Development of a next generation SNP genotyping array for wheat.

High-throughput genotyping arrays have provided a cost-effective, reliable and interoperable system for genotyping hexaploid wheat and its relatives. Existing, highly cited arrays including our 35K Wheat Breeder's array and the Illumina 90K array were designed based on a limited amount of varietal sequence diversity and with imperfect knowledge of SNP positions. Recent progress in wheat sequencing has given us access to a vast pool of SNP diversity, whilst technological improvements have allowed us to fit significantly more probes onto a 384-well format Axiom array than previously possible. Here we describe a novel Axiom genotyping array, the 'Triticum aestivum Next Generation' array (TaNG), largely derived from whole genome skim sequencing of 204 elite wheat lines and 111 wheat landraces taken from the Watkins 'Core Collection'. We used a novel haplotype optimization approach to select SNPs with the highest combined varietal discrimination and a design iteration step to test and replace SNPs which failed to convert to reliable markers. The final design with 43 372 SNPs contains a combination of haplotype-optimized novel SNPs and legacy cross-platform markers. We show that this design has an improved distribution of SNPs compared to previous arrays and can be used to generate genetic maps with a significantly higher number of distinct bins than our previous array. We also demonstrate the improved performance of TaNGv1.1 for Genome-wide association studies (GWAS) and its utility for Copy Number Variation (CNV) analysis. The array is commercially available with supporting marker annotations and initial genotyping results freely available.

Wheat genetic resources have avoided disease pandemics, improved food security, and reduced environmental footprints: A review of historical impacts and future opportunities.

The use of plant genetic resources (PGR)-wild relatives, landraces, and isolated breeding gene pools-has had substantial impacts on wheat breeding for resistance to biotic and abiotic stresses, while increasing nutritional value, end-use quality, and grain yield. In the Global South, post-Green Revolution genetic yield gains are generally achieved with minimal additional inputs. As a result, production has increased, and millions of hectares of natural ecosystems have been spared. Without PGR-derived disease resistance, fungicide use would have easily doubled, massively increasing selection pressure for fungicide resistance. It is estimated that in wheat, a billion liters of fungicide application have been avoided just since 2000. This review presents examples of successful use of PGR including the relentless battle against wheat rust epidemics/pandemics, defending against diseases that jump species barriers like blast, biofortification giving nutrient-dense varieties and the use of novel genetic variation for improving polygenic traits like climate resilience. Crop breeding genepools urgently need to be diversified to increase yields across a range of environments (>200 Mha globally), under less predictable weather and biotic stress pressure, while increasing input use efficiency. Given that the ~0.8 m PGR in wheat collections worldwide are relatively untapped and massive impacts of the tiny fraction studied, larger scale screenings and introgression promise solutions to emerging challenges, facilitated by advanced phenomic and genomic tools. The first translocations in wheat to modify rhizosphere microbiome interaction (reducing biological nitrification, reducing greenhouse gases, and increasing nitrogen use efficiency) is a landmark proof of concept. Phenomics and next-generation sequencing have already elucidated exotic haplotypes associated with biotic and complex abiotic traits now mainstreamed in breeding. Big data from decades of global yield trials can elucidate the benefits of PGR across environments. This kind of impact cannot be achieved without widescale sharing of germplasm and other breeding technologies through networks and public-private partnerships in a pre-competitive space.

Genomic Prediction of Resistance to Tan Spot, Spot Blotch and Septoria Nodorum Blotch in Synthetic Hexaploid Wheat.

Genomic prediction combines molecular and phenotypic data in a training population to predict the breeding values of individuals that have only been genotyped. The use of genomic information in breeding programs helps to increase the frequency of favorable alleles in the populations of interest. This study evaluated the performance of BLUP (Best Linear Unbiased Prediction) in predicting resistance to tan spot, spot blotch and Septoria nodorum blotch in synthetic hexaploid wheat. BLUP was implemented in single-trait and multi-trait models with three variations: (1) the pedigree relationship matrix (A-BLUP), (2) the genomic relationship matrix (G-BLUP), and (3) a combination of the two matrices (A+G BLUP). In all three diseases, the A-BLUP model had a lower performance, and the G-BLUP and A+G BLUP were statistically similar (p ≥ 0.05). The prediction accuracy with the single trait was statistically similar (p ≥ 0.05) to the multi-trait accuracy, possibly due to the low correlation of severity between the diseases.

