Genetic characterization of the wheat association mapping initiative (WAMI) panel for dissection of complex traits in spring wheat

Genome-Wide Association Study Reveals Novel Powdery Mildew Resistance Loci in Bread Wheat

Powdery mildew (PM), caused by the fungal pathogen Blumeria graminis f. sp. tritici (Bgt), significantly threatens global bread wheat production. Although the use of resistant cultivars is an effective strategy for managing PM, currently available wheat cultivars lack sufficient levels of resistance. To tackle this challenge, we conducted a comprehensive genome-wide association study (GWAS) using a diverse panel of 286 bread wheat genotypes. Over three consecutive years (2020-2021, 2021-2022, and 2022-2023), these genotypes were extensively evaluated for PM severity under field conditions following inoculation with virulent Bgt isolates. The panel was previously genotyped using the Illumina 90K Infinium iSelect assay to obtain genome-wide single-nucleotide polymorphism (SNP) marker coverage. By applying FarmCPU, a multilocus mixed model, we identified a total of 113 marker-trait associations (MTAs) located on chromosomes 1A, 1B, 2B, 3A, 3B, 4A, 4B, 5A, 5B, 6B, 7A, and 7B at a significance level of p ≤ 0.001. Notably, four novel MTAs on chromosome 6B were consistently detected in 2020-2021 and 2021-2022. Furthermore, within the confidence intervals of the identified SNPs, we identified 96 candidate genes belonging to different proteins including 12 disease resistance/host-pathogen interaction-related protein families. Among these, protein kinases, leucine-rich repeats, and zinc finger proteins were of particular interest due to their potential roles in PM resistance. These identified loci can serve as targets for breeding programs aimed at developing disease-resistant wheat cultivars.

GWAS for Early-Establishment QTLs and Their Linkage to Major Phenology-Affecting Genes (Vrn, Ppd, and Eps) in Bread Wheat

Farmers in northern and central Indian regions prefer to plant wheat early in the season to take advantage of the remaining soil moisture. By planting crops before the start of the season, it is possible to extend the time frame for spring wheat. The early-wheat-establishment experiment began in the 2017 growing season at the Borlaug Institute for South Asia (BISA) in Ludhiana, India, and, after three years of intensive study, numerous agronomic, physiological, and yield data points were gathered. This study aimed to identify wheat lines suitable for early establishment through an analysis of the agro-morphological traits and the genetic mapping of associated genes or quantitative trait loci (QTLs). Advancing the planting schedule by two-three weeks proved to be advantageous in terms of providing a longer duration for crop growth and reducing the need for irrigation. This is attributed to the presence of residual soil moisture resulting from the monsoon season. Early sowing facilitated the selection of genotypes able to withstand early elevated temperatures and a prolonged phenological period. The ideotype, which includes increased photo-growing degree days for booting and heading, as well as a longer grain-filling period, is better suited to early planting than timely planting. Senescence was delayed in combination with a slower rate of canopy temperature rise, which was an excellent trait for early-adapted ideotypes. Thus, a novel approach to wheat breeding would include a screening of genotypes for early planting and an ideotype design with consistent and appropriate features. A genome-wide association study (GWAS) revealed multiple QTLs linked to early adaptation in terms of the yield and its contributing traits. Among them, 44 novel QTLs were also found along with known loci. Furthermore, the study discovered that the phenology regulatory genes, such as Vrn and Ppd, are in the same genomic region, thereby contributing to early adaptation.

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.

Identification of Single-Nucleotide Polymorphisms (SNPs) Associated with Heat Tolerance at the Reproductive Stage in Synthetic Hexaploid Wheats Using GWAS

The projected rise in global ambient temperature by 3-5 °C by the end of this century, along with unpredicted heat waves during critical crop growth stages, can drastically reduce grain yield and will pose a great food security challenge. It is therefore important to identify wheat genetic resources able to withstand high temperatures, discover genes underpinning resilience to higher temperatures, and deploy such genetic resources in wheat breeding to develop heat-tolerant cultivars. In this study, 180 accessions of synthetic hexaploid wheats (SHWs) were evaluated under normal and late wheat growing seasons (to expose them to higher temperatures) at three locations (Islamabad, Bahawalpur, and Tando Jam), and data were collected on 11 morphological and yield-related traits. The diversity panel was genotyped with a 50 K SNP array to conduct genome-wide association studies (GWASs) for heat tolerance in SHW. A known heat-tolerance locus, TaHST1, was profiled to identify different haplotypes of this locus in SHWs and their association with grain yield and related traits in SHWs. There was a 36% decrease in grain yield (GY), a 23% decrease in thousand-grain weight (TKW), and an 18% decrease in grains per spike (GpS) across three locations in the population due to the heat stress conditions. GWASs identified 143 quantitative trait nucleotides (QTNs) distributed over all 21 chromosomes in the SHWs. Out of these, 52 QTNs were associated with morphological and yield-related traits under heat stress, while 15 of them were pleiotropically associated with multiple traits. The heat shock protein (HSP) framework of the wheat genome was then aligned with the QTNs identified in this study. Seventeen QTNs were in proximity to HSPs on chr2B, chr3D, chr5A, chr5B, chr6D, and chr7D. It is likely that QTNs on the D genome and those in proximity to HSPs may carry novel alleles for heat-tolerance genes. The analysis of TaHST1 indicated that 15 haplotypes were present in the SHWs for this locus, while hap1 showed the highest frequency of 25% (33 SHWs). These haplotypes were significantly associated with yield-related traits in the SHWs. New alleles associated with yield-related traits in SHWs could be an excellent reservoir for breeding deployment.

Estimation of genetic diversity using seed storage protein (SSP) profiling in wild and cultivated species of Cicer L

BACKGROUND

The narrow genetic diversity of chickpea is a serious impediment to modern cultivar creation. Seed storage proteins (SSPs) are stable and have minimal or no degradation when subjected to isolation and SDS-PAGE.

METHODS AND RESULTS

We have characterized SSPs of 436 chickpea genotypes, belonging to nine annual Cicer species, originated from 47 countries by SDS-PAGE and determined the extent of genetic diversity in chickpea through clustering. Based on scoring, a total of 44 bands (10 to 170 kDa) were identified, which were all polymorphic. The least appeared protein bands were 11, 160 and 170 kDa where band of 11 and 160 kDa was present exclusively in wild type. Five bands were present in < 10% of genotypes. Bands appeared in 200-300 genotypes were suggested less polymorphic, on contrary bands present in 10-150 genotypes were suggested more polymorphic. Polymorphism of protein bands in context to their potential functions reported in literature were explored and suggested that the glubulins were most and glutelins were least abundant, whereas albumins with their known role in stress tolerance can be used as marker in chickpea breeding. Cluster analysis produced 14 clusters, interestingly three clusters contained only Pakistani genotypes and thus Pakistani genotypes appeared as a separate entity from the rest of the genotypes.

CONCLUSION

Our results indicate that SDS-PAGE of SSPs is a powerful technique in determining the genetic diversity plus it is easily adaptable, due to its cost effectiveness in comparison to other genomics tools.

Ensuring Nutritional Security in India through Wheat Biofortification: A Review

Undernourishment of nutrients, also known as hidden hunger, affects over 2 billion populace globally. Even though stunting among children below five years of age has decreased in India in the last ten years, India is home to roughly thirty percent of the world's population of stunted pre-schoolers. A significant improvement has been witnessed in the targeted development and deployment of biofortified crops; approximately 20 million farm households from developing counties benefit from cultivating and consuming biofortified crops. There is ample scope for including biofortified varieties in the seed chain, ensuring nutritional security. Wheat is a dietary staple in India, typically consumed as wholemeal flour in the form of flatbreads such as chapatti and roti. Wheat contributes to nearly one fifth of global energy requirements and can also provide better amounts of iron (Fe) and zinc (Zn). As a result, biofortified wheat can serve as a medium for delivery of essential micronutrients such as Fe and Zn to end users. This review discusses wheat biofortification components such as Fe and Zn dynamics, its uptake and movement in plants, the genetics of their buildup, and the inclusion of biofortified wheat varieties in the seed multiplication chain concerning India.

