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Plant nitrogen assimilation and use efficiency in the seedling's root system are beneficial for adult plants in field condition for yield enhancement. Identification of the genetic basis between root traits and N uptake plays a crucial role in wheat breeding. In the present study, 198 doubled haploid lines from the cross of Yangmai 16/Zhongmai 895 were used to identify quantitative trait loci (QTLs) underpinning four seedling biomass traits and five root system architecture (RSA) related traits. The plants were grown under hydroponic conditions with control, low and high N treatments (Ca(NO3)2·4H2O at 0, 0.05 and 2.0 mmol L−1, respectively). Significant variations among the treatments and genotypes, and positive correlations between seedling biomass and RSA traits (r=0.20 to 0.98) were observed. Inclusive composite interval mapping based on a high-density map from the Wheat 660K single nucleotide polymorphisms (SNP) array identified 51 QTLs from the three N treatments. Twelve new QTLs detected on chromosomes 1AL (1) in the control, 1DS (2) in high N treatment, 4BL (5) in low and high N treatments, and 7DS (3) and 7DL (1) in low N treatments, are first reported in influencing the root and biomass related traits for N uptake. The most stable QTLs (RRS.caas-4DS) on chromosome 4DS, which were related to ratio of root to shoot dry weight trait, was in close proximity of the Rht-D1 gene, and it showed high phenotypic effects, explaining 13.1% of the phenotypic variance. Twenty-eight QTLs were clustered in 12 genetic regions. SNP markers tightly linked to two important QTLs clusters C10 and C11 on chromosomes 6BL and 7BL were converted to kompetitive allele-specific PCR (KASP) assays that underpin important traits in root development, including root dry weight, root surface area and shoot dry weight. These QTLs, clusters and KASP assays can greatly improve the efficiency of selection for root traits in wheat breeding programmes.

Stem lignin content (SLC) in common wheat (Triticum aestivum L.) contributes to lodging resistance. Caffeic acid 3-O-methyltransferase (COMT) is a key enzyme involved in lignin biosynthesis. Characterization of TaCOMT genes and development of gene-specific markers could enable marker-assisted selection in wheat breeding. In the present study, the full-length genomic DNA (gDNA) sequences of TaCOMT genes located on chromosomes 3A, 3B, and 3D were cloned by homologous cloning. Two allelic variants, TaCOMT-3Ba and TaCOMT-3Bb, were identified and differed by a 222-bp insertion/deletion (InDel) in the 3′-untranslated region (3′-UTR). A co-dominant gene-specific marker based on this InDel was developed and designated as TaCOMT-3BM. A total of 157 wheat cultivars and advanced lines grown in four environments were used to validate the associations between allelic patterns and SLC. The SLC of cultivars with TaCOMT-3Ba was significantly (P

Background Phosphorus (P) is an important in ensuring plant morphogenesis and grain quality, therefore an efficient root system is crucial for P-uptake. Identification of useful loci for root morphological and P uptake related traits at seedling stage is important for wheat breeding. The aims of this study were to evaluate phenotypic diversity of Yangmai 16/Zhongmai 895 derived doubled haploid (DH) population for root system architecture (RSA) and biomass related traits (BRT) in different P treatments at seedling stage using hydroponic culture, and to identify QTL using 660 K SNP array based high-density genetic map. Results All traits showed significant variations among the DH lines with high heritabilities (0.76 to 0.91) and high correlations (r = 0.59 to 0.98) among all traits. Inclusive composite interval mapping (ICIM) identified 34 QTL with 4.64–20.41% of the phenotypic variances individually, and the log of odds (LOD) values ranging from 2.59 to 10.43. Seven QTL clusters (C1 to C7) were mapped on chromosomes 3DL, 4BS, 4DS, 6BL, 7AS, 7AL and 7BL, cluster C5 on chromosome 7AS (AX-109955164 - AX-109445593) with pleiotropic effect played key role in modulating root length (RL), root tips number (RTN) and root surface area (ROSA) under low P condition, with the favorable allele from Zhongmai 895. Conclusions This study carried out an imaging pipeline-based rapid phenotyping of RSA and BRT traits in hydroponic culture. It is an efficient approach for screening of large populations under different nutrient conditions. Four QTL on chromosomes 6BL (2) and 7AL (2) identified in low P treatment showed positive additive effects contributed by Zhongmai 895, indicating that Zhongmai 895 could be used as parent for P-deficient breeding. The most stable QTL QRRS.caas-4DS for ratio of root to shoot dry weight (RRS) harbored the stable genetic region with high phenotypic effect, and QTL clusters on 7A might be used for speedy selection of genotypes for P-uptake. SNPs closely linked to QTLs and clusters could be used to improve nutrient-use efficiency.

