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Drought is one of the most adverse factors affecting plant growth and productivity. Identifying elite genotypes and their ideotypic traits conferring high yield potential and drought tolerance is critical in selecting and breeding drought‐tolerant wheat cultivars. In this study, we conducted field experiments at the Xinxiang Agricultural Comprehensive Experimental station in the North China Plain from 2018 to 2020 and assessed 209 wheat cultivars released since the 1940s under irrigated and nonirrigated conditions. Then, we selected drought‐tolerant cultivars by classifying them into four groups based on yield response to drought stress and several drought indices. Finally, the key ideotypic traits associated with high yield potential and drought tolerance were identified. Results indicated that the grain yield of the 209 cultivars decreased on average by 10.4% and 9.4% under nonirrigated treatment in 2018–2019 and 2019–2020, respectively, relative to full irrigation. The high‐yielding cultivars under both irrigation treatments are characterised by a compact plant type, larger thousand‐grain weight, larger chlorophyll content, higher leaf photosynthesis, shorter plant height and stay‐green traits. The stomatal and nonstomatal limitations are strongly associated with genotype yield performance, elucidating a potential mechanism underlying drought tolerance. Drought tolerance and yield stability of wheat cultivars have been improved through breeding over the past 70 years. Our findings enhance understanding of drought tolerance and identify genotypes and traits beneficial for breeding high‐yielding and drought‐tolerant cultivars. [ABSTRACT FROM AUTHOR]

Summary: Wheat needs different durations of vernalization, which accelerates flowering by exposure to cold temperature, to ensure reproductive development at the optimum time, as that is critical for adaptability and high yield. TaVRN1 is the central flowering regulator in the vernalization pathway and encodes a MADS‐box transcription factor (TF) that usually works by forming hetero‐ or homo‐dimers. We previously identified that TaVRN1 bound to an MADS‐box TF TaSOC1 whose orthologues are flowering activators in other plants. The specific function of TaSOC1 and the biological implication of its interaction with TaVRN1 remained unknown. Here, we demonstrated that TaSOC1 was a flowering repressor in the vernalization and photoperiod pathways by overexpression and knockout assays. We confirmed the physical interaction between TaSOC1 and TaVRN1 in wheat protoplasts and in planta, and further validated their genetic interplay. A Flowering Promoting Factor 1‐like gene TaFPF1‐2B was identified as a common downstream target of TaSOC1 and TaVRN1 through transcriptome and chromatin immunoprecipitation analyses. TaSOC1 competed with TaVRT2, another MADS‐box flowering regulator, to bind to TaVRN1; their coding genes synergistically control TaFPF1‐2B expression and flowering initiation in response to photoperiod and low temperature. We identified major haplotypes of TaSOC1 and found that TaSOC1‐Hap1 conferred earlier flowering than TaSOC1‐Hap2 and had been subjected to positive selection in wheat breeding. We also revealed that wheat SOC1 family members were important domestication loci and expanded by tandem and segmental duplication events. These findings offer new insights into the regulatory mechanism underlying flowering control along with useful genetic resources for wheat improvement. [ABSTRACT FROM AUTHOR]

Melatonin (Mel) is a multifunctional biomolecule found in both animals and plants. In plants, the biosynthesis of Mel from tryptophan (Trp) has been delineated to comprise of four consecutive reactions. However, while the genes encoding these enzymes in rice are well characterized no systematic evaluation of the overall pathway has, as yet, been published for wheat. In the current study, the relative contents of six Mel‐pathway‐intermediates including Trp, tryptamine (Trm), serotonin (Ser), 5‐methoxy tryptamine (5M‐Trm), N‐acetyl serotonin (NAS) and Mel, were determined in 24 independent tissues spanning the lifetime of wheat. These studies indicated that Trp was the most abundant among the six metabolites, followed by Trm and Ser. Next, the candidate genes expressing key enzymes involved in the Mel pathway were explored by means of metabolite‐based genome‐wide association study (mGWAS), wherein two TDC genes, a T5H gene and one SNAT gene were identified as being important for the accumulation of Mel pathway metabolites. Moreover, a 463‐bp insertion within the T5H gene was discovered that may be responsible for variation in Ser content. Finally, a ASMT gene was found via sequence alignment against its rice homolog. Validations of these candidate genes were performed by in vitro enzymatic reactions using proteins purified following recombinant expression in Escherichia coli, transient gene expression in tobacco, and transgenic approaches in wheat. Our results thus provide the first comprehensive investigation into the Mel pathway metabolites, and a swift candidate gene identification via forward‐genetics strategies, in common wheat. [ABSTRACT FROM AUTHOR]

Background and Aims Physiological and morphological traits play essential roles in wheat (Triticum aestivum) growth and development. In particular, photosynthesis is a limitation to yield. Increasing photosynthesis in wheat has been identified as an important strategy to increase yield. However, the genotypic variations and the genomic regions governing morphological, architectural and photosynthesis traits remain unexplored. Methods Here, we conducted a large-scale investigation of the phenological, physiological, plant architectural and yield-related traits, involving 32 traits for 166 wheat lines during 2018–2020 in four environments, and performed a genome-wide association study with wheat 90K and 660K single nucleotide polymorphism (SNP) arrays. Key Results These traits exhibited considerable genotypic variations in the wheat diversity panel. Higher yield was associated with higher net photosynthetic rate (r = 0.41, P < 0.01), thousand-grain weight (r = 0.36, P < 0.01) and truncated and lanceolate shape, but shorter plant height (r = −0.63, P < 0.01), flag leaf angle (r = −0.49, P < 0.01) and spike number per square metre (r = −0.22, P < 0.01). Genome-wide association mapping discovered 1236 significant stable loci detected in the four environments among the 32 traits using SNP markers. Trait values have a cumulative effect as the number of the favourable alleles increases, and significant progress has been made in determining phenotypic values and favourable alleles over the years. Eleven elite cultivars and 14 traits associated with grain yield per plot (GY) were identified as potential parental lines and as target traits to develop high-yielding cultivars. Conclusions This study provides new insights into the phenotypic and genetic elucidation of physiological and morphological traits in wheat and their associations with GY, paving the way for discovering their underlying gene control and for developing enhanced ideotypes in wheat breeding. [ABSTRACT FROM AUTHOR]