Linkage disequilibrium patterns, population structure and diversity analysis in a worldwide durum wheat collection including Argentinian genotypes.

BACKGROUND: Durum wheat (Triticum turgidum L. ssp. durum Desf. Husn) is the main staple crop used to make pasta products worldwide. Under the current climate change scenarios, genetic variability within a crop plays a crucial role in the successful release of new varieties with high yields and wide crop adaptation. In this study we evaluated a durum wheat collection consisting of 197 genotypes that mainly comprised a historical set of Argentinian germplasm but also included worldwide accessions. RESULTS: We assessed the genetic diversity, population structure and linkage disequilibrium (LD) patterns in this collection using a 35 K SNP array. The level of polymorphism was considered, taking account of the frequent and rare allelic variants. A total of 1547 polymorphic SNPs was located within annotated genes. Genetic diversity in the germplasm collection increased slightly from 1915 to 2010. However, a reduction in genetic diversity using SNPs with rare allelic variants was observed after 1979. However, larger numbers of rare private alleles were observed in the 2000-2009 period, indicating that a high reservoir of rare alleles is still present among the recent germplasm in a very low frequency. The percentage of pairwise loci in LD in the durum genome was low (13.4%) in our collection. Overall LD and the high (r2 > 0.7) or complete (r2 = 1) LD presented different patterns in the chromosomes. The LD increased over three main breeding periods (1915-1979, 1980-1999 and 2000-2020). CONCLUSIONS: Our results suggest that breeding and selection have impacted differently on the A and B genomes, particularly on chromosome 6A and 2A. The collection was structured in five sub-populations and modern Argentinian accessions (cluster Q4) which were clearly differentiated. Our study contributes to the understanding of the complexity of Argentinian durum wheat germplasm and to derive future breeding strategies enhancing the use of genetic diversity in a more efficient and targeted way.

Using a gene-based phenology model to identify optimal flowering periods of spring wheat in irrigated mega-environments.

To maximize the grain yield of spring wheat, flowering needs to coincide with the optimal flowering period (OFP) by minimizing frost and heat stress on reproductive development. This global study conducted a comprehensive modelling analysis of genotype, environment, and management to identify the OFPs for sites in irrigated mega-environments of spring wheat where the crop matures during a period of increasing temperatures. We used a gene-based phenology model to conduct long-term simulation analysis with parameterized genotypes to identify OFPs and optimal sowing dates for sites in irrigated mega-environments, considering the impacts of frost and heat stress on yield. The validation results showed that the gene-based model accurately predicted wheat heading dates across global wheat environments. The long-term simulations indicated that frost and heat stress significantly advanced or delayed OFPs and shrank the durations of OFPs in irrigated mega-environments when compared with OFPs where the model excluded frost and heat stress impacts. The simulation results (incorporating frost and heat penalties on yield) also showed that earlier flowering generally resulted in higher yields, and early sowing dates and/or early flowering genotypes were suggested to achieve early flowering. These results provided an interpretation of the regulation of wheat flowering to the OFP by the selection of sowing date and cultivar to achieve higher yields in irrigated mega-environments.

Harnessing translational research in wheat for climate resilience.

Despite being the world's most widely grown crop, research investments in wheat (Triticum aestivum and Triticum durum) fall behind those in other staple crops. Current yield gains will not meet 2050 needs, and climate stresses compound this challenge. However, there is good evidence that heat and drought resilience can be boosted through translating promising ideas into novel breeding technologies using powerful new tools in genetics and remote sensing, for example. Such technologies can also be applied to identify climate resilience traits from among the vast and largely untapped reserve of wheat genetic resources in collections worldwide. This review describes multi-pronged research opportunities at the focus of the Heat and Drought Wheat Improvement Consortium (coordinated by CIMMYT), which together create a pipeline to boost heat and drought resilience, specifically: improving crop design targets using big data approaches; developing phenomic tools for field-based screening and research; applying genomic technologies to elucidate the bases of climate resilience traits; and applying these outputs in developing next-generation breeding methods. The global impact of these outputs will be validated through the International Wheat Improvement Network, a global germplasm development and testing system that contributes key productivity traits to approximately half of the global wheat-growing area.