Unmanned aerial vehicle (UAV) based remote sensing is a promising approach for non-destructive and high-throughput assessment of crop water and nitrogen (N) efficiencies. In this study, UAV was used to evaluate two field trials using four water (T0 = 0 mm, T1 = 80 mm, T2 = 120 mm, and T3 = 160 mm), and four N (T0 = 0, T1 = 120 kg ha-1, T2 = 180 kg ha-1, and T3 = 240 kg ha-1) treatments, respectively, conducted on three wheat genotypes at two locations. Ground-based destructive data of water and N indictors such as biomass and N contents were also measured to validate the aerial surveillance results. Multispectral traits including red normalized difference vegetation index (RNDVI), green normalized difference vegetation index (GNDVI), normalized difference red-edge index (NDRE), red-edge chlorophyll index (RECI) and normalized green red difference index (NGRDI) were recorded using UAV as reliable replacement of destructive measurements by showing high r values up to 0.90. NGRDI was identified as the most efficient non-destructive indicator through strong prediction values ranged from R 2 = 0.69 to 0.89 for water use efficiencies (WUE) calculated from biomass (WUE.BM), and R 2 = 0.80 to 0.86 from grain yield (WUE.GY). RNDVI was better in predicting the phenotypic variations for N use efficiency calculated from nitrogen contents of plant samples (NUE.NC) with high R 2 values ranging from 0.72 to 0.94, while NDRE was consistent in predicting both NUE.NC and NUE.GY by 0.73 to 0.84 with low root mean square errors. UAV-based remote sensing demonstrates that treatment T2 in both water 120 mm and N 180 kg ha-1 supply trials was most appropriate dosages for optimum uptake of water and N with high GY. Among three cultivars, Zhongmai 895 was highly efficient in WUE and NUE across the water and N treatments. Conclusively, UAV can be used to predict time-series WUE and NUE across the season for selection of elite genotypes, and to monitor crop efficiency under varying N and water dosages.

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 Bx7OE (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 Bx7OE 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 Bx7OE 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 Bx7OE 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.

GWAS identified 36 potentially new loci for wheat stem water-soluble carbohydrate (WSC) contents and 13 pleiotropic loci affecting WSC and thousand-kernel weight. Five KASP markers were developed and validated. Water-soluble carbohydrates (WSC) reserved in stems contribute significantly to grain yield (GY) in wheat. However, knowledge of the genetic architecture underlying stem WSC content (SWSCC) is limited. In the present study, 166 diverse wheat accessions from the Yellow and Huai Valleys Winter Wheat Zone of China and five other countries were grown in four well-watered environments. SWSCC at 10 days post-anthesis (10DPA), 20DPA and 30DPA, referred as WSC10, WSC20 and WSC30, respectively, and thousand-kernel weight (TKW) were assessed. Correlation analysis showed that TKW was significantly and positively correlated with WSC10 and WSC20. Genome-wide association study was performed on SWSCC and TKW with 373,106 markers from the wheat 660 K and 90 K SNP arrays. Totally, 62 stable loci were detected for SWSCC, with 36, 24 and 19 loci for WSC10, WSC20 and WSC30, respectively; among these, 36 are potentially new, 16 affected SWSCC at two or three time-points, and 13 showed pleiotropic effects on both SWSCC and TKW. Linear regression showed clear cumulative effects of favorable alleles for increasing SWSCC and TKW. Genetic gain analyses indicated that pyramiding favorable alleles of SWSCC had simultaneously improved TKW. Kompetitive allele-specific PCR markers for five pleiotropic loci associated with both SWSCC and TKW were developed and validated. This study provided a genome-wide landscape of the genetic architecture of SWSCC, gave a perspective for understanding the relationship between WSC and GY and explored the theoretical basis for co-improvement of WSC and GY. It also provided valuable loci and markers for future breeding.