Capturing Wheat Phenotypes at the Genome Level

Recent technological advances in next-generation sequencing (NGS) technologies have dramatically reduced the cost of DNA sequencing, allowing species with large and complex genomes to be sequenced. Although bread wheat (Triticum aestivum L.) is one of the world's most important food crops, efficient exploitation of molecular marker-assisted breeding approaches has lagged behind that achieved in other crop species, due to its large polyploid genome. However, an international public-private effort spanning 9 years reported over 65% draft genome of bread wheat in 2014, and finally, after more than a decade culminated in the release of a gold-standard, fully annotated reference wheat-genome assembly in 2018. Shortly thereafter, in 2020, the genome of assemblies of additional 15 global wheat accessions was released. As a result, wheat has now entered into the pan-genomic era, where basic resources can be efficiently exploited. Wheat genotyping with a few hundred markers has been replaced by genotyping arrays, capable of characterizing hundreds of wheat lines, using thousands of markers, providing fast, relatively inexpensive, and reliable data for exploitation in wheat breeding. These advances have opened up new opportunities for marker-assisted selection (MAS) and genomic selection (GS) in wheat. Herein, we review the advances and perspectives in wheat genetics and genomics, with a focus on key traits, including grain yield, yield-related traits, end-use quality, and resistance to biotic and abiotic stresses. We also focus on reported candidate genes cloned and linked to traits of interest. Furthermore, we report on the improvement in the aforementioned quantitative traits, through the use of (i) clustered regularly interspaced short-palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9)-mediated gene-editing and (ii) positional cloning methods, and of genomic selection. Finally, we examine the utilization of genomics for the next-generation wheat breeding, providing a practical example of using in silico bioinformatics tools that are based on the wheat reference-genome sequence.

Genome-Wide Association Mapping of Grain Metal Accumulation in Wheat

Increasing wheat grain yield while ignoring grain quality and metal accumulation can result in metal deficiencies, particularly in countries where bread wheat accounts for the majority of daily dietary regimes. When the accumulation level exceeds a certain threshold, it becomes toxic and causes various diseases. Biofortification is an effective method of ensuring nutritional security. We screened 200 spring wheat advanced lines from the wheat association mapping initiative for Mn, Fe, Cu, Zn, Ni, and Cd concentrations. Interestingly, high-yielding genotypes had high essential metals, such as Mn, Fe, Cu, and Zn, but low levels of toxic metals, such as Ni and Cd. Positive correlations were found between all metals except Ni and Cd, where no correlation was found. We identified 142 significant SNPs, 26 of which had possible pleiotropic effects on two or more metals. Several QTLs co-located with previously mapped QTL for the same or other metals, whereas others were new. Our findings contribute to wheat genetic biofortification through marker-assisted selection, ensuring nutritional security in the long run.

Improving Zinc and Iron Biofortification in Wheat through Genomics Approaches

Globally, about 20% of calories (energy) come from wheat. In some countries, it is more than 70%. More than 2 billion people are at risk for zinc deficiency and even more, people are at risk of iron deficiency, nearly a quarter of all children underage group of 5 are physically and cognitively stunted, and lack of dietary zinc is a major contributing factor. Biofortified wheat with elevated levels of zinc and iron has several potential advantages as a delivery vehicle for micronutrients in the diets of resource-poor consumers who depend on cereal-based diets. The conventional breeding strategies have been successful in the introduction of novel alleles for grain Zn and Fe that led to the release of competitive Zn enriched wheat varieties in South Asia. The major challenge over the next few decades will be to maintain the rates of genetic gains for grain yield along with increased grain Zn/Fe concentration to meet the food and nutritional security challenges. Therefore, to remain competitive, the performance of Zn-enhanced lines/varieties must be equal or superior to that of current non-biofortified elite lines/varieties. Since both yield and Zn content are invisible and quantitatively inherited traits except few intermediate effect QTL regions identified for grain Zn, increased breeding efforts and new approaches are required to combine them at high frequency, ensuring that Zn levels are steadily increased to the required levels across the breeding pipelines. The current review article provides a comprehensive list of genomic regions for enhancing grain Zn and Fe concentrations in wheat including key candidate gene families such NAS, ZIP, VLT, ZIFL, and YSL. Implementing forward breeding by taking advantage of the rapid cycling trait pipeline approaches would simultaneously introgress high Zn and Fe QTL into the high Zn and normal elite lines, further increasing Zn and Fe concentrations.

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

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

Genome-wide association 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.

Drought-Tolerance QTLs Associated with Grain Yield and Related Traits in Spring Bread Wheat

The present research aims to identify the efficient combination of drought-tolerance selection criteria and associated quantitative trait loci. A panel of 197 bread wheat genotypes was evaluated for yield- and drought-tolerance-related traits in two environments (favorable and semiarid) for 2 years (2015-2016). Grain number, biomass, number of fertile spikes per plant and ground cover exhibited a significant correlation with grain yield and constitute potential secondary selection criteria for yield under drought conditions. About 73 significant marker-trait associations were detected along various chromosomal positions. The markers "wsnp_Ex_Rep_c67786_66472676" and "ExcalibuR_c24593_1217" exhibited important genetic gains associated with yield increase under drought (11 and 7%, respectively). The markers "KukRi_c94792_127" and "wsnp_Ex_c298_580660" showed a significant correlation with grain yield, biomass and grain number and were associated with a significant increase in yield performance at the semiarid site (+6 and +7%, respectively). The ground cover was found associated with grain yield and biomass through the markers "wsnp_Ex_Rep_c67786_66472676" (+11%) and "KukRi_c49927_151" (+10%). One marker "TduRuM_contig25432_1377" on chromosome 5B at 20 cM was consistently correlated with the number of fertile spikes across both environments. Further research should be considered to validate the efficiency of these markers to undertake selection for drought tolerance under various environments and genetic backgrounds.

Genome-Wide Association Study of Root-Lesion Nematodes Pratylenchus Species and Crown Rot Fusarium culmorum in Bread Wheat

Triticum aestivum L., also known as common wheat, is affected by many biotic stresses. Root diseases are the most difficult to tackle due to the complexity of phenotypic evaluation and the lack of resistant sources compared to other biotic stress factors. Soil-borne pathogens such as the root-lesion nematodes caused by the Pratylenchus species and crown rot caused by various Fusarium species are major wheat root diseases, causing substantial yield losses globally. A set of 189 advanced spring bread wheat lines obtained from the International Maize and Wheat Improvement Center (CIMMYT) were genotyped with 4056 single nucleotide polymorphisms (SNP) markers and screened for root-lesion nematodes and crown rot resistance. Population structure revealed that the genotypes could be divided into five subpopulations. Genome-Wide Association Studies were carried out for both resistances to Pratylenchus and Fusarium species. Based on our results, 11 different SNPs on chromosomes 1A, 1B, 2A, 3A, 4A, 5B, and 5D were significantly associated with root-lesion nematode resistance. Seven markers demonstrated association with P. neglectus, while the remaining four were linked to P. thornei resistance. In the case of crown rot, eight different markers on chromosomes 1A, 2B, 3A, 4B, 5B, and 7D were associated with Fusarium crown rot resistance. Identification and screening of root diseases is a challenging task; therefore, the newly identified resistant sources/genotypes could be exploited by breeders to be incorporated in breeding programs. The use of the identified markers in marker-assisted selection could enhance the selection process and cultivar development with root-lesion nematode and crown rot resistance.