SUMMARY: Wheat (Triticum aestivum L.) radiation use efficiency (RUE) must be raised through crop breeding to further increase the yield potential, as the harvest index is now close to its theoretical limit. Field experiments including 209 wheat cultivars which have been widely cultivated in China since the 1940s were conducted in two growing seasons (2018–2019 and 2019–2020) to evaluate the variations of phenological, physiological, plant architectural, and yield‐related traits and their contributions to RUE and to identify limiting factors for wheat yield potential. The average annual genetic gain in grain yield was 0.60% (or 45.32 kg ha−1 year−1; R2 = 0.44, P < 0.01), mainly attributed to the gain in RUE (r = 0.85, P < 0.01). The net photosynthetic rates were positively and closely correlated with grain RUE and grain yield, suggesting source as a limiting factor to future yield gains. Thirty‐four cultivars were identified, exhibiting not only high RUE, but also traits contributing to high RUE and 11 other critical traits – of known genetic basis – as potential parents for breeding to improve yield and RUE. Our findings reveal wheat traits and the associated loci conferring RUE, which are valuable for facilitating marker‐assisted breeding to improve wheat RUE and yield potential. [ABSTRACT FROM AUTHOR]

Root hairs play an important role in absorbing water and nutrients in crop plants. Here we optimized high-throughput root hair length (RHL) and root hair density (RHD) phenotyping in wheat using a portable Dinolite™ microscope. A collection of 24 century wide spring wheat cultivars released between 1911 and 2016 were phenotyped for RHL and RHD. The results revealed significant variations for both traits with five and six-fold variation for RHL and RHD, respectively. RHL ranged from 1.01 mm to 1.77 mm with an average of 1.39 mm, and RHD ranged from 17.08 mm−2 to 20.8 mm−2 with an average of 19.6 mm−2. Agronomic and physiological traits collected from five different environments and their best linear unbiased predictions (BLUPs) were correlated with RHL and RHD, and results revealed that relative-water contents (RWC), biomass and grain per spike (GpS) were positively correlated with RHL in both water-limited and well-watered conditions. While RHD was negatively correlated with grain yield (GY) in four environments and their BLUPs. Both RHL and RHD had positive correlation indicating the possibility of simultaneous selection of both phenotypes during wheat breeding. The expression pattern of TaRSL4 gene involved in regulation of root hair length was determined in all 24 wheat cultivars based on RNA-seq data, which indicated the differentially higher expression of the A- and D- homeologues of the gene in roots, while B-homeologue was consistently expressed in both leaf and roots. The results were validated by qRT-PCR and the expression of TaRSL4 was consistently high in rainfed cultivars such as Chakwal-50, Rawal-87, and Margallah-99. Overall, the new phenotyping method for RHL and RHD along with correlations with morphological and physiological traits in spring wheat cultivars improved our understanding for selection of these phenotypes in wheat breeding. [ABSTRACT FROM AUTHOR]

Grain yield (GY) prediction for wheat based on canopy spectral reflectance can improve selection efficiency in breeding programs. Time-series spectral information from different growth stages such as flowering to maturity is considered to have high accuracy in predicting GY and combining this information from multiple growth stages could effectively improve prediction accuracy. For this, 207 wheat cultivars and breeding lines were grown in full and limited irrigation treatments, and their canopy spectral reflectance was measured at the flowering, early, middle, and late grain fill stages. The potential of temporal spectral information at multiple growth stages for GY prediction was evaluated by a new method based on stacking the multiple growth stages data. Twenty VIs derived from spectral reflectance were used as the input feature of a support vector regression (SVR) to predict GY at each growth stage. The predicted GY values at multiple growth stages were trained by multiple linear regression (MLR) to establish a second-level prediction model. Results suggested that the prediction accuracy (R2) of VIs data from single growth stages ranged from 0.60 to 0.66 and 0.35 to 0.42 in the full and limited irrigation treatments, respectively. The prediction accuracy was increased by an average of 0.06, 0.07, and 0.07 after stacking the VIs of two, three, and four growth stages, respectively, under full irrigation. Similarly, under limited irrigation, the prediction accuracy was increased by 0.03, 0.04, and 0.04 by stacking the VIs of two, three, and four growth stages, respectively. Stacking of VIs of multiple important growth stages can increase the accuracy of GY prediction and application of a stable stacking model could increase the usefulness of data obtained from different phenotyping platforms. [ABSTRACT FROM AUTHOR]

Summary: Rht‐B1b and Rht‐D1b, the 'Green Revolution' (GR) genes, greatly improved yield potential of wheat under nitrogen fertilizer application, but reduced coleoptile length, seedling vigor and grain weight. Thus, mining alternative reduced plant height genes without adverse effects is urgently needed.We isolated the causal gene of Rht24 through map‐based cloning and characterized its function using transgenic, physiobiochemical and transcriptome assays. We confirmed genetic effects of the dwarfing allele Rht24b with an association analysis and also traced its origin and distribution.Rht24 encodes a gibberellin (GA) 2‐oxidase, TaGA2ox‐A9. Rht24b conferred higher expression of TaGA2ox‐A9 in stems, leading to a reduction of bioactive GA in stems but an elevation in leaves at the jointing stage. Strikingly, Rht24b reduced plant height, but had no yield penalty; it significantly increased nitrogen use efficiency, photosynthetic rate and the expression of related genes. Evolutionary analysis demonstrated that Rht24b first appeared in wild emmer and was detected in more than half of wild emmer and wheat accessions, suggesting that it underwent both natural and artificial selection.These findings uncover an important genetic resource for wheat breeding and also provide clues for dissecting the regulatory mechanisms underlying GA‐mediated morphogenesis and yield formation. [ABSTRACT FROM AUTHOR]

It is important to understand the genetic gain achieved through selection of key yield traits for planning future breeding strategies in developing high yielding wheat (Triticum aestivum L.) cultivars. The aim of this study was to characterize the genetic changes and genotype × environment (G×E) interaction by additive main effect and multiplicative interactions (AMMI) for morphological, physiological, and yield component traits under five environments using 24 wheat cultivars released from 1911 to 2016 in Pakistan. There was a significant increase in grain yield (9.03 kg ha−1 yr−1, 0.37%), and plant height was reduced linearly (−0.26 cm yr−1, −0.33%). The traits waxiness, leaf rolling, harvest index, spike length, and grains per spike significantly increased but the gain was only 0.16–0.2% per year. Analysis of variance revealed that genotype, environment, and G×E interaction were highly significant (P <.01) for all traits except relative chlorophyll content, biomass, days to maturity, and number of spikes. Gene‐specific markers identified the durable resistance gene Lr67/Yr46/Sr55/Pm46 in obsolete cultivars as early as 1911, whereas the photoperiod‐insensitive allele Ppd‐D1a and reduced height alleles Rht‐B1b and Rht‐D1b were present only in the post‐1965 cultivars. Diversity analysis based on a 50K single nucleotide polymorphism genotyping array clearly differentiated temporal patterns in 24 cultivars, which was correlated with the agronomic performance of the cultivars. This dataset provided detailed insight into the performance of historical wheat cultivars and could help in devising wheat breeding strategies to focus on the traits contributing to grain yield and have slower rate of genetic progress. Core Ideas: The genetic gain in morphology of Pakistani bread wheat cultivars over 105 yr areas was assessed.Leaf rolling, waxiness, and grains/spikes associated with genetic gains in grain yield were achieved by breeding.The performance and stability of yield and yield‐related traits was analyzed for the different cultivars. [ABSTRACT FROM AUTHOR]