Development and validation of high-throughput and low-cost STARP assays for genes underpinning economically important traits in wheat.

KEY MESSAGE: We developed and validated 56 gene-specific semi-thermal asymmetric reverse PCR (STARP) markers for 46 genes of important wheat quality, biotic and abiotic stress resistance, grain yield, and adaptation-related traits for marker-assisted selection in wheat breeding. Development of high-throughput, low-cost, gene-specific molecular markers is important for marker-assisted selection in wheat breeding. In this study, we developed 56 gene-specific semi-thermal asymmetric reverse PCR (STARP) markers for wheat quality, tolerance to biotic and abiotic stresses, grain yield, and adaptation-related traits. The STARP assays were validated by (1) comparison of the assays with corresponding diagnostic STS/CAPS markers on 40 diverse wheat cultivars and (2) characterization of allelic effects based on the phenotypic and genotypic data of three segregating populations and 305 diverse wheat accessions from China and 13 other countries. The STARP assays showed the advantages of high-throughput, accuracy, flexibility, simple assay design, low operational costs, and platform compatibility. The state-of-the-art assays of this study provide a robust and reliable molecular marker toolkit for wheat breeding programs.

Quantitative Trait Loci Mapping for Spot Blotch Resistance in Two Biparental Mapping Populations of Bread Wheat.

Spot blotch (SB), caused by Bipolaris sorokiniana, is a major fungal disease of wheat in South Asia and South America. Two biparental mapping populations with 232 F2:7 progenies each were generated, with CIMMYT breeding lines CASCABEL and KATH as resistant parents and CIANO T79 as the common susceptible parent. The two populations were evaluated for field SB resistance in CIMMYT's Agua Fria station for three consecutive cropping seasons, with artificial inoculation. Genotyping was done with the DArTseq platform and approximately 1,500 high quality and nonredundant markers were used for quantitative trait loci (QTL) mapping. In both populations, a major QTL was found on chromosome 5A in the Vrn-A1 region, explaining phenotypic variations of 13.5 to 25.9%, which turned up to be less- or nonsignificant when days to heading and plant height were used as covariates in the analysis, implying a disease escape mechanism. Another major QTL was located on chromosome 5B in CASCABEL, accounting for 8.9 to 21.4% of phenotypic variation. Minor QTL were found on 4A and 4B in CASCABEL; 1B, 4B, and 4D in KATH; and 1B, 2B, and 4B in CIANO T79. Through an analysis of QTL projection onto the IWGSC Chinese Spring reference genome, the 5B QTL in CASCABEL was mapped in the Sb2 region, delimited by the single nucleotide polymorphism marker wsnp_Ku_c50354_55979952 and the simple sequence repeat marker gwm213, with a physical distance of about 14 Mb to the Tsn1 locus.

Four Consistent Loci Confer Adult Plant Resistance to Leaf Rust in the Durum Wheat Lines Heller#1 and Dunkler.

The durum wheat lines Heller#1 and Dunkler from the International Maize and Wheat Improvement Center Global Wheat Program showed moderate and stable adult plant resistance to leaf rust under high disease pressure over field environments in northwestern Mexico. Leaf rust phenotyping was performed on two recombinant inbred line (RIL) populations derived from crosses of Heller#1 and Dunkler with the susceptible parent Atred#2, conducted under artificially induced Puccinia triticina epidemics in 2013, 2014, 2015, and 2016. The Atred#2 × Heller#1 and Atred#2 × Dunkler populations were genotyped by single nucleotide polymorphism (SNP) platforms and diversity arrays technology markers, respectively. Four leaf rust resistance quantitative trait loci were detected simultaneously in the two RIL populations: Lr46, QLr.cim-2BC, QLr.cim-5BL, and QLr.cim-6BL based on phenotypic data across all four crop seasons. They explained 11.7 to 46.8%, 7.2 to 26.1%, 8.4 to 24.1%, and 12.4 to 28.5%, respectively, of the phenotypic variation for leaf rust resistance in Atred#2 × Heller#1 and 16.3 to 56.6%, 6.7 to 15.7%, 4.1 to 10.1%, and 5.1 to 20.2% of the variation in the Atred#2 × Dunkler population. Only the resistance allele of QLr.cim-2BC was from the susceptible parent Atred#2, and resistance alleles at other loci came from the resistant parents Heller#1 and Dunkler. The SNP markers closely linked to Lr46 and QLr.cim-2BC were converted to kompetitive allele specific PCR markers for use in marker-assisted selection to improve leaf rust resistance through crosses with Heller#1 and Dunkler sources.