Phenotypic Evaluation and Genetic Analysis of Seedling Emergence in a Global Collection of Wheat Genotypes (Triticum aestivum L.) Under Limited Water Availability

The challenge in establishing an early-sown wheat crop in southern Australia is the need for consistently high seedling emergence when sowing deep in subsoil moisture (>10 cm) or into dry top-soil (4 cm). However, the latter is strongly reliant on a minimum soil water availability to ensure successful seedling emergence. This study aimed to: (1) evaluate 233 Australian and selected international wheat genotypes for consistently high seedling emergence under limited soil water availability when sown in 4 cm of top-soil in field and glasshouse (GH) studies; (2) ascertain genetic loci associated with phenotypic variation using a genome-wide association study (GWAS); and (3) compare across loci for traits controlling coleoptile characteristics, germination, dormancy, and pre-harvest sprouting. Despite significant (P < 0.001) environment and genotype-by-environment interactions within and between field and GH experiments, eight genotypes that included five cultivars, two landraces, and one inbred line had consistently high seedling emergence (mean value > 85%) across nine environments. Moreover, 21 environment-specific quantitative trait loci (QTL) were detected in GWAS analysis on chromosomes 1B, 1D, 2B, 3A, 3B, 4A, 4B, 5B, 5D, and 7D, indicating complex genetic inheritance controlling seedling emergence. We aligned QTL for known traits and individual genes onto the reference genome of wheat and identified 16 QTL for seedling emergence in linkage disequilibrium with coleoptile length, width, and cross-sectional area, pre-harvest sprouting and dormancy, germination, seed longevity, and anthocyanin development. Therefore, it appears that seedling emergence is controlled by multifaceted networks of interrelated genes and traits regulated by different environmental cues.

The Genetic Architecture of Grain Yield in Spring Wheat Based on Genome-Wide Association Study

Uncovering the genetic architecture for grain yield (GY)–related traits is important for wheat breeding. To detect stable loci for GY-related traits, a genome-wide association study (GWAS) was conducted in a diverse panel, which included 251 elite spring wheat accessions mainly from the Northeast of China. In total, 52,503 single nucleotide polymorphisms (SNPs) from the wheat 55 K SNP arrays were used. Thirty-eight loci for GY-related traits were detected and each explained 6.5–16.7% of the phenotypic variations among which 12 are at similar locations with the known genes or quantitative trait loci and 26 are likely to be new. Furthermore, six genes possibly involved in cell division, signal transduction, and plant development are candidate genes for GY-related traits. This study provides new insights into the genetic architecture of GY and the significantly associated SNPs and accessions with a larger number of favorable alleles could be used to further enhance GY in breeding.

Direct introgression of untapped diversity into elite wheat lines

The effective utilization of natural variation has become essential in addressing the challenges that climate change and population growth pose to global food security. Currently adopted protracted approaches to introgress exotic alleles into elite cultivars need substantial transformation. Here, through a strategic three-way crossing scheme among diverse exotics and the best historical elites (exotic/elite1//elite2), 2,867 pre-breeding lines were developed, genotyped and screened for multiple agronomic traits in four mega-environments. A meta-genome-wide association study, selective sweeps and haplotype-block-based analyses unveiled selection footprints in the genomes of pre-breeding lines as well as exotic-specific associations with agronomic traits. A simulation with a neutrality assumption demonstrated that many pre-breeding lines had significant exotic contributions despite substantial selection bias towards elite genomes. National breeding programmes worldwide have adopted 95 lines for germplasm enhancement, and 7 additional lines are being advanced in varietal release trials. This study presents a great leap forwards in the mobilization of GenBank variation to the breeding pipelines.

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

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

Elucidating SNP-based genetic diversity and population structure of advanced breeding lines of bread wheat (Triticum aestivum L.)

Genetic diversity and population structure information are crucial for enhancing traits of interest and the development of superlative varieties for commercialization. The present study elucidated the population structure and genetic diversity of 141 advanced wheat breeding lines using single nucleotide polymorphism markers. A total of 14,563 high-quality identified genotyping-by-sequencing (GBS) markers were distributed covering 13.9 GB wheat genome, with a minimum of 1,026 SNPs on the homoeologous group four and a maximum of 2,838 SNPs on group seven. The average minor allele frequency was found 0.233, although the average polymorphism information content (PIC) and heterozygosity were 0.201 and 0.015, respectively. Principal component analyses (PCA) and population structure identified two major groups (sub-populations) based on SNPs information. The results indicated a substantial gene flow/exchange with many migrants (Nm = 86.428) and a considerable genetic diversity (number of different alleles, Na = 1.977; the number of effective alleles, Ne = 1.519; and Shannon's information index, I = 0.477) within the population, illustrating a good source for wheat improvement. The average PIC of 0.201 demonstrates moderate genetic diversity of the present evaluated advanced breeding panel. Analysis of molecular variance (AMOVA) detected 1% and 99% variance between and within subgroups. It is indicative of excessive gene traffic (less genetic differentiation) among the populations. These conclusions deliver important information with the potential to contribute new beneficial alleles using genome-wide association studies (GWAS) and marker-assisted selection to enhance genetic gain in South Asian wheat breeding programs.

Importance of Landraces in Cereal Breeding for Stress Tolerance

The renewed focus on cereal landraces is a response to some negative consequences of modern agriculture and conventional breeding which led to a reduction of genetic diversity. Cereal landraces are still cultivated on marginal lands due to their adaptability to unfavourable conditions, constituting an important source of genetic diversity usable in modern plant breeding to improve the adaptation to abiotic or biotic stresses, yield performance and quality traits in limiting environments. Traditional agricultural production systems have played an important role in the evolution and conservation of wide variability in gene pools within species. Today, on-farm and ex situ conservation in gene bank collections, together with data sharing among researchers and breeders, will greatly benefit cereal improvement. Many efforts are usually made to collect, organize and phenotypically and genotypically analyse cereal landrace collections, which also utilize genomic approaches. Their use in breeding programs based on genomic selection, and the discovery of beneficial untapped QTL/genes/alleles which could be introgressed into modern varieties by MAS, pyramiding or biotechnological tools, increase the potential for their better deployment and exploitation in breeding for a more sustainable agricultural production, particularly enhancing adaptation and productivity in stress-prone environments to cope with current climate changes.

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.

QTL mapping of agronomic traits in wheat using the UK Avalon × Cadenza reference mapping population grown in Kazakhstan

Background

The success of wheat production is largely dependent on local breeding projects that focus on the development of high-yielding cultivars with the use of novel molecular tools. One strategy for improving wheat productivity involves the deployment of diverse germplasms with a high potential yield. An important factor for achieving success involves the dissection of quantitative trait loci (QTLs) for complex agronomic traits, such as grain yield components, in targeted environments for wheat growth.

Methods

In this study, we tested the United Kingdom (UK) spring set of the doubled haploid (DH) reference population derived from the cross between two British cultivars, Avalon (winter wheat) and Cadenza (spring wheat), in the Northern, Central, and Southern regions (Karabalyk, Karaganda, Kyzylorda) of Kazakhstan over three years (2013–2015). The DH population has previously been genotyped by UK scientists using 3647 polymorphic DNA markers. The list of tested traits includes the heading time, seed maturation time, plant height, spike length, productive tillering, number of kernels per spike, number of kernels per meter, thousand kernel weight, and yield per square meter. Windows QTL Cartographer was applied for QTL mapping using the composite interval mapping method.