SUMMARY: High‐molecular‐weight glutenin subunits (HMW‐GS) are major components of seed storage proteins (SSPs) and largely determine the processing properties of wheat (Triticum aestivum) flour. HMW‐GS are encoded by the GLU‐1 loci and regulated at the transcriptional level by interaction between cis‐elements and transcription factors (TFs). We recently validated the function of conserved cis‐regulatory modules (CCRMs) in GLU‐1 promoters, but their interacting TFs remained uncharacterized. Here we identified a CCRM‐binding NAM‐ATAF‐CUC (NAC) protein, TaNAC100, through yeast one‐hybrid (Y1H) library screening. Transactivation assays demonstrated that TaNAC100 could bind to the GLU‐1 promoters and repress their transcription activity in tobacco (Nicotiana benthamiana). Overexpression of TaNAC100 in wheat significantly reduced the contents of HMW‐GS and other SSPs as well as total seed protein. This was confirmed by transcriptome analyses. Conversely, enhanced expression of TaNAC100 increased seed starch contents and expression of key starch synthesis‐related genes, such as TaGBSS1 and TaSUS2. Y1H assays also indicated TaNAC100 binding with the promoters of TaGBSS1 and TaSUS2. These results suggest that TaNAC100 functions as a hub controlling seed protein and starch synthesis. Phenotypic analyses showed that TaNAC100 overexpression repressed plant height, increased heading date, and promoted seed size and thousand kernel weight. We also investigated sequence variations in a panel of cultivars, but did not identify significant association of TaNAC100 haplotypes with agronomic traits. The findings not only uncover a useful gene for wheat breeding but also provide an entry point to reveal the mechanism underlying metabolic balance of seed storage products. Significance Statement: High‐molecular‐weight glutenin subunits (HMW‐GS) have a great effect on wheat (Triticum aestivum) quality. Here we identified a NAC transcription factor, TaNAC100, binding with HMW‐GS promoters. TaNAC100 overexpression in wheat reduced the contents of HMW‐GS and total seed protein, but increased seed starch content. TaNAC100 overproduction also significantly affects agronomic traits. The findings not only uncover a useful gene for wheat breeding but also provide an entry point to reveal the mechanism underlying metabolic balance of seed storage products. [ABSTRACT FROM AUTHOR]

Preharvest sprouting (PHS) significantly reduces grain yield and quality. Identification of genetic loci for PHS resistance will facilitate breeding sprouting-resistant wheat cultivars. In this study, we constructed a genetic map comprising 1,702 non-redundant markers in a recombinant inbred line (RIL) population derived from cross Yangxiaomai/Zhongyou9507 using the wheat 15K single-nucleotide polymorphism (SNP) assay. Four quantitative trait loci (QTL) for germination index (GI), a major indicator of PHS, were identified, explaining 4.6–18.5% of the phenotypic variances. Resistance alleles of Qphs.caas-3AL, Qphs.caas-3DL , and Qphs.caas-7BL were from Yangxiaomai, and Zhongyou9507 contributed a resistance allele in Qphs.caas-4AL. No epistatic effects were detected among the QTL, and combined resistance alleles significantly increased PHS resistance. Sequencing and linkage mapping showed that Qphs.caas-3AL and Qphs.caas-3DL corresponded to grain color genes Tamyb10-A and Tamyb10-D , respectively, whereas Qphs.caas-4AL and Qphs.caas-7BL were probably new QTL for PHS. We further developed cost-effective, high-throughput kompetitive allele-specific PCR (KASP) markers tightly linked to Qphs.caas-4AL and Qphs.caas-7BL and validated their association with GI in a test panel of cultivars. The resistance alleles at the Qphs.caas-4AL and Qphs.caas-7BL loci were present in 72.2 and 16.5% cultivars, respectively, suggesting that the former might be subjected to positive selection in wheat breeding. The findings provide not only genetic resources for PHS resistance but also breeding tools for marker-assisted selection. [ABSTRACT FROM AUTHOR]

Key message: We fine-mapped QBp.caas-3BL for black point resistance in an interval of 1.7 Mb containing five high-confidence annotated genes and developed a KASP marker suitable for selection of QBp.caas-3BL. Wheat black point, which occurs in most wheat-growing regions of the world, is detrimental to grain appearance, processing and nutrient quality. Mining and characterization of genetic loci for black point resistance are helpful for breeding resistant wheat cultivars. We previously identified a major QTL QBp.caas-3BL in a recombinant inbred line (RIL) population of Linmai 2/Zhong 892 across five environments. Here we confirmed the QTL in two additional environments. The genetic region of QBp.caas-3BL was enriched with newly developed markers. Using four sets of near isogenic lines, QBp.caas-3BL was narrowed down to a physical interval of approximately 1.7 Mb, including five annotated genes according to IWGSC reference genome. TraesCS3B02G404300, TraesCS3B02G404600 and TraesCS3B02G404700 were predicted as candidate genes based on the analyses of sequence polymorphisms and differential expression. We also converted a SNP of TraesCS3B02G404700 into a breeding-applicable KASP marker and verified its efficacy for marker-assisted breeding in a panel of germplasm. The findings not only lay a foundation for map-based cloning of QBp.caas-3BL but also provide a useful marker for selection of resistant cultivars genotypes in wheat breeding. [ABSTRACT FROM AUTHOR]