Disease Resistance Evaluation of Elite CIMMYT Wheat Lines Containing the Coupled Fhb1 and Sr2 Genes.

Fusarium head blight (FHB) and stem rust are among the most devastating diseases of wheat worldwide. Fhb1 is the most widely utilized and the only isolated gene for FHB resistance, while Sr2 is a durable stem rust resistance gene used in rust-prone areas. The two loci are closely linked on the short arm of chromosome 3B and the two genes are in repulsion phase among cultivars. With climate change and the shift in Fusarium populations, it is imperative to develop wheat cultivars resistant to both diseases. The present study was dedicated to developing wheat germplasm combining Fhb1 and Sr2 resistance alleles in the International Maize and Wheat Improvement Center (CIMMYT)'s elite cultivars' backgrounds. Four recombinant inbred lines (RILs) in Hartog background that have the resistant Fhb1 and Sr2 alleles in coupled phase linkage were crossed with seven CIMMYT bread wheat lines, resulting in 208 lines. Molecular markers for both genes were employed in addition to the use of pseudo-black chaff (PBC) as a phenotypic marker for the selection of Sr2. At various stages of the selection process, progeny lines were assessed for FHB index, Fusarium damaged kernels (FDK), stem rust, and PBC expression as well as other diseases of interest (stripe rust and leaf spotting diseases). The 25 best lines were selected for CIMMYT's wheat breeding program. In addition to expressing resistance to FHB, most of these 25 lines have an acceptable level of resistance to other tested diseases. These lines will be useful for wheat breeding programs worldwide and potentially speed up the resistance breeding efforts against FHB and stem rust.

Effect of allele combinations at Ppd-1 loci on durum wheat grain filling at contrasting latitudes.

Flowering time is the most critical developmental stage in wheat, as it determines environmental conditions during grain filling. Thirty-five spring durum genotypes carrying all known allele variants at Ppd-1 loci were evaluated in fully irrigated field experiments for three years at latitudes of 41°N (Spain), 27°N (northern Mexico) and 19°N (southern Mexico). Relationships between weight of central grains of main spikes (W) and thermal time from flowering to maturity were described by a logistic equation. Differences in flowering time between the allele combination causing the earliest (GS100/Ppd-B1a) and the latest (Ppd-A1b/Ppd-B1a) flowering were 7, 20 and 18 days in Spain, northern Mexico and southern Mexico, respectively. Flowering delay drastically reduced the mean grain filling rate (R) and W at all sites. At autumn-sowing sites, an increase of 1°C in mean temperature during the first half of the grain filling period decreased W by 5.2 mg per grain. At these sites, W was strongly dependent on R. At the spring-sowing site (southern Mexico), W depended on both R and grain filling duration. Our results suggest that incorporating the allele combinations GS100/Ppd-B1a and GS105/Ppd-B1a (alleles conferring photoperiod insensitivity) in newly released varieties can reduce the negative effects of climate change on grain filling at the studied latitudes.

Genetics for low correlation between Fusarium head blight disease and deoxynivalenol (DON) content in a bread wheat mapping population.

KEY MESSAGE: Two QTL with major effects on DON content reduction were identified on chromosomes 3BL and 3DL, with the former showing minor and the latter showing no effects on FHB resistance. Deoxynivalenol (DON) contamination in food and feed is a major concern regarding Fusarium head blight (FHB) infection in wheat. However, relatively less attention has been paid on DON compared to FHB. In this study, a FHB-susceptible cultivar 'NASMA' was hybridized with a FHB-resistant CIMMYT breeding line 'IAS20*5/H567.71' to generate 197 recombinant inbred lines. The population was phenotyped for FHB and associated traits including DON accumulation in spray-inoculated field experiments at CIMMYT-Mexico across four years. Genotyping was performed by using the Illumina Infinium 15 K Beadchip and SSR markers. QTL mapping results indicated that the field FHB resistance was mainly controlled by QTL at Rht-D1 and Vrn-A1, along with a few minor QTL. For DON content, two major QTL were identified: the first located on chromosome 3BL (R2 of 16-24%), showing minor effects on FHB, and the second was on chromosome 3DL (R2 of 10-15%), exhibiting no effect on FHB resistance. It is likely that both DON QTL are new based on comparison with previous studies. This study indicates that resistance to DON accumulation and FHB disease could involve different genes, and the utilization of the two DON QTL in breeding could be helpful in further reducing DON contamination in food and feed.