Results

In total, 83 out of 232 QTLs were identified as stable QTLs from at least two environments. A literature survey suggests that 40 QTLs had previously been reported elsewhere, indicating that this study identified 43 QTLs that are presumably novel marker-trait associations (MTA) for these environments. Hence, the phenotyping of the DH population in new environments led to the discovery of novel MTAs. The identified SNP markers associated with agronomic traits in the DH population could be successfully used in local Kazakh breeding projects for the improvement of wheat productivity.

Genomic Architecture of Phenotypic Plasticity in Response to Water Stress in Tetraploid Wheat

Phenotypic plasticity is one of the main mechanisms of adaptation to abiotic stresses via changes in critical developmental stages. Altering flowering phenology is a key evolutionary strategy of plant adaptation to abiotic stresses, to achieve the maximum possible reproduction. The current study is the first to apply the linear regression residuals as drought plasticity scores while considering the variation in flowering phenology and traits under non-stress conditions. We characterized the genomic architecture of 17 complex traits and their drought plasticity scores for quantitative trait loci (QTL) mapping, using a mapping population derived from a cross between durum wheat (Triticum turgidum ssp. durum) and wild emmer wheat (T. turgidum ssp. dicoccoides). We identified 79 QTLs affected observed traits and their plasticity scores, of which 33 reflected plasticity in response to water stress and exhibited epistatic interactions and/or pleiotropy between the observed and plasticity traits. Vrn-B3 (TaTF1) residing within an interval of a major drought-escape QTL was proposed as a candidate gene. The favorable alleles for most of the plasticity QTLs were contributed by wild emmer wheat, demonstrating its high potential for wheat improvement. Our study presents a new approach for the quantification of plant adaptation to various stresses and provides new insights into the genetic basis of wheat complex traits under water-deficit stress.

Evaluation of genetic structure in European wheat cultivars and advanced breeding lines using high-density genotyping-by-sequencing approach

BACKGROUND

The genetic diversity and gene pool characteristics must be clarified for efficient genome-wide association studies, genomic selection, and hybrid breeding. The aim of this study was to evaluate the genetic structure of 509 wheat accessions representing registered varieties and advanced breeding lines via the high-density genotyping-by-sequencing approach.

RESULTS

More than 30% of 13,499 SNP markers representing 2162 clusters were mapped to genes, whereas 22.50% of 26,369 silicoDArT markers overlapped with coding sequences and were linked in 3527 blocks. Regarding hexaploidy, perfect sequence matches following BLAST searches were not sufficient for the unequivocal mapping to unique loci. Moreover, allelic variations in homeologous loci interfered with heterozygosity calculations for some markers. Analyses of the major genetic changes over the last 27 years revealed the selection pressure on orthologs of the gibberellin biosynthesis-related GA2 gene and the senescence-associated SAG12 gene. A core collection representing the wheat population was generated for preserving germplasm and optimizing breeding programs.

CONCLUSIONS

Our results confirmed considerable differences among wheat subgenomes A, B and D, with D characterized by the lowest diversity but the highest LD. They revealed genomic regions that have been targeted by breeding.

Haplotype-Based, Genome-Wide Association Study Reveals Stable Genomic Regions for Grain Yield in CIMMYT Spring Bread Wheat

We untangled key regions of the genetic architecture of grain yield (GY) in CIMMYT spring bread wheat by conducting a haplotype-based, genome-wide association study (GWAS), together with an investigation of epistatic interactions using seven large sets of elite yield trials (EYTs) consisting of a total of 6,461 advanced breeding lines. These lines were phenotyped under irrigated and stress environments in seven growing seasons (2011-2018) and genotyped with genotyping-by-sequencing markers. Genome-wide 519 haplotype blocks were constructed, using a linkage disequilibrium-based approach covering 14,036 Mb in the wheat genome. Haplotype-based GWAS identified 7, 4, 10, and 15 stable (significant in three or more EYTs) associations in irrigated (I), mild drought (MD), severe drought (SD), and heat stress (HS) testing environments, respectively. Considering all EYTs and the four testing environments together, 30 stable associations were deciphered with seven hotspots identified on chromosomes 1A, 1B, 2B, 4A, 5B, 6B, and 7B, where multiple haplotype blocks were associated with GY. Epistatic interactions contributed significantly to the genetic architecture of GY, explaining variation of 3.5-21.1%, 3.7-14.7%, 3.5-20.6%, and 4.4- 23.1% in I, MD, SD, and HS environments, respectively. Our results revealed the intricate genetic architecture of GY, controlled by both main and epistatic effects. The importance of these results for practical applications in the CIMMYT breeding program is discussed.

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

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

Genetic characterization for lesion mimic and other traits in relation to spot blotch resistance in spring wheat

Lesion mimic (Lm) mutants display hypersensitive responses (HR) without any pathogen attack; their symptoms are similar to those produced by a pathogen and result in cell death. In wheat, such mutants have been reported to be resistant against leaf rust due to their biotrophic nature. However, Lm mutants tend to encourage spot blotch (SB) disease caused by Bipolarissorokiniana since dead cells facilitate pathogen multiplication. In this study, 289 diverse wheat germplasm lines were phenotyped in three consecutive growing seasons (2012–2015). Genotype data was generated using the Illumina iSelect beadchip assay platform for wheat germplasm lines. A total of 13,589 single-nucleotide polymorphisms (SNPs) were selected andused for further association mapping. Lm was positively associated with Area Under Disease Progress Curve (AUDPC) for SB but negatively with glaucous index (GI), leaf tip necrosis (Ltn) and latent period (LP). Ltn had a negative association with AUDPC and Lm but a positive one with LP. In a genome-wide association study (GWAS), 29 markers were significantly associated with these traits and 27 were an notated. Seven SNP markers associated with Lm were on chromosome 6A; another on 1B was found to be linked with Ltn. Like wise, seven SNP markers were associated with GI; one on chromosome 6A with the others on 6B. Five SNP markers on chromosomes 3B and 3Dwere significantly correlated with LP, while nine SNP markers on chromosomes 5A and 5B were significantly associated with AUDPC for SB. This study is the first to explore the interaction in wheat between Lm mutants and the hemibiotrophic SB pathogen B.sorokiniana.

Genetic Diversity and Population Structure of Asian and European Common Wheat Accessions Based on Genotyping-By-Sequencing

Obtaining information on the genetic diversity and population structure of germplasm facilitates its use in wheat breeding programs. Recently, with the development of next-generation sequencing technology, genotyping-by-sequencing (GBS) has been used as a high-throughput and cost-effective molecular tool for examination of the genetic diversity of wheat breeding lines. In this study, GBS was used to characterize a population of 180 accessions of common wheat originating from Asia and Europe between the latitudes 30° and 45°N. In total, 24,767 high-quality single-nucleotide polymorphism (SNP) markers were used for analysis of genetic diversity and population structure. The B genome contained the highest number of SNPs, followed by the A and D genomes. The polymorphism information content was in the range of 0.1 to 0.4, with a mean of 0.26. The distribution of SNPs markers on the 21 chromosomes ranged from 243 on chromosome 4D to 2,337 on chromosome 3B. Structure and cluster analyses divided the panel of accessions into two subgroups (G1 and G2). G1 principally consisted of European and partial Asian accessions, and G2 comprised mainly accessions from the Middle East and partial Asia. Molecular analysis of variance showed that the genetic variation was greater within groups (99%) than between groups (1%). Comparison of the two subgroups indicated that G1 and G2 contained a high level of genetic diversity. The genetic diversity of G2 was slightly higher as indicated by the observed heterozygosity (H o) = 0.23, and unbiased diversity index (uh) = 0.34. The present results will not only help breeders to understand the genetic diversity of wheat germplasm on the Eurasian continent between the latitudes of 30° and 45°N, but also provide valuable information for wheat genetic improvement through introgression of novel genetic variation in this region.