Key message: A genome-wide association analysis identified diverse loci for seedling and adult plant resistance to leaf rust and stripe rust. KASP markers were developed and validated for marker-assisted selection. Wheat leaf rust and stripe rust cause significant losses in many wheat producing regions worldwide. The objective of this study was to identify chromosome regions conferring resistance to both leaf rust and stripe rust at the seedling and adult plant stages. A diversity panel of 268 wheat lines, including 207 accessions from different wheat growing regions in China, and 61 accessions from foreign countries, were evaluated for leaf rust response at seedling stage using eight Chinese Puccinia triticina pathotypes, and also tested for leaf rust and stripe rust at adult plant stage in multiple field environments. The panel was genotyped with the Wheat 90 K Illumina iSelect SNP array. Genome-wide association mapping (GWAS) was performed using the mixed linear model (MLM). Twenty-two resistance loci including the known Lr genes, Lr1, Lr26, Lr3ka, LrZH22, and 18 potentially new loci were identified associated with seedling resistance, explaining 4.6 to 25.2% of the phenotypic variance. Twenty-two and 23 adult plant resistance (APR) QTL associated with leaf and stripe rust, respectively, were identified at adult stage, explaining 4.2–11.5% and 4.4–9.7% of the phenotypic variance. Among them, QLr-2BS was the potentially most valuable all-stage resistance gene. Seven and six consistent APR QTL were identified in multiple environments including best linear unbiased prediction (BLUP) data, respectively. Comparison with previously mapped resistance loci indicated that three of the seven leaf rust resistance APR QTL, and two of the six stripe rust resistance APR QTL were new. Four potentially pleiotropic APR QTL, including Lr46/Yr29, QLr-2AL.1/QYr-2AL.1, QLr-2AL.2/QYr-2AL.2, and QLr-5BL/QYr-5BL.1, were identified. Twelve associated SNPs were converted into kompetitive allele-specific PCR (KASP) markers and verified in bi-parental populations. The study reports genetic loci conferring resistance to both diseases, and the closely linked markers should be applicable for marker-assisted wheat breeding. [ABSTRACT FROM AUTHOR]

Key message: Two major QTL for tiller angle were identified on chromosomes 1AL and 5DL, and TaTAC-D1 might be the candidate gene for QTA.caas-5DL. An ideal plant architecture is important for achieving high grain yield in crops. Tiller angle (TA) is an important factor influencing yield. In the present study, 266 recombinant inbred lines (RILs) derived from a cross between Zhongmai 871 (ZM871) and its sister line Zhongmai 895 (ZM895) was used to map TA by extreme pool-genotyping and inclusive composite interval mapping (ICIM). Two quantitative trait loci (QTL) on chromosomes 1AL and 5DL were identified with reduced tiller angle alleles contributed by ZM895. QTA.caas-1AL was detected in six environments, explaining 5.4–11.2% of the phenotypic variances. The major stable QTL, QTA.caas-5DL, was identified in all eight environments, accounting for 13.8–24.8% of the phenotypic variances. The two QTL were further validated using BC1F4 populations derived from backcrosses ZM871/ZM895//ZM871 (121 lines) and ZM871/ZM895//ZM895 (175 lines). Gene TraesCS5D02G322600, located in the 5DL QTL and designated TaTAC-D1, had a SNP in the third exon with 'A' and 'G' in ZM871 and ZM895, respectively, resulting in a Thr169Ala amino acid change. A KASP marker based on this SNP was validated in two sets of germplasm, providing further evidence for the significant effects of TaTAC-D1 on TA. Thus extreme pool-genotyping can be employed to detect QTL for plant architecture traits and KASP markers tightly linked with the QTL can be used in wheat breeding programs targeting improved plant architecture. [ABSTRACT FROM AUTHOR]

Summary: The marriage of metabolomic approaches with genetic design has proven a powerful tool in dissecting diversity in the metabolome and has additionally enhanced our understanding of complex traits. That said, such studies have rarely been carried out in wheat. In this study, we detected 805 metabolites from wheat kernels and profiled their relative contents among 182 wheat accessions, conducting a metabolite‐based genome‐wide association study (mGWAS) utilizing 14 646 previously described polymorphic SNP markers. A total of 1098 mGWAS associations were detected with large effects, within which 26 candidate genes were tentatively designated for 42 loci. Enzymatic assay of two candidates indicated they could catalyse glucosylation and subsequent malonylation of various flavonoids and thereby the major flavonoid decoration pathway of wheat kernel was dissected. Moreover, numerous high‐confidence genes associated with metabolite contents have been provided, as well as more subdivided metabolite networks which are yet to be explored within our data. These combined efforts presented the first step towards realizing metabolomics‐associated breeding of wheat. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Key message: We identified four chromosome regions harboring QTL for grain yield-related traits, and breeder-friendly KASP markers were developed and validated for marker-assisted selection. Identification of major stable quantitative trait loci (QTL) for grain yield-related traits is important for yield potential improvement in wheat breeding. In the present study, 266 recombinant inbred lines (RILs) derived from a cross between Zhongmai 871 (ZM871) and its sister line Zhongmai 895 (ZM895) were evaluated for thousand grain weight (TGW), grain length (GL), grain width (GW), and grain number per spike (GNS) in 10 environments and for grain filling rate in six environments. Sixty RILs, with 30 higher and 30 lower TGW, respectively, were genotyped using the wheat 660 K SNP array for preliminary QTL mapping. Four genetic regions on chromosomes 1AL, 2BS, 3AL, and 5B were identified to have a significant effect on TGW-related traits. A set of Kompetitive Allele Specific PCR markers were converted from the SNP markers on the above target chromosomes and used to genotype all 266 RILs. The mapping results confirmed the QTL named Qgw.caas-1AL, Qgl.caas-3AL, Qtgw.caas-5B, and Qgl.caas-5BS on the targeted chromosomes, explaining 5.0–20.6%, 5.7–15.7%, 5.5–17.3%, and 12.5–20.5% of the phenotypic variation for GW, GL, TGW, and GL, respectively. A novel major QTL for GNS on chromosome 5BS, explaining 5.2–15.2% of the phenotypic variation, was identified across eight environments. These QTL were further validated using BC1F4 populations derived from backcrosses ZM871/ZM895//ZM871 (121 lines) and ZM871/ZM895//ZM895 (175 lines) and 186 advanced breeding lines. Collectively, selective genotyping is a simple, economic, and effective approach for rapid QTL mapping and can be generally applied to genetic mapping studies for important agronomic traits. [ABSTRACT FROM AUTHOR]

Key message: 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. [ABSTRACT FROM AUTHOR]