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.

Genome Wide Association Study of Karnal Bunt Resistance in a Wheat Germplasm Collection from Afghanistan.

Karnal bunt disease of wheat, caused by the fungus Neovossia indica, is one of the most important challenges to the grain industry as it affects the grain quality and also restricts the international movement of infected grain. It is a seed-, soil- and airborne disease with limited effect of chemical control. Currently, this disease is contained through the deployment of host resistance but further improvement is limited as only a few genotypes have been found to carry partial resistance. To identify genomic regions responsible for resistance in a set of 339 wheat accessions, genome-wide association study (GWAS) was undertaken using the DArTSeq® technology, in which 18 genomic regions for Karnal bunt resistance were identified, explaining 5-20% of the phenotypic variation. The identified quantitative trait loci (QTL) on chromosome 2BL showed consistently significant effects across all four experiments, whereas another QTL on 5BL was significant in three experiments. Additional QTLs were mapped on chromosomes 1DL, 2DL, 4AL, 5AS, 6BL, 6BS, 7BS and 7DL that have not been mapped previously, and on chromosomes 4B, 5AL, 5BL and 6BS, which have been reported in previous studies. Germplasm with less than 1% Karnal bunt infection have been identified and can be used for resistance breeding. The SNP markers linked to the genomic regions conferring resistance to Karnal bunt could be used to improve Karnal bunt resistance through marker-assisted selection.

Correction to: Genetic analysis of multi-environmental spring wheat trials identifies genomic regions for locus-specific trade-offs for grain weight and grain number.

Unfortunately, the Fig. 1 of this original article was incorrectly published. The corrected Fig. 1 is given below.

Genetic analysis of multi-environmental spring wheat trials identifies genomic regions for locus-specific trade-offs for grain weight and grain number.

KEY MESSAGE: GWAS on multi-environment data identified genomic regions associated with trade-offs for grain weight and grain number. Grain yield (GY) can be dissected into its components thousand grain weight (TGW) and grain number (GN), but little has been achieved in assessing the trade-off between them in spring wheat. In the present study, the Wheat Association Mapping Initiative (WAMI) panel of 287 elite spring bread wheat lines was phenotyped for GY, GN, and TGW in ten environments across different wheat growing regions in Mexico, South Asia, and North Africa. The panel genotyped with the 90 K Illumina Infinitum SNP array resulted in 26,814 SNPs for genome-wide association study (GWAS). Statistical analysis of the multi-environmental data for GY, GN, and TGW observed repeatability estimates of 0.76, 0.62, and 0.95, respectively. GWAS on BLUPs of combined environment analysis identified 38 loci associated with the traits. Among them four loci-6A (85 cM), 5A (98 cM), 3B (99 cM), and 2B (96 cM)-were associated with multiple traits. The study identified two loci that showed positive association between GY and TGW, with allelic substitution effects of 4% (GY) and 1.7% (TGW) for 6A locus and 0.2% (GY) and 7.2% (TGW) for 2B locus. The locus in chromosome 6A (79-85 cM) harbored a gene TaGW2-6A. We also identified that a combination of markers associated with GY, TGW, and GN together explained higher variation for GY (32%), than the markers associated with GY alone (27%). The marker-trait associations from the present study can be used for marker-assisted selection (MAS) and to discover the underlying genes for these traits in spring wheat.

Identification of Novel Quantitative Trait Loci Linked to Crown Rot Resistance in Spring Wheat.