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.

Genome-Wide Association Mapping of Adult-Plant Resistance to Stripe Rust in Common Wheat (Triticum aestivum)

Stripe rust, caused by Puccinia striiformis f. sp. tritici, is a globally devastating disease of common wheat (Triticum aestivum L.), resulting in substantial economic losses. To identify effective resistance genes, a genome-wide association study was conducted on 120 common wheat lines from different wheat-growing regions of China using the wheat 90K iSelect SNP array. Seventeen loci were identified, explaining 9.5 to 21.8% of the phenotypic variation. Most of these genes were detected in the A (seven) and B (seven) genomes, with only three in the D genome. Among them, 11 loci were colocated with known resistance genes or quantitative trait loci reported previously, whereas the other six are likely new resistance loci. Annotation of flanking sequences of significantly associated SNPs indicated the presence of three important candidate genes, including E3 ubiquitin-protein ligase, F-box repeat protein, and disease resistance RPP13-like protein. This study increased our knowledge in understanding the genetic architecture for stripe rust resistance and identified wheat varieties with multiple resistance alleles, which are useful for improvement of stripe rust resistance in breeding.

Longin CF, Ganal M, Himmelbach A, Reif JC, Schulthess AW. Exome association analysis sheds light onto leaf rust (Puccinia triticina) resistance genes currently used in wheat breeding (Triticum aestivum L.)

Resistance breeding is crucial for a sustainable control of leaf rust (Puccinia triticina) in wheat (Triticum aestivum L.) while directly targeting functional variants is the Holy Grail for efficient marker-assisted selection and map-based cloning. We assessed the limits and prospects of exome association analysis for severity of leaf rust in a large hybrid wheat population of 1574 single-crosses plus their 133 parents. After imputation and quality control, exome sequencing revealed 202 875 single-nucleotide polymorphisms (SNPs) covering 19.7% of the high-confidence annotated gene space. We performed intensive data mining and found significant associations for 2171 SNPs corresponding to 50 different loci. Some of these associations mapped in the proximity of the already known resistance genes Lr21, Lr34-B, Lr1 and Lr10, while other associated genomic regions, such as those on chromosomes 1A and 3D, harboured several annotated genes putatively involved in resistance. Validation with an independent population helped to narrow down the list of putative resistance genes that should be targeted by fine-mapping. We expect that the proposed strategy of intensive data mining coupled with validation will significantly influence research in plant genetics and breeding.

Breeder friendly phenotyping

The word phenotyping can nowadays invoke visions of a drone or phenocart moving swiftly across research plots collecting high-resolution data sets on a wide array of traits. This has been made possible by recent advances in sensor technology and data processing. Nonetheless, more comprehensive often destructive phenotyping still has much to offer in breeding as well as research. This review considers the 'breeder friendliness' of phenotyping within three main domains: (i) the 'minimum data set', where being 'handy' or accessible and easy to collect and use is paramount, visual assessment often being preferred; (ii) the high throughput phenotyping (HTP), relatively new for most breeders, and requiring significantly greater investment with technical hurdles for implementation and a steeper learning curve than the minimum data set; (iii) detailed characterization or 'precision' phenotyping, typically customized for a set of traits associated with a target environment and requiring significant time and resources. While having been the subject of debate in the past, extra investment for phenotyping is becoming more accepted to capitalize on recent developments in crop genomics and prediction models, that can be built from the high-throughput and detailed precision phenotypes. This review considers different contexts for phenotyping, including breeding, exploration of genetic resources, parent building and translational research to deliver other new breeding resources, and how the different categories of phenotyping listed above apply to each. Some of the same tools and rules of thumb apply equally well to phenotyping for genetic analysis of complex traits and gene discovery.

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.

Genome-wide association mapping for adult resistance to powdery mildew in common wheat

Blumeria graminis f. sp. tritici, the causal agent of wheat powdery mildew disease, can occur at all stages of the crop and constantly threatens wheat production. To identify candidate resistance genes for powdery mildew, we performed GWAS (genome-wide association studies) on a total set of 329 wheat varieties obtained from different origins. These wheat materials were genotyped using wheat 90K SNP array and evaluated for their resistance in either field or glasshouse condition from 2016 to 2018. Using a mixed linear model, 33 SNP markers of which 14 QTL (quantitative trait loci) were later defined were observed to associate with powdery mildew resistance. Among these, QTL on chromosome 3A, 3B, 6D and 7D were concluded as potentially new QTL. Exploration of candidate genes for new QTL suggested roles of these genes involved in encoding disease resistance and defence-related proteins, and regulating early immune response to the pathogen. Overall, the results reveal that GWAS can be an effective means of identifying marker-trait associations, though further functional validation and fine-mapping of gene candidates are required before creating opportunities for developing new resistant genotypes.

Genome-wide association study of agronomic traits in bread wheat reveals novel putative alleles for future breeding programs

BACKGROUND

Identification of loci for agronomic traits and characterization of their genetic architecture are crucial in marker-assisted selection (MAS). Genome-wide association studies (GWAS) have increasingly been used as potent tools in identifying marker-trait associations (MTAs). The introduction of new adaptive alleles in the diverse genetic backgrounds may help to improve grain yield of old or newly developed varieties of wheat to balance supply and demand throughout the world. Landraces collected from different climate zones can be an invaluable resource for such adaptive alleles.

RESULTS

GWAS was performed using a collection of 298 Iranian bread wheat varieties and landraces to explore the genetic basis of agronomic traits during 2016-2018 cropping seasons under normal (well-watered) and stressed (rain-fed) conditions. A high-quality genotyping by sequencing (GBS) dataset was obtained using either all original single nucleotide polymorphism (SNP, 10938 SNPs) or with additional imputation (46,862 SNPs) based on W7984 reference genome. The results confirm that the B genome carries the highest number of significant marker pairs in both varieties (49,880, 27.37%) and landraces (55,086, 28.99%). The strongest linkage disequilibrium (LD) between pairs of markers was observed on chromosome 2D (0.296). LD decay was lower in the D genome, compared to the A and B genomes. Association mapping under two tested environments yielded a total of 313 and 394 significant (-log10 P >3) MTAs for the original and imputed SNP data sets, respectively. Gene ontology results showed that 27 and 27.5% of MTAs of SNPs in the original set were located in protein-coding regions for well-watered and rain-fed conditions, respectively. While, for the imputed data set 22.6 and 16.6% of MTAs represented in protein-coding genes for the well-watered and rain-fed conditions, respectively.

CONCLUSIONS

Our finding suggests that Iranian bread wheat landraces harbor valuable alleles that are adaptive under drought stress conditions. MTAs located within coding genes can be utilized in genome-based breeding of new wheat varieties. Although imputation of missing data increased the number of MTAs, the fraction of these MTAs located in coding genes were decreased across the different sub-genomes.