Modern breeding imposed selection for improved productivity that largely influenced the frequency of superior alleles underpinning traits of breeding interest. Therefore, molecular diagnosis for the allelic variations of such genes is important to manipulate beneficial alleles in wheat molecular breeding. We analyzed a diversity panel largely consisted of advanced lines derived from synthetic hexaploid wheats for allelic variation at 87 functional genes or loci of breeding importance using 124 high-throughput KASP markers. We also developed two KASP markers for water-soluble carbohydrate genes (TaSST-D1 and TaSST-A1) associated with plant height and thousand grain weight (TGW) in the diversity panel. KASP genotyping results indicated that beneficial alleles for genes underpinning flowering time (Ppd-D1 and Vrn-D3), thousand grain weight (TaCKX-D1, TaTGW6-A1, TaSus1-7B , and TaCwi-D1), water-soluble carbohydrates (TaSST-A1), yellow-pigment content (Psy-B1 and Zds-D1), and root lesion nematodes (Rlnn1) were fixed in diversity panel with frequency ranged from 96.4 to 100%. The association analysis of functional genes with agronomic and biochemical traits under well-watered (WW) and water-limited (WL) conditions revealed that 21 marker-trait associations (MTAs) were consistently detected in both moisture conditions. The major developmental genes such as Vrn-A1, Rht-D1 , and Ppd-B1 had the confounding effect on several agronomic traits including plant height, grain size and weight, and grain yield in both WW and WL conditions. The accumulation of favorable alleles for grain size and weight genes additively enhanced grain weight in the diversity panel. Graphical genotyping approach was used to identify accessions with maximum number of favorable alleles, thus likely to have high breeding value. These results improved our knowledge on the selection of favorable and unfavorable alleles through unconscious selection breeding and identified the opportunities to deploy alleles with effects in wheat breeding. [ABSTRACT FROM AUTHOR]

Wheat leaf rust (LR), caused by the obligate biotrophic fungus Puccinia triticina ( Pt), is a destructive foliar disease of common wheat ( Triticum aestivum L.) worldwide. The most effective, economic means to control the disease is resistant cultivars. The Romanian wheat line Fundulea 900 showed high resistance to LR in the field. To identify the basis of resistance to LR in Fundulea 900, a population of 188 F2:3 lines from the cross Fundulea 900/'Thatcher' was phenotyped for LR severity during the 2010-2011, 2011-2012 and 2012-2013 cropping seasons in the field at Baoding, Hebei Province. Bulked segregant analysis and simple sequence repeat markers were used to identify the quantitative trait loci ( QTLs) for LR adult-plant resistance in the population. Three QTLs were detected and designated as QLr.hebau-1 BL, QLr.hebau-2 DS and QLr.hebau-7 DS. Based on the chromosome positions and molecular marker tests, QLr.hebau-1 BL is Lr46, and QLr.hebau-7 DS is Lr34. QLr.hebau-2 DS was derived from 'Thatcher' and was close to Lr22. This result suggests that Lr22b may confer residual resistance on field nurseries when challenged with isolates virulent on Lr22b, or another gene linked to Lr22b confers this resistance from 'Thatcher'. This study confirms the value of Lr34 and Lr46 in breeding for LR resistance in China; the contribution of the QTL to chromosome 2D needs further validation. [ABSTRACT FROM AUTHOR]

Key message : Nine QTL for black point resistance in wheat were identified using a RIL population derived from a Linmai 2/Zhong 892 cross and 90K SNP assay. Abstract: Black point, discoloration of the embryo end of the grain, downgrades wheat grain quality leading to significant economic losses to the wheat industry. The availability of molecular markers will accelerate improvement of black point resistance in wheat breeding. The aims of this study were to identify quantitative trait loci (QTL) for black point resistance and tightly linked molecular markers, and to search for candidate genes using a high-density genetic linkage map of wheat. A recombinant inbred line (RIL) population derived from the cross Linmai 2/Zhong 892 was evaluated for black point reaction during the 2011-2012, 2012-2013 and 2013-2014 cropping seasons, providing data for seven environments. A high-density linkage map was constructed by genotyping the RILs with the wheat 90K single nucleotide polymorphism (SNP) chip. Composite interval mapping detected nine QTL on chromosomes 2AL, 2BL, 3AL, 3BL, 5AS, 6A, 7AL (2) and 7BS, designated as QBp.caas- 2AL, QBp.caas- 2BL, QBp.caas- 3AL, QBp.caas- 3BL, QBp.caas- 5AS, QBp.caas- 6A, QBp.caas- 7AL.1, QBp.caas- 7AL.2 and QBp.caas- 7BS, respectively. All resistance alleles, except for QBp.caas- 7AL.1 from Linmai 2, were contributed by Zhong 892. QBp.caas- 3BL, QBp.caas- 5AS, QBp.caas- 7AL.1, QBp.caas- 7AL.2 and QBp.caas- 7BS probably represent new loci for black point resistance. Sequences of tightly linked SNPs were used to survey wheat and related cereal genomes identifying three candidate genes for black point resistance. The tightly linked SNP markers can be used in marker-assisted breeding in combination with the kompetitive allele specific PCR technique to improve black point resistance. [ABSTRACT FROM AUTHOR]

Water soluble carbohydrates (WSC) in stems play an important role in buffering grain yield in wheat against biotic and abiotic stresses; however, knowledge of genes controlling WSC is very limited. We conducted a genome-wide association study (GWAS) using a high-density 90K SNP array to better understand the genetic basis underlying WSC, and to explore marker-based breeding approaches. WSC was evaluated in an association panel comprising 166 Chinese bread wheat cultivars planted in four environments. Fifty two marker-trait associations (MTAs) distributed across 23 loci were identified for phenotypic best linear unbiased estimates (BLUEs), and 11 MTAs were identified in two or more environments. Liner regression showed a clear dependence of WSC BLUE scores on numbers of favorable (increasing WSC content) and unfavorable alleles (decreasing WSC), indicating that genotypes with higher numbers of favorable or lower numbers of unfavorable alleles had higher WSC content. In silico analysis of flanking sequences of trait-associated SNPs revealed eight candidate genes related to WSC content grouped into two categories based on the type of encoding proteins, namely, defense response proteins and proteins triggered by environmental stresses. The identified SNPs and candidate genes related to WSC provide opportunities for breeding higher WSC wheat cultivars. [ABSTRACT FROM AUTHOR]

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. Abstract: 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. [ABSTRACT FROM AUTHOR]