Crown rot (CR), caused by various Fusarium species, is a major disease in many cereal-growing regions worldwide. Fusarium culmorum is one of the most important species, which can cause significant yield losses in wheat. A set of 126 advanced International Maize and Wheat Improvement Center (CIMMYT) spring bread wheat lines were phenotyped against CR for field crown, greenhouse crown and stem, and growth room crown resistance scores. Of these, 107 lines were genotyped using Diversity Array Technology (DArT) markers to identify quantitative trait loci linked to CR resistance by genome-wide association study. Results of the population structure analysis grouped the accessions into three sub-groups. Genome wide linkage disequilibrium was large and declined on average within 20 cM (centi-Morgan) in the panel. General linear model (GLM), mixed linear model (MLM), and naïve models were tested for each CR score and the best model was selected based on quarantine-quarantine plots. Three marker-trait associations (MTAs) were identified linked to CR resistance; two of these on chromosome 3B were associated with field crown scores, each explaining 11.4% of the phenotypic variation and the third MTA on chromosome 2D was associated with greenhouse stem score and explained 11.6% of the phenotypic variation. Together, these newly identified loci provide opportunity for wheat breeders to exploit in enhancing CR resistance via marker-assisted selection or deployment in genomic selection in wheat breeding programs.

Resistance to Spot Blotch in Two Mapping Populations of Common Wheat Is Controlled by Multiple QTL of Minor Effects.

Spot blotch (SB) is an important fungal disease of wheat in South Asia and South America. Host resistance is regarded as an economical and environmentally friendly approach of controlling SB, and the inheritance of resistance is mostly quantitative. In order to gain a better understanding on the SB resistance mechanism in CIMMYT germplasm, two bi-parental mapping populations were generated, both comprising 232 F2:7 progenies. Elite CIMMYT breeding lines, BARTAI and WUYA, were used as resistant parents, whereas CIANO T79 was used as susceptible parent in both populations. The two populations were evaluated for field SB resistance at CIMMYT's Agua Fria station for three consecutive years, from the 2012⁻2013 to 2014⁻2015 cropping seasons. Phenological traits like plant height (PH) and days to heading (DH) were also determined. Genotyping was performed using the DArTSeq genotyping-by-sequencing (GBS) platform, and a few D-genome specific SNPs and those for phenological traits were integrated for analysis. The most prominent quantitative trait locus (QTL) in both populations was found on chromosome 5AL at the Vrn-A1 locus, explaining phenotypic variations of 7⁻27%. Minor QTL were found on chromosomes 1B, 3A, 3B, 4B, 4D, 5B and 6D in BARTAI and on chromosomes 1B, 2A, 2D and 4B in WUYA, whereas minor QTL contributed by CIANO T79 were identified on chromosome 1B, 1D, 3A, 4B and 7A. In summary, resistance to SB in the two mapping populations was controlled by multiple minor QTL, with strong influence from Vrn-A1.

Development and validation of KASP assays for genes underpinning key economic traits in bread wheat.

KEY MESSAGE: We developed and validated a robust marker toolkit for high-throughput and cost-effective screening of a large number of functional genes in wheat. Functional markers (FMs) are the most valuable markers for crop breeding programs, and high-throughput genotyping for FMs could provide an excellent opportunity to effectively practice marker-assisted selection while breeding cultivars. Here we developed and validated kompetitive allele-specific PCR (KASP) assays for genes that underpin economically important traits in bread wheat including adaptability, grain yield, quality, and biotic and abiotic stress resistances. In total, 70 KASP assays either developed in this study or obtained from public databases were validated for reliability in application. The validation of KASP assays were conducted by (a) comparing the assays with available gel-based PCR markers on 23 diverse wheat accessions, (b) validation of the derived allelic information using phenotypes of a panel comprised of 300 diverse cultivars from China and 13 other countries, and (c) additional testing, where possible, of the assays in four segregating populations. All KASP assays being reported were significantly associated with the relevant phenotypes in the cultivars panel and bi-parental populations, thus revealing potential application in wheat breeding programs. The results revealed 45 times superiority of the KASP assays in speed than gel-based PCR markers. KASP has recently emerged as single-plex high-throughput genotyping technology; this is the first report on high-throughput screening of a large number of functional genes in a major crop. Such assays could greatly accelerate the characterization of crossing parents and advanced lines for marker-assisted selection and can complement the inflexible, high-density SNP arrays. Our results offer a robust and reliable molecular marker toolkit that can contribute towards maximizing genetic gains in wheat breeding programs.