Crop yields need to be improved in a sustainable manner to meet the expected worldwide increase in population over the coming decades as well as the effects of anticipated climate change. Recently, genomics-assisted breeding has become a popular approach to food security; in this regard, the crop breeding community must better link the relationships between the phenotype and the genotype. While high-throughput genotyping is feasible at a low cost, highthroughput crop phenotyping methods and data analytical capacities need to be improved. High-throughput phenotyping offers a powerful way to assess particular phenotypes in large-scale experiments, using high-tech sensors, advanced robotics, and imageprocessing systems to monitor and quantify plants in breeding nurseries and field experiments at multiple scales. In addition, new bioinformatics platforms are able to embrace large-scale, multidimensional phenotypic datasets. Through the combined analysis of phenotyping and genotyping data, environmental responses and gene functions can now be dissected at unprecedented resolution. This will aid in finding solutions to currently limited and incremental improvements in crop yields.

The content and composition of seed storage proteins is largely responsible for wheat end-use quality. They mainly consist of polymeric glutenins and monomeric gliadins. According to their electrophoretic mobility, gliadins and glutenins are subdivided into several fractions. Glutenins are classified as high molecular weight or low molecular weight glutenin subunits (HMW-GSs and LMW-GSs, respectively). LMW-GSs are encoded by multigene families located at the orthologous Glu-3 loci. We designed a set of 16 single-nucleotide polymorphism (SNP) markers that are able to detect SDS-PAGE alleles at the Glu-A3 and Glu-B3 loci. The SNP markers captured the diversity of alleles in 88 international reference lines and 27 Mexican cultivars, when compared to SDS-PAGE and STS markers, however, showed a slightly larger percent of multiple alleles, mainly for Glu-B3. SNP markers were then used to determine the Glu-1 and Glu-3 allele composition in 54 CIMMYT historical lines and demonstrated to be useful tool for breeding programs to improve wheat end product properties.

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. Electronic supplementary material The online version of this article (10.1186/s13007-019-0419-7) contains supplementary material, which is available to authorized users.

The simultaneous improvement of protein content (PC) and grain yield (GY) in bread wheat (Triticum aestivum L.) under low-input management enables the development of resource-use efficient varieties that combine high grain yield potential with desirable end-use quality. However, the complex mechanisms of genotype, management, and growing season, and the negative correlation between PC and GY complicate the simultaneous improvement of PC and GY under low-input management. To identify favorable genotypes for PC and GY under low-input management, this study used 209 wheat varieties, including strong gluten, medium-strong gluten, medium gluten, weak gluten, winter, semi-winter, weak-spring, and spring types, which has been promoted from the 1980s to the 2010s. Allelic genotyping, performed using kompetitive allele-specific polymerase chain reaction (KASP) technology, found 69 types of GY-PC allelic combinations in the tested materials. Field trials were conducted with two growing season treatments (2018–2019 and 2019–2020) and two management treatments (conventional management and low-input management). Multi-environment analysis of variance showed that genotype, management, and growing season had extremely substantial effects on wheat GY and PC, respectively, and the interaction of management × growing season also had extremely significant effects on wheat GY. According to the three-sigma rule of the normal distribution, the GY of wheat varieties Liangxing 66 and Xinmai 18 were stable among the top 15.87% of all tested materials with high GY, and their PC reached mean levels under low-input management, but also stably expressed high GY and high PC under conventional management, which represents a great development potential. These varieties can be used as cultivars of interest for breeding because TaSus1-7A, TaSus1-7B, TaGW2-6A, and TaGW2-6B, which are related to GY, and Glu-B3, which is related to PC, carry favorable alleles, among which Hap-1/2, the allele of TaSus1-7A, and Glu-B3b/d/g/i, the allele of Glu-B3, can be stably expressed. Our results may be used to facilitate the development of high-yielding and high-quality wheat varieties under low-input management, which is critical for sustainable food and nutrition security.

Many physiological traits are associated with grain yield and yield-related traits in wheat. The aim of the present study was to identify quantitative trait loci (QTL) for physiological traits, including ground cover, normalized difference in vegetation index and canopy temperature depression, and closely linked molecular markers for marker-assisted breeding. Two hundred and forty-six F8 recombinant inbred lines (RILs) come from the Zhou 8425B/Chinese Spring cross were genotyped using the high-density Illumina iSelect 90K single nucleotide polymorphism (SNP) assay. Field trials were conducted under irrigated conditions at Zhengzhou and Zhoukou in Henan province, during the 2012–2013 and 2013–2014 cropping seasons. Analysis of variance of physiological traits showed significant differences (P