Stripe rust is one of the most devastating diseases of wheat (Triticum aestivum) worldwide. Adult-plant resistance (APR) is an efficient approach to provide long-term protection of wheat from the disease. The Chinese winter wheat cultivar Zhong 892 has a moderate level of APR to stripe rust in the field. To determine the inheritance of the APR resistance in this cultivar, 273 F6 recombinant inbred lines (RILs) were developed from a cross between Linmai 2 and Zhong 892. The RILs were evaluated for maximum disease severity (MDS) in two sites during the 2011–2012, 2012–2013 and 2013–2014 cropping seasons, providing data for five environments. Illumina 90k SNP (single nucleotide polymorphism) chips were used to genotype the RILs and their parents. Composite interval mapping (CIM) detected eight QTL, namely QYr.caas-2AL, QYr.caas-2BL.3, QYr.caas-3AS, QYr.caas-3BS, QYr.caas-5DL, QYr.caas-6AL, QYr.caas-7AL and QYr.caas-7DS.1, respectively. All except QYr.caas-2BL.3 resistance alleles were contributed by Zhong 892. QYr.caas-3AS and QYr.caas-3BS conferred stable resistance to stripe rust in all environments, explaining 6.2–17.4% and 5.0–11.5% of the phenotypic variances, respectively. The genome scan of SNP sequences tightly linked to QTL for APR against annotated proteins in wheat and related cereals genomes identified two candidate genes (autophagy-related gene and disease resistance gene RGA1), significantly associated with stripe rust resistance. These QTL and their closely linked SNP markers, in combination with kompetitive allele specific PCR (KASP) technology, are potentially useful for improving stripe rust resistances in wheat breeding. [ABSTRACT FROM AUTHOR]

Kernel texture is a major factor influencing the classification and end use properties of wheat ( Triticum aestivum L.), and is mainly controlled by the Puroindoline a ( Pina) and Puroindoline b ( Pinb) genes. Recently, a new puroindoline gene, Puroindoline b- 2 ( Pin b- 2), was identified. In this study, 388 wheat cultivars and advanced breeding lines from the U.S. Pacific Northwest were investigated for frequencies of Puroindoline D1 alleles and Pinb- 2 variants 2 and 3. Results indicated that Pinb- D1b (74.0%) was the predominant genotype among hard wheats ( N = 196), the only other hard allele encountered was Pina- D1b (26.0%). Across all varieties, Pinb- 2v3 was the predominant genotype (84.5%) compared with Pinb- 2v2 (15.5%). However, among 240 winter wheat varieties (124 soft white, 15 club, 68 hard red and 33 hard white varieties), all carried Pinb- 2v3. Among spring wheats, Pinb- 2v2 and Pinb- 2v3 frequencies were more variable (soft white 25.0:75.0, hard red 58.2:41.8 and hard white 40.0:60.0, respectively). Kernel texture variation was analyzed using 247 of the 388 wheat varieties grown in multi-location factorial trials in up to 7 crop years. The range of variety means among the four groups, soft winter, soft spring, hard winter and hard spring, was on the order of 15-25 single kernel characterization system (SKCS) Hardness Index. The least significant difference for each of these trials ranged from 2.8 to 5.6 SKCS Hardness Index. Observations lead to the conclusion that Pinb- 2 variants do not exert a prominent effect on kernel texture, however, Pinb- 2 variants do identify features of wheat germ plasm structure in the U.S. Pacific Northwest. [ABSTRACT FROM AUTHOR]

Over the past century, environmental changes have significantly impacted wheat spike morphology, crucial for adaptation and grain yield. However, the changes in wheat spike modifications during this period remain largely unknown. This study examines 16 spike morphology traits in 830 accessions released from 1900 to 2020. It finds that spike weight, grain number per spike (GN), and thousand kernel weight have significantly increased, while spike length has no significant change. The increase in fertile spikelets is due to fewer degenerated spikelets, resulting in a higher GN. Genome‐wide association studies identified 49,994 significant SNPs, grouped into 293 genomic regions. The accumulation of favorable alleles in these genomic regions indicates the genetic basis for modification in spike morphology traits. Genetic network analysis of these genomic regions reveals the genetic basis for phenotypic correlations among spike morphology traits. The haplotypes of the identified genomic regions display obvious geographical differentiation in global accessions and environmental adaptation over the past 120 years. In summary, we reveal the genetic basis of adaptive evolution and the interactions of spike morphology, offering valuable resources for the genetic improvement of spike morphology to enhance environmental adaptation. [ABSTRACT FROM AUTHOR]

Grain yield is increasingly affected by climate factors such as drought and heat. To develop resilient and high-yielding cultivars, high-throughput phenotyping (HTP) techniques are essential for precise decisions in wheat breeding. The ability of unmanned aerial vehicle (UAV)-based multispectral imaging and ensemble learning methods to increase the accuracy of grain yield prediction in practical breeding work is evaluated in this study. For this, 211 winter wheat genotypes were planted under full and limited irrigation treatments, and multispectral data were collected at heading, flowering, early grain filling (EGF), and mid-grain filling (MGF) stages. Twenty multispectral vegetation indices (VIs) were estimated, and VIs with heritability greater than 0.5 were selected to evaluate the models across the growth stages under both irrigation treatments. A framework for ensemble learning was developed by combining multiple base models such as random forest (RF), support vector machine (SVM), Gaussian process (GP), and ridge regression (RR). The R2 values between VIs and grain yield for individual base models were ranged from 0.468 to 0.580 and 0.537 to 0.598 for grain yield prediction in full and limited irrigation treatments across growth stages, respectively. The prediction results of ensemble models were ranged from 0.491 to 0.616 and 0.560 to 0.616 under full and limited irrigation treatments respectively, and were higher than that of the corresponding base learners. Moreover, the grain yield prediction results were observed high at mid grain filling stage under both full (R2 = 0.625) and limited (R2 = 0.628) irrigation treatments through ensemble learning based stacking of four base learners. Further improvements in ensemble learning models can accelerate the use of UAV-based multispectral data for accurate predictions of complex traits like grain yield in wheat. [ABSTRACT FROM AUTHOR]

Pronounced anther extrusion (AE) is associated with field resistance to Fusarium head blight (FHB), one of the most devastating diseases of wheat globally. In this study, two recombinant inbred line (RIL) populations were used to map quantitative trait loci (QTL) for AE and field FHB resistance and to investigate the association of both traits at the genetic level. Furthermore, two panels of International Maize and Wheat Improvement Center (CIMMYT) wheat breeding lines were evaluated to describe the phenotypic association between the two traits in detail. Highly significant negative correlation was identified between AE and FHB severity in the two populations and the two panels, with r-values ranging from 0.55 to 0.74. QTL analysis in the two RIL populations identified 12 QTL for AE and nine for FHB resistance, of which five QTL located on chromosomes 3BL, 4BS, 4DS, 5AL, and 5BL were associated with both AE and FHB, collectively explaining over 50% of phenotypic variation for FHB. The QTL on chromosomes 4BS, 4DS, 5AL, and 5BL were closely linked to Rht-B1, Rht-D1, Vrn-A1, and Vrn-B1 genes, respectively. In conclusion, AE is closely related to field FHB resistance and could be used as a morphological marker in wheat breeding for field FHB resistance. [ABSTRACT FROM AUTHOR]

