly in SSA, where the parasitic weed is endemic.

Identification and mapping of a new recessive dwarfing gene dw9 on the 6RL rye chromosome and its phenotypic effects

The introduction of high-yielding semi-dwarf varieties of wheat into cultivation has led to a "green revolution." This has required intensive research into various sources of dwarfism in wheat. However, there has been very little advancement in research on dwarfing genes in rye in comparison to wheat or barley. So far, three dominant dwarfing genes (Ddw1, Ddw3, and Ddw4) and three recessive genes (ct1, ct2, and np) have been characterized and precisely mapped in rye. There is no complete catalog of dwarfing genes available in rye. This paper presents an identification of the source of dwarfism and preliminary characterization of the new recessive gene dw9 from the BK-1 line. The gene was mapped on the long arm of the 6R chromosome and belongs to the GA-insensitive group. The initial characterization of the influence of this gene on morphological traits shows that it significantly affects the decrease of yielding trait parameters. A full evaluation can be performed after detailed breeding studies.

Genetic dissection of zinc, iron, copper, manganese and phosphorus in wheat (Triticum aestivum L.) grain and rachis at two developmental stages

The development of high-yielding wheat genotypes containing micronutrient-dense grains are the main priorities of biofortification programs. At the International Maize and Wheat Improvement Center, breeders have successfully crossed high zinc progenitors including synthetic hexaploid wheat, T. dicoccum, T. spelta and landraces to generate high-zinc varieties. In this study, we report a genome-wide association using a wheat diversity panel to dissect the genetics controlling zinc, iron, copper, manganese and phosphorus concentrations in the grain and rachis during grain development and at physiological maturity. Significant marker-trait associations (MTAs) were identified for each nutrient using multi-locus mixed model methodologies. For mature grain, markers that showed significant pleiotropic effects were found on chromosomes 1A, 3B and 5B, of which those on chromosome 5B at ∼95.5 cM were consistent over two growing seasons. Co-located MTAs were identified for the nutrient concentrations in developing grain, rachis and mature grain on multiple chromosomes. The identified genomic regions included putative candidate genes involved in metal uptake and transport and storage protein processing. These findings add to our understanding of the genetics of the five important nutrients in wheat grain and provide information on genetic markers for selecting high micronutrient genotypes.