Bread-making quality is a core trait for wheat breeding programs. Recently, the expression of a novel gene named wheat bread making (wbm) gene has been associated with good bread-making quality. In this study, 54 historical and modern bread wheat genotypes from CIMMYT were screened by PCR marker for the presence of the allele associated with high wbm expression. Eight of the 54 wheat genotypes tested positive for the wbm allele and the genotype Waxwing was identified as the most likely donor of the allele in part of CIMMYT germplasm. The wbm allele had a significant effect on overall gluten quality, gluten strength, gluten extensibility and bread-making quality, although its effect was smaller than the effects of other quality related genes as Glu-D1, Glu-B1 or the negative effect of the 1BL.1RS translocation. The wbm allele was associated with higher values of the traits mentioned but not with higher protein content. The identification of this new wbm gene/protein is a step forward in understanding wheat quality genetic control. Implementation of marker assisted selection in breeding programs to detect the wbm allele is highly recommended.

We cloned TaSST genes, developed a gene-specific marker for TaSST - D1 , and identified three QTL in the Doumai/Shi 4185 RIL population. TaSST - D1 is within one of the three QTL. Sucrose:sucrose-1-fructosyltransferase (1-SST), a critical enzyme in the fructan biosynthetic pathway, is significantly and positively associated with water soluble carbohydrate (WSC) content in bread wheat stems. In the present study, wheat 1-SST genes (TaSST) were isolated and located on chromosomes 4A, 7A and 7D. Sequence analysis of TaSST-D1 revealed 15 single nucleotide polymorphisms (SNP) in the third exon between cultivars with higher and lower WSC content. A cleaved amplified polymorphism sequence (CAPS) marker, WSC7D, based on the polymorphism at position 1216 (C-G) was developed to discriminate the two alleles. WSC7D was located on chromosome 7DS using a recombinant inbred line (RIL) population from a Doumai/Shi 4185 cross, and a set of Chinese Spring nullisomic-tetrasomic lines. TaSST-D1 co-segregated with the CAPS marker WSC7D and was linked to SNP marker BS00108793_51 on chromosome 7DS at a genetic distance of 6.1 cM. It explained 8.8, 10.9, and 11.3 % of the phenotypic variances in trials at Beijing and Shijiazhuang as well as the averaged data from those environments, respectively. Two additional QTL (QWSC.caas-4BS and QWSC.caas-7AS) besides TaSST-D1 were mapped in the RIL population. One hundred and forty-nine Chinese wheat cultivars and advanced lines tested in four environments were used to validate a highly significant (P

International audience; Detection of senescence’s dynamics in crop breeding is time consuming and needs considerable details regarding its rate of progression and intensity. Normalized difference red-edge index (NDREI) along with four other spectral vegetative indices (SVIs) derived from unmanned aerial vehicle (UAV) based spatial imagery, were evaluated for rapid and accurate prediction of senescence. For this, 32 selected winter wheat genotypes were planted under full and limited irrigation treatments. Significant variations for all five SVIs: green normalize difference vegetation index (GNDVI), simple ratio (SR), green chlorophyll index (GCI), red-edge chlorophyll index (RECI), and normalized difference red-edge index (NDREI) among genotypes and between treatments, were observed from heading to late grain filling stages. The SVIs showed strong relationship (R2 = 0.69 to 0.78) with handheld measurements of chlorophyll and leaf area index (LAI), while negatively correlated (R2 = 0.75 to 0.77) with canopy temperature (CT) across the treatments. NDREI as a new SVI showed higher correlations with ground data under both treatments, similarly as exhibited by other four SVIs. There were medium to strong correlations (r = 0.23–0.63) among SVIs, thousand grain weight (TGW) and grain yield (GY) under both treatments. Senescence rate was calculated by decreasing values of SVIs from their peak values at heading stage, while variance for senescence rate among genotypes and between treatments could be explained by SVIs variations. Under limited irrigation, 10% to 15% higher senescence rate was detected as compared with full irrigation. Principle component analysis corroborated the negative association of high senescence rate with TGW and GY. Some genotypes, such as Beijing 0045, Nongda 5181, and Zhongmai 175, were selected with low senescence rate, stable TGW and GY in both full and limited irrigation treatments, nearly in accordance with the actual performance of these cultivars in field. Thus, SVIs derived from UAV appeared as a promising tool for rapid and precise estimation of senescence rate at maturation stages.

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.

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.