Variations in straw fodder quality and grain-Straw relationships in a mapping population of 287 diverse spring wheat lines

A wheat association mapping population consisting of 287 diverse spring wheat lines were evaluated for three years in one location (Varanasi) and out of these for one year across three locations (Karnal, Dharwad and Varanasi) in India. Straw fodder quality traits analyzed were nitrogen (N) content, neutral (NDF) and acid (ADF) detergent fiber, acid detergent lignin (ADL), ash (ASH), in vitro organic matter digestibility (IVOMD) and metabolizable energy (ME) content. Grain yield (GY) and straw yield (SY) were also recorded. Highly significant (P < 0.0001) differences among lines were observed for all traits except for ADF and ADL in the three years trials conducted at Varanasi. However, year and location had strong (P < 0.0001) effects on all traits. Compared to line-dependent variations in GY and SY variation in straw fodder quality traits were small. Proportionally greatest variations between lines were observed for straw N where lowest and highest N varied by about 30%. Difference for NDF and ADF between lines were at most 4% units and below 3% units for IVOMD. Grain yield and straw yield were positively correlated (P < 0.0001) with GY accounting for 26% of the variation in SY. Straw N, IVOMD and ME were weakly but significantly (P < 0.05) negatively associated with GY and SY. Straw NDF and ADF were significantly (P < 0.05) positively correlated with GY but the association was again weak. Straw NDF, ADF and ADL were also weakly but significantly positively correlated with SY. Genome-wide association studies (GWAS) were applied to detect significant marker- straw fodder quality trait associations. Five genomic regions contributed for six traits (ADF, ADL, ASH, IVOMD, ME and NDF). ADF and ADL mapped in the common QTL region on chromosome 2B. Similarly, for the IVOMD and ME QTLs on chromosome 5B were associated with SNP marker, wsnp_Ku_c35090_44349517. While some associations were detected for ADF, ALD, ASH, IVOMD, ME and NDF on chromosomes 1A, 2B, 3A, 5A and 5B, the phenotypic variation explained was low to medium by individual QTL. A likely contributing factor was the comparatively small difference in straw fodder quality traits among the lines. It is interesting to note that line dependent variations in GY and SY were about two-fold. In other words, strong genotypic variations of GY and SY do exist. The lack of any similar variations in straw fodder quality traits is intriguing and requires further research.

GWAS to Identify Genetic Loci for Resistance to Yellow Rust in Wheat Pre-Breeding Lines Derived From Diverse Exotic Crosses

Yellow rust (YR) or stripe rust, caused by Puccinia striformis f. sp tritici Eriks (Pst), is a major challenge to resistance breeding in wheat. A genome wide association study (GWAS) was performed using 22,415 single nucleotide polymorphism (SNP) markers and 591 haplotypes to identify genomic regions associated with resistance to YR in a subset panel of 419 pre-breeding lines (PBLs) developed at International Center for Maize and Wheat Improvement (CIMMYT). The 419 PBLs were derived from an initial set of 984 PBLs generated by a three-way crossing scheme (exotic/elite1//elite2) among 25 best elites and 244 exotics (synthetics, landraces) from CIMMYT's germplasm bank. For the study, 419 PBLs were characterized with 22,415 high-quality DArTseq-SNPs and phenotyped for severity of YR disease at five locations in Mexico. A population structure was evident in the panel with three distinct subpopulations, and a genome-wide linkage disequilibrium (LD) decay of 2.5 cM was obtained. Across all five locations, 14 SNPs and 7 haplotype blocks were significantly (P < 0.001) associated with the disease severity explaining 6.0 to 14.1% and 7.9 to 19.9% of variation, respectively. Based on average LD decay of 2.5 cM, identified 14 SNP-trait associations were delimited to seven quantitative trait loci in total. Seven SNPs were part of the two haplotype blocks on chromosome 2A identified in haplotypes-based GWAS. In silico analysis of the identified SNPs showed hits with interesting candidate genes, which are related to pathogenic process or known to regulate induction of genes related to pathogenesis such as those coding for glunolactone oxidase, quinate O-hydroxycinnamoyl transferase, or two-component histidine kinase. The two-component histidine kinase, for example, acts as a sensor in the perception of phytohormones ethylene and cytokinin. Ethylene plays a very important role in regulation of multiple metabolic processes of plants, including induction of defense mechanisms mediated by jasmonate. The SNPs linked to the promising genes identified in the study can be used for marker-assisted selection.

Artificial selection causes significant linkage disequilibrium among multiple unlinked genes in Australian wheat

Australia has one of the oldest modern wheat breeding programs worldwide although the crop was first introduced to the country in 1788. Breeders selected wheat with high adaptation to different Australian climates, while ensuring satisfactory yield and quality. This artificial selection left distinct genomic signatures that can be used to retrospectively understand breeding targets, and to detect economically important alleles. To study the effect of artificial selection on modern cultivars and cultivars released in different Australian states, we genotyped 482 Australian cultivars representing the history of wheat breeding in Australia since 1840. Computer simulation showed that 86 genomic regions were significantly affected by artificial selection. Characterization of 18 major genes known to affect wheat adaptation, yield, and quality revealed that many were affected by artificial selection and contained within regions under selection. Similarly, many reported QTL and genes for yield, quality, and adaptation were also contained in regions affected by artificial selection. These included TaCwi-A1, TaGw2-6A, Sus-2B, TaSus1-7A, TaSAP1-7A, Glu-A1, Glu-B1, Glu-B3, PinA, PinB, Ppo-D1, Psy-A1, Psy-A2, Rht-A1, Rht-B1, Ppd-D1, Vrn-A1, Vrn-B1, and Cre8. Interestingly, 17 regions affected by artificial selection were in moderate-to-high linkage disequilibrium with each other with an average r 2 value of 0.35 indicating strong simultaneous selection on specific alleles. These regions included Glu-B1, TaGw2-6A, Cre8, Ppd-D1, Rht-B1, Vrn-B1, TaSus1-7A, TaSAP1-7A, and Psy-A1 plus multiple QTL affecting wheat yield and yield components. These results highlighted the effects of the long-term artificial selection on Australian wheat germplasm and identified putative regions underlying important traits in wheat.

Genome-wide variation patterns between landraces and cultivars uncover divergent selection during modern wheat breeding

Genetic diversity, population structure, LD decay, and selective sweeps in 687 wheat accessions were analyzed, providing relevant guidelines to facilitate the use of the germplasm in wheat breeding. Common wheat (Triticum aestivum L.) is one of the most widely grown crops in the world. Landraces were subjected to strong human-mediated selection in developing high-yielding, good quality, and widely adapted cultivars. To investigate the genome-wide patterns of allelic variation, population structure and patterns of selective sweeps during modern wheat breeding, we tested 687 wheat accessions, including landraces (148) and cultivars (539) mainly from China and Pakistan in a wheat 90 K single nucleotide polymorphism array. Population structure analysis revealed that cultivars and landraces from China and Pakistan comprised three relatively independent genetic clusters. Cultivars displayed lower nucleotide diversity and a wider average LD decay across whole genome, indicating allelic erosion and a diversity bottleneck due to the modern breeding. Analysis of genetic differentiation between landraces and cultivars from China and Pakistan identified allelic variants subjected to selection during modern breeding. In total, 477 unique genome regions showed signatures of selection, where 109 were identified in both China and Pakistan germplasm. The majority of genomic regions were located in the B genome (225), followed by the A genome (175), and only 77 regions were located in the D genome. EigenGWAS was further used to identify key selection loci in modern wheat cultivars from China and Pakistan by comparing with global winter wheat and spring wheat diversity panels, respectively. A few known functional genes or loci found within these genome regions corresponded to known phenotypes for disease resistance, vernalization, quality, adaptability and yield-related traits. This study uncovered molecular footprints of modern wheat breeding and explained the genetic basis of polygenic adaptation in wheat. The results will be useful for understanding targets of modern wheat breeding, and in devising future breeding strategies to target beneficial alleles currently not pursued.