Uncovering the genetic basis and optimization of root system architecture (RSA) traits are crucial for modern wheat breeding. Genome-wide association mapping has become a powerful approach to dissect the genetic architecture of complex quantitative traits. In the present study, RSA traits, viz. total root length (TRL), total root area, average root diameter and number of root tips in a diverse panel of 165 elite wheat cultivars from the Yellow and Huai River Valley Facultative Wheat Region of China were evaluated as seedlings in hydroponic culture and in the field to identify loci significantly associated with those traits. The diverse panel was genotyped using the wheat 90 K and 660 K SNP arrays, and a genome-wide association study using a mixed linear model identified 28 and 4 loci significantly associated with RSA traits in hydroponic culture and in the field, explaining 8.8–15.6% and 8.9–12.6% of phenotypic variances, respectively. Seven loci for RSA traits co-located with known genes or quantitative trait loci (QTL), whereas the other 22 were potentially new. Linear regression between favorable alleles and RSA traits suggested that QTL pyramiding should be effective in optimizing root systems. Two candidate genes for RSA traits were identified, including genes encoding calcium dependent protein kinase and E3-Ubiquitin protein ligase. This study provides novel insights into the genetic architecture of RSA traits. [ABSTRACT FROM AUTHOR]

Background: Plant height is an important selection target since it is associated with yield potential, stability and particularly with lodging resistance in various environments. Rapid and cost-effective estimation of plant height from airborne devices using a digital surface model can be integrated with academic research and practical wheat breeding programs. A bi-parental wheat population consisting of 198 doubled haploid lines was used for time-series assessments of progress in reaching final plant height and its accuracy was assessed by quantitative genomic analysis. UAV-based data were collected at the booting and mid-grain fill stages from two experimental sites and compared with conventional measurements to identify quantitative trait loci (QTL) underlying plant height. Results: A significantly high correlation of R2 = 0.96 with a 5.75 cm root mean square error was obtained between UAV-based plant height estimates and ground truth observations at mid-grain fill across both sites. Correlations for UAV and ground-based plant height data were also very high (R2 = 0.84–0.85, and 0.80–0.83) between plant height at the booting and mid-grain fill stages, respectively. Broad sense heritabilities were 0.92 at booting and 0.90–0.91 at mid-grain fill across sites for both data sets. Two major QTL corresponding to Rht-B1 on chromosome 4B and Rht-D1 on chromosome 4D explained 61.3% and 64.5% of the total phenotypic variations for UAV and ground truth data, respectively. Two new and stable QTL on chromosome 6D seemingly associated with accelerated plant growth was identified at the booting stage using UAV-based data. Genomic prediction accuracy for UAV and ground-based data sets was significantly high, ranging from r = 0.47–0.55 using genome-wide and QTL markers for plant height. However, prediction accuracy declined to r = 0.20–0.31 after excluding markers linked to plant height QTL. Conclusion: This study provides a fast way to obtain time-series estimates of plant height in understanding growth dynamics in bread wheat. UAV-enabled phenotyping is an effective, high-throughput and cost-effective approach to understand the genetic basis of plant height in genetic studies and practical breeding. [ABSTRACT FROM AUTHOR]

Highlights • An unmanned aerial vehicle (UAV) was optimized and used for non-destructive high-throughput phenotyping of NDVI. • UAV-NDVI measurements were highly consistent with ground data captured by a handheld Greenseeker. • UAV-NDVI explained significant variations in biomass and grain yield. • UAV-NDVI was accurate and can be used for selection of high yielding genotypes during grain-filling stages in large breeding programs. Abstract Wheat improvement programs require rapid assessment of large numbers of individual plots across multiple environments. Vegetation indices (VIs) that are mainly associated with yield and yield-related physiological traits, and rapid evaluation of canopy normalized difference vegetation index (NDVI) can assist in-season selection. Multi-spectral imagery using unmanned aerial vehicles (UAV) can readily assess the VIs traits at various crop growth stages. Thirty-two wheat cultivars and breeding lines grown in limited irrigation and full irrigation treatments were investigated to monitor NDVI across the growth cycle using a Sequoia sensor mounted on a UAV. Significant correlations ranging from R2 = 0.38 to 0.90 were observed between NDVI detected from UAV and Greenseeker (GS) during stem elongation (SE) to late grain gilling (LGF) across the treatments. UAV-NDVI also had high heritabilities at SE (h2 = 0.91), flowering (F)(h2 = 0.95), EGF (h2 = 0.79) and mid grain filling (MGF) (h2 = 0.71) under the full irrigation treatment, and at booting (B) (h2 = 0.89), EGF (h2 = 0.75) in the limited irrigation treatment. UAV-NDVI explained significant variation in grain yield (GY) at EGF (R2 = 0.86), MGF (R2 = 0.83) and LGF (R2 = 0.89) stages, and results were consistent with GS-NDVI. Higher correlations between UAV-NDVI and GY were observed under full irrigation at three different grain-filling stages (R2 = 0.40, 0.49 and 0.45) than the limited irrigation treatment (R2 = 0.08, 0.12 and 0.14) and GY was calculated to be 24.4% lower under limited irrigation conditions. Pearson correlations between UAV-NDVI and GY were also low ranging from r = 0.29 to 0.37 during grain-filling under limited irrigation but higher than GS-NDVI data. A similar pattern was observed for normalized difference red-edge (NDRE) and normalized green red difference index (NGRDI) when correlated with GY. Fresh biomass estimated at late flowering stage had significant correlations of r = 0.30 to 0.51 with UAV-NDVI at EGF. Some genotypes Nongda 211, Nongda 5181, Zhongmai 175 and Zhongmai 12 were identified as high yielding genotypes using NDVI during grain-filling. In conclusion, a multispectral sensor mounted on a UAV is a reliable high-throughput platform for NDVI measurement to predict biomass and GY and grain-filling stage seems the best period for selection. [ABSTRACT FROM AUTHOR]