From landraces to improved cultivars: Assessment of genetic diversity and population structure of Mediterranean wheat using SNP markers

Assessment of genetic diversity and population structure in crops is essential for breeding and germplasm conservation. A collection of 354 bread wheat genotypes, including Mediterranean landraces and modern cultivars representative of the ones most widely grown in the Mediterranean Basin, were characterized with 11196 single nucleotide polymorphism (SNP) markers. Total genetic diversity (H_T) and polymorphic information content (PIC) were 0.36 and 0.30 respectively for both landraces and modern cultivars. Linkage disequilibrium for the modern cultivars was higher than for the landraces (0.18 and 0.12, respectively). Analysis of the genetic structure showed a clear geographical pattern for the landraces, which were clustered into three subpopulations (SPs) representing the western, northern and eastern Mediterranean, whereas the modern cultivars were structured according to the breeding programmes that developed them: CIMMYT/ICARDA, France/Italy, and Balkan/eastern European countries. The modern cultivars showed higher genetic differentiation (G_ST) and lower gene flow (0.1673 and 2.49, respectively) than the landraces (0.1198 and 3.67, respectively), indicating a better distinction between subpopulations. The maximum gene flow was observed between landraces from the northern Mediterranean SPs and the modern cultivars released mainly by French and Italian breeding programmes.

Broadening the bread wheat D genome

Although Ae. tauschii has been extensively utilised for wheat breeding, the D-genome-containing allopolyploids have largely remained unexploited. In this review, we discuss approaches that can be used to exploit the D genomes of the different Aegilops species for the improvement of bread wheat. The D genome of allohexaploid bread wheat (Triticum aestivum, 2n = AABBDD) is the least diverse of the three wheat genomes and is unarguably less diverse than that of diploid progenitor Aegilops tauschii (2n = DD). Useful genetic variation and phenotypic traits also exist within each of the wheat group species containing a copy of the D genome: allopolyploid Aegilops species Ae. cylindrica (2n = D^cD^cC^cC^c), Ae. crassa 4x (2n = D¹D¹X^crX^cr), Ae. crassa 6x (2n = D¹D¹X^crX^crD^crD^cr), Ae. ventricosa (2n = D^vD^vN^vN^v), Ae. vavilovii (2n = D¹D¹X^crX^crS^vS^v) and Ae. juvenalis (2n = D¹D¹X^crX^crU^jU^j). Although Ae. tauschii has been extensively utilised for wheat breeding, the D-genome-containing allopolyploids have largely remained unexploited. Some of these D genomes appear to be modified relative to the bread wheat and Ae. tauschii D genomes, and others present in the allopolyploids may also contain useful variation as a result of adaptation to an allopolyploid, multi-genome environment. We summarise the genetic relationships, karyotypic variation and phenotypic traits known to be present in each of the D genome species that could be of relevance for bread wheat improvement and discuss approaches that can be used to exploit the D genomes of the different Aegilops species for the improvement of bread wheat. Better understanding of factors controlling chromosome inheritance and recombination in wheat group interspecific hybrids, as well as effective utilisation of new and developing genetics and genomics technologies, have great potential to improve the agronomic potential of the bread wheat D genome.

Genetic architecture of grain yield in bread wheat based on genome-wide association studies

BACKGROUND

Identification of loci for grain yield (GY) and related traits, and dissection of the genetic architecture are important for yield improvement through marker-assisted selection (MAS). Two genome-wide association study (GWAS) methods were used on a diverse panel of 166 elite wheat varieties from the Yellow and Huai River Valleys Wheat Zone (YHRVWD) of China to detect stable loci and analyze relationships among GY and related traits.

RESULTS

A total of 326,570 single nucleotide polymorphism (SNP) markers from the wheat 90 K and 660 K SNP arrays were chosen for GWAS of GY and related traits, generating a physical distance of 14,064.8 Mb. One hundred and twenty common loci were detected using SNP-GWAS and Haplotype-GWAS, among which two were potentially functional genes underpinning kernel weight and plant height (PH), eight were at similar locations to the quantitative trait loci (QTL) identified in recombinant inbred line (RIL) populations in a previous study, and 78 were potentially new. Twelve pleiotropic loci were detected on eight chromosomes; among these the interval 714.4-725.8 Mb on chromosome 3A was significantly associated with GY, kernel number per spike (KNS), kernel width (KW), spike dry weight (SDW), PH, uppermost internode length (UIL), and flag leaf length (FLL). GY shared five loci with thousand kernel weight (TKW) and PH, indicating significantly affected by two traits. Compared with the total number of loci for each trait in the diverse panel, the average number of alleles for increasing phenotypic values of GY, TKW, kernel length (KL), KW, and flag leaf width (FLW) were higher, whereas the numbers for PH, UIL and FLL were lower. There were significant additive effects for each trait when favorable alleles were combined. UIL and FLL can be directly used for selecting high-yielding varieties, whereas FLW can be used to select spike number per unit area (SN) and KNS.

CONCLUSIONS

The loci and significant SNP markers identified in the present study can be used for pyramiding favorable alleles in developing high-yielding varieties. Our study proved that both GWAS methods and high-density genetic markers are reliable means of identifying loci for GY and related traits, and provided new insight to the genetic architecture of GY.

CropSNPdb: a database of SNP array data for Brassica crops and hexaploid bread wheat

Advances in sequencing technology have led to a rapid rise in the genomic data available for plants, driving new insights into the evolution, domestication and improvement of crops. Single nucleotide polymorphisms (SNPs) are a major component of crop genomic diversity, and are invaluable as genetic markers in research and breeding programs. High-throughput SNP arrays, or 'SNP chips', can generate reproducible sets of informative SNP markers and have been broadly adopted. Although there are many public repositories for sequencing data, which are routinely uploaded, there are no formal repositories for crop SNP array data. To make SNP array data more easily accessible, we have developed CropSNPdb (http://snpdb.appliedbioinformatics.com.au), a database for SNP array data produced by the Illumina Infinium™ hexaploid bread wheat (Triticum aestivum) 90K and Brassica 60K arrays. We currently host SNPs from datasets covering 526 Brassica lines and 309 bread wheat lines, and provide search, download and upload utilities for users. CropSNPdb provides a useful repository for these data, which can be applied for a range of genomics and molecular crop-breeding activities.

Novel Alleles for Combined Drought and Heat Stress Tolerance in Wheat

Drought and heat waves commonly co-occur in many wheat-growing regions causing significant crop losses. The identification of stress associated quantitative trait loci, particularly those for yield, is problematic due to their association with plant phenology and the high genetic × environment interaction. Here we studied a panel of 315 diverse, spring type accessions of bread wheat (Triticum aestivum) in pots in a semi-controlled environment under combined drought and heat stress over 2 years. Importantly, we treated individual plants according to their flowering time. We found 134 out of the 145 identified loci for grain weight that were not associated with either plant phenology or plant height. The majority of loci uncovered here were novel, with favorable alleles widespread in Asian and African landraces providing opportunities for their incorporation into modern varieties through breeding. Using residual heterozygosity in lines from a nested association mapping population, we were able to rapidly develop near-isogenic lines for important target loci. One target locus on chromosome 6A contributed to higher grain weight, harvest index, thousand kernel weight, and grain number under drought and heat stress in field conditions consistent with allelic effects demonstrated in the genome-wide association study.

Integrating genomic-enabled prediction and high-throughput phenotyping in breeding for climate-resilient bread wheat

Genomic selection and high-throughput phenotyping (HTP) are promising tools to accelerate breeding gains for high-yielding and climate-resilient wheat varieties. Hence, our objective was to evaluate them for predicting grain yield (GY) in drought-stressed (DS) and late-sown heat-stressed (HS) environments of the International maize and wheat improvement center's elite yield trial nurseries. We observed that the average genomic prediction accuracies using fivefold cross-validations were 0.50 and 0.51 in the DS and HS environments, respectively. However, when a different nursery/year was used to predict another nursery/year, the average genomic prediction accuracies in the DS and HS environments decreased to 0.18 and 0.23, respectively. While genomic predictions clearly outperformed pedigree-based predictions across nurseries, they were similar to pedigree-based predictions within nurseries due to small family sizes. In populations with some full-sibs in the training population, the genomic and pedigree-based prediction accuracies were on average 0.27 and 0.35 higher than the accuracies in populations with only one progeny per cross, indicating the importance of genetic relatedness between the training and validation populations for good predictions. We also evaluated the item-based collaborative filtering approach for multivariate prediction of GY using the green normalized difference vegetation index from HTP. This approach proved to be the best strategy for across-nursery predictions, with average accuracies of 0.56 and 0.62 in the DS and HS environments, respectively. We conclude that GY is a challenging trait for across-year predictions, but GS and HTP can be integrated in increasing the size of populations screened and evaluating unphenotyped large nurseries for stress-resilience within years.

Validation of Candidate Gene-Based Markers and Identification of Novel Loci for Thousand-Grain Weight in Spring Bread Wheat

Increased thousand-grain weight (TGW) is an important breeding target for indirectly improving grain yield (GY). Fourteen reported candidate genes known to enhance TGW were evaluated in two independent and existing datasets of wheat at CIMMYT, the Elite Yield Trial (EYT) from 2015 to 2016 (EYT2015-16) and the Wheat Association Mapping Initiative (WAMI) panel, to study their allele effects on TGW and to verify their suitability for marker-assisted selection. Of these, significant associations were detected for only one gene (TaGs3-D1) in the EYT2015-16 and two genes (TaTGW6 and TaSus1) in WAMI. The reported favorable alleles of TaGs3-D1 and TaTGW6 genes decreased TGW in the datasets. A haplotype-based genome wide association study was implemented to identify the genetic determinants of TGW on a large set of CIMMYT germplasm (4,302 lines comprising five EYTs), which identified 15 haplotype blocks to be significantly associated with TGW. Four of them, identified on chromosomes 4A, 6A, and 7A, were associated with TGW in at least three EYTs. The locus on chromosome 6A (Hap-6A-13) had the largest effect on TGW and additionally GY with increases of up to 2.60 g and 258 kg/ha, respectively. Discovery of novel TGW loci described in our study expands the opportunities for developing diagnostic markers and for multi-gene pyramiding to derive new allele combinations for enhanced TGW and GY in CIMMYT wheat.

Genome-Wide Association Studies Reveal Genomic Regions Associated With the Response of Wheat (Triticum aestivum L.) to Mycorrhizae Under Drought Stress Conditions

In the majority of wheat growing areas worldwide, the incidence of drought stress has increased significantly resulting in a negative impact on plant development and grain yield. Arbuscular mycorrhizal symbiosis is known to improve drought stress tolerance of wheat. However, quantitative trait loci (QTL) involved in the response to drought stress conditions in the presence of mycorrhizae are largely unknown. Therefore, a diverse set consisting of 94 bread wheat genotypes was phenotyped under drought stress and well watered conditions in the presence and absence of mycorrhizae. Grain yield and yield components, drought stress related traits as well as response to mycorrhizae were assessed. In parallel, wheat accessions were genotyped by using the 90k iSelect chip, resulting in a set of 15511 polymorphic and mapped SNP markers, which were used for genome-wide association studies (GWAS). In general, drought stress tolerance of wheat was significantly increased in the presence of mycorrhizae compared to drought stress tolerance in the absence of mycorrhizae. However, genotypes differed in their response to mycorrhizae under drought stress conditions. Several QTL regions on different chromosomes were detected associated with grain yield and yield components under drought stress conditions. Furthermore, two genome regions on chromosomes 3D and 7D were found to be significantly associated with the response to mycorrhizae under drought stress conditions. Overall, the results reveal that inoculation of wheat with mycorrhizal fungi significantly improves drought stress tolerance and that QTL regions associated with the response to mycorrhizae under drought stress conditions exist in wheat. Further research is necessary to validate detected QTL regions. However, this study may be the starting point for the identification of candidate genes associated with drought stress tolerance and response to mycorrhizae under drought stress conditions. Maybe in future, these initial results will help to contribute to use mycorrhizal fungi effectively in agriculture and combine new approaches i.e., use of genotypic variation in response to mycorrhizae under drought stress conditions with existing drought tolerance breeding programs to develop new drought stress tolerant genotypes.

Genetic dissection of grain zinc concentration in spring wheat for mainstreaming biofortification in CIMMYT wheat breeding

Wheat is an important staple that acts as a primary source of dietary energy, protein, and essential micronutrients such as iron (Fe) and zinc (Zn) for the world’s population. Approximately two billion people suffer from micronutrient deficiency, thus breeders have crossed high Zn progenitors such as synthetic hexaploid wheat, T. dicoccum, T. spelta, and landraces to generate wheat varieties with competitive yield and enhanced grain Zn that are being adopted by farmers in South Asia. Here we report a genome-wide association study (GWAS) using the wheat Illumina iSelect 90 K Infinitum SNP array to characterize grain Zn concentrations in 330 bread wheat lines. Grain Zn phenotype of this HarvestPlus Association Mapping (HPAM) panel was evaluated across a range of environments in India and Mexico. GWAS analysis revealed 39 marker-trait associations for grain Zn. Two larger effect QTL regions were found on chromosomes 2 and 7. Candidate genes (among them zinc finger motif of transcription-factors and metal-ion binding genes) were associated with the QTL. The linked markers and associated candidate genes identified in this study are being validated in new biparental mapping populations for marker-assisted breeding.

Genome-wide association mapping in bread wheat subjected to independent and combined high temperature and drought stress

Most investigations to date aiming to identify the genetic basis of the stress response of wheat (Triticum aestivum L.) have focused on the response to single stress agents such as high temperature or drought, even though in the natural situation, these stresses tend often to occur together. Here, a panel of 108 spring type bread wheat cultivars was phenotyped for 15 yield and yield related traits for two years (2014/15 and 2015/16) under non-stressed conditions, under high temperature stress, under drought and under a combined high temperature and drought regime. The mean loss in grain yield caused by all stress regimes was 51.33%. Analysis of variance (ANOVA) of yield trait showed significant differences among genotypes environments and their interactions (G×E). All the studied traits had higher heritability values which ranged from 0.35-0.94 under [C], 0.58-0.95 under [D], 0.62-0.93 under [H] and 0.60-0.95 under [HD]. GWAS was performed by using 9,646 informative SNP markers and based on these polymorphic SNPs population structure analysis divided whole germplasm into five major sub-populations. Mixed model association analysis detected 503 marker-trait associations (MTAs) at P ≤0.001 while 329 MTAs crossed FDR ≤ 0.05 for all traits with phenotypic variances (R2) ranged from 24.83% to 12.51%. Seven new pleiotropic SNPs on chromosome 7D and IAAV8258 (86.91cM) and wsnp_Ex_c7168_12311649 (57.93cM) on chromosome 5A were most stable association in present study. Furthermore, candidate genes Psy and Sr25 (TG0040) were also significant in present study, these genes were previously mapped on 7A and 7D. The region on 7D was assiociated with 7DL.7Ag translocation from Lophopyrum carring rust resistance Yr16 and many other genes. Similarly region on chromosome 7A which was associated with Psy gene was linked with grain yellow pigment content QTLs. Favourable alleles controlling grain yield were of vital importance and incorporation of these alleles after validation through marker assisted selection and fine mapping could be helpful in wheat yield improvement stress and non-stress conditions.