Abstract We developed and validated high-throughput Kompetitive Allele-Specific PCR (KASP) assays for key genes underpinning bread-making quality, including the wbm gene on chromosome 7AL and over-expressed glutenin Bx7 OE (Glu-B1al) gene. Additionally, we used pre-existing KASP assay for Sec1 (1B.1R translocation) gene on chromosome 1B. The newly developed KASP assays were compared with gel-based markers for reliability and phenotypically validated in a diversity panel for Mixograph, Rapid Visco Analyzer (RVA) and Mixolab traits. Genotypes carrying the 1B.1R translocation had significantly lower Mixolab parameters than those without the translocation. Similarly, superior effects of the wbm+ and Bx7 OE alleles on Mixograph and RVA properties and their extremely low frequencies in global wheat collections supported the idea of using these genes for bread-making quality improvement. The allele frequencies of wbm + and Bx7 OE were extremely low in historical Chinese and CIMMYT wheat germplasm, but were relatively higher in synthetic hexaploid wheats and their breeding derivatives. In both the Vavilov and Watkins global landrace collections, the frequency of wbm+ was 6.4 and 3.5%, and frequency of Bx7 OE was 3.2% and 7.0%, respectively. The high-throughput marker resources and large-scale global germplasm screening provided further opportunities to exploit these genes in wheat breeding to enhance bread-making quality. Highlights • High-throughput KASP markers were developed for three important quality genes, Bx7 OE , wbm and 1BL.1RS in bread wheat. • Significant allelic effects were identified in a diversity panel. • Screening global landraces and cultivar collections identified candidates with superior alleles. • The use of KASP markers could help to fine tune bread-making quality in wheat breeding. [ABSTRACT FROM AUTHOR]

Grain yield (GY) is a primary trait for phenotype selection in crop breeding. Rapid and cost-effective prediction of GY before harvest from remote sensing platforms can be integrated with practical breeding activities. In this study, a natural population containing 166 wheat cultivars and elite lines was used for time-series prediction of GY using ground-based hyperspectral remote sensing. Canopy hyperspectral data (350–2500 nm) was collected at the flowering, early grain-filling (EGF), mid grain-filling (MGF), and late grain-filling (LGF) stages under four environments. GY was predicted by using full bands reflectance as input of multi-layer neural network. Genome-wide association study (GWAS) was performed using 373,106 markers from 660 K and 90 K single-nucleotide polymorphism (SNP) arrays in 166 wheat genotypes. Prediction accuracy for GY characterized by R 2 values were 0.68, 0.69, 0.76, and 0.65 at flowering, EGF, MGF, and LGF, respectively. Among the 26 loci identified by predicted GY, 13 were located in similar positions to previously reported loci related to yield, and another 13 were potentially new loci. Linear regression (R 2) ranged from 0.87 to 0.94 indicating that distinct cumulative effects of favorable alleles detected by predicted GY were increasing as compared to measured GY. This study highlights the feasibility of combining remote sensing with machine learning for wheat breeding decisions and to understand the underlying genetic basis of crop yield. • The use of hyperspectral reflectance to predict wheat yield is investigated. • Higher accuracy of yield prediction at the mid grain-filling stage. • Predicted yield can detect QTLs that are consistent with the measured yield. [ABSTRACT FROM AUTHOR]

Ferulic acid is an important bioactive compound in wheat grains and has great effect on dietary health. Identification of genetic loci can facilitate breeding wheat cultivars with higher ferulic acid content (FAC). Here a genome-wide association study (GWAS) was conducted to identify genetic loci controlling FAC in wheat grain using 90K and 660K chips in a diversity panel of wheat cultivars. Eight major loci for FAC, FAC-1B , FAC-2A , FAC-4A-I , FAC-4A-II , FAC-6B , FAC-7B – I , FAC-7B - II and FAC-7B - III were detected and each explained approximately 10% of the phenotypic variances. The favorable alleles of the major loci have significantly accumulative effects on FAC. A group of varieties with more favorable alleles and higher FAC was also identified according to genotypic and phenotypic analyses. Two SNPs closely associated with FAC-4A-I and FAC-6B , respectively, were successfully converted to flexible kompetitive allele-specific PCR (KASP) markers to facilitate marker-assisted selection in breeding. The findings not only supply useable materials for food industry and breeding, but also lay a foundation for dissecting genetic architecture underpinning FAC in wheat. [Display omitted] • Identification of wheat genetic loci for ferulic acid content (FAC) facilitates breeding high-FAC varieties. • Major loci for FAC and wheat varieties with more favorable alleles and higher FAC were identified using SNP chips. • These outcomes dissected genetic architecture underpinning FAC and provided useable materials and tools for wheat high-FAC breeding. [ABSTRACT FROM AUTHOR]

Abstract: High-molecular-weight glutenin (HMW-GS) and low-molecular-weight glutenin (LMW-GS) subunits play an important role in determining wheat quality. To clarify the contribution of each subunit/allele to processing quality, 25 near-isogenic lines with different HMW-GS and LMW-GS compositions grown at two locations during the 2010 cropping season were used to investigate the effects of allelic variation on milling parameters, mixograph properties, raw white Chinese noodle (RWCN) and northern style Chinese steamed bread (NSCSB) qualities. The results showed that Glu-B1 and Glu-B3 made a large contribution to determining mixograph properties and processing quality, respectively. Subunit pairs 17 + 18 and 5 + 10, and alleles Glu-A3b, Glu-A3d, Glu-B3g and Glu-D3f made significant contributions to mixograph properties and no significant difference was detected on most parameters of RWCN and NSCSB for the allelic variation of HMW-GS and LMW-GS. The allelic interactions among glutenin loci had significant effects on wheat quality. The line with 1, 17 + 18, 2 + 12, Glu-A3c, Glu-B3b, Glu-D3c associated with superior mixograph properties, the line with 1, 7 + 9, 2 + 12, Glu-A3c, Glu-B3d, Glu-D3c had superior viscoelasticity of RWCN, and the line with 1, 7 + 9, 2 + 12, Glu-A3e, Glu-B3b, Glu-D3c had the highest total score of NSCSB. These results provide useful information for genetic improvement of the qualities of traditional Chinese wheat products. [Copyright &y& Elsevier]

Abstract: Phenolic acid concentrations were determined in 37 Chinese commercial winter wheat cultivars grown at a single site over two seasons, and fractions comprising free and bound types were analyzed using HPLC with measurements of individual phenolic acids in each fraction. Most of the parameters were significantly influenced by cultivar, season, and their interaction effects, with cultivar variance being predominant. Wide ranges of concentration among the 37 cultivars were observed. The average concentration of bound type was 661 μg g−1 of dm, making up 97.5% of the phenolic acid determined with ferulic accounting for 70.7% of it, while free type made up only 2.5% of the phenolic acid determined with syringic accounting for 44.7% of it. Bound type was the predominant source to the grain phenolic acid concentrations determined. There were highly significant and positive correlations between bound ferulic concentration and total bound phenolic acid concentration, and between free syringic concentration and total free phenolic acid concentration. Cultivars Liangxing 66 and Zhongmai 895 were stable in concentration of components of phenolic acids across seasons, with high values of free and bound phenolic acids indicating they could be selected as parents in wheat breeding for health beneficial phenolic acid. [Copyright &y& Elsevier]