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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. [ABSTRACT FROM AUTHOR]

Background: Black point is a serious threat to wheat production and can be managed by host resistance. Marker-assisted selection (MAS) has the potential to accelerate genetic improvement of black point resistance in wheat breeding. We performed a genome-wide association study (GWAS) using the high-density wheat 90 K and 660 K single nucleotide polymorphism (SNP) assays to better understand the genetic basis of black point resistance and identify associated molecular markers. Results: Black point reactions were evaluated in 166 elite wheat cultivars in five environments. Twenty-five unique loci were identified on chromosomes 2A, 2B, 3A, 3B (2), 3D, 4B (2), 5A (3), 5B (3), 6A, 6B, 6D, 7A (5), 7B and 7D (2), respectively, explaining phenotypic variation ranging from 7.9 to 18.0%. The highest number of loci was detected in the A genome (11), followed by the B (10) and D (4) genomes. Among these, 13 were identified in two or more environments. Seven loci coincided with known genes or quantitative trait locus (QTL), whereas the other 18 were potentially novel loci. Linear regression showed a clear dependence of black point scores on the number of favorable alleles, suggesting that QTL pyramiding will be an effective approach to increase resistance. In silico analysis of sequences of resistance-associated SNPs identified 6 genes possibly involved in oxidase, signal transduction and stress resistance as candidate genes involved in black point reaction. Conclusion: SNP markers significantly associated with black point resistance and accessions with a larger number of resistance alleles can be used to further enhance black point resistance in breeding. This study provides new insights into the genetic architecture of black point reaction. [ABSTRACT FROM AUTHOR]

Background: Phytoene synthase 1 (PSY1) is the most important regulatory enzyme in carotenoid biosynthesis, whereas its function is hardly known in common wheat. The aims of the present study were to investigate Psy1 function and genetic regulation using reverse genetics approaches. Results: Transcript levels of Psy1 in RNAi transgenic lines were decreased by 54-76 % and yellow pigment content (YPC) was reduced by 26-35 % compared with controls, confirming the impact of Psy1 on carotenoid accumulation. A series of candidate genes involved in secondary metabolic pathways and core metabolic processes responded to Psy1 down-regulation. The aspartate rich domain (DXXXD) was important for PSY1 function, and conserved nucleotides adjacent to the domain influenced YPC by regulating gene expression, enzyme activity or alternative splicing. Compensatory responses analysis indicated that three Psy1 homoeologs may be coordinately regulated under normal conditions, but separately regulated under stress. The period 14 days post anthesis (DPA) was found to be a key regulation node during grain development. Conclusion: The findings define key aspects of flour color regulation in wheat and facilitate the genetic improvement of wheat quality targeting color/nutritional specifications required for specific end products. [ABSTRACT FROM AUTHOR]

Background Grain size and shape greatly influence grain weight which ultimately enhances grain yield in wheat. Digital imaging (DI) based phenomic characterization can capture the three dimensional variation in grain size and shape than has hitherto been possible. In this study, we report the results from using digital imaging of grain size and shape to understand the relationship among different components of this trait, their contribution to enhance grain weight, and to identify genomic regions (QTLs) controlling grain morphology using genome wide association mapping with high density diversity array technology (DArT) and allele-specific markers. Results Significant positive correlations were observed between grain weight and grain size measurements such as grain length (r = 0.43), width, thickness (r = 0.64) and factor from density (FFD) (r = 0.69). A total of 231 synthetic hexaploid wheats (SHWs) were grouped into five different sub-clusters by Bayesian structure analysis using unlinked DArT markers. Linkage disequilibrium (LD) decay was observed among DArT loci > 10 cM distance and approximately 28% marker pairs were in significant LD. In total, 197 loci over 60 chromosomal regions and 79 loci over 31 chromosomal regions were associated with grain morphology by genome wide analysis using general linear model (GLM) and mixed linear model (MLM) approaches, respectively. They were mainly distributed on homoeologous group 2, 3, 6 and 7 chromosomes. Twenty eight marker-trait associations (MTAs) on the D genome chromosomes 2D, 3D and 6D may carry novel alleles with potential to enhance grain weight due to the use of untapped wild accessions of Aegilops tauschii. Statistical simulations showed that favorable alleles for thousand kernel weight (TKW), grain length, width and thickness have additive genetic effects. Allelic variations for known genes controlling grain size and weight, viz. TaCwi-2A, TaSus-2B, TaCKX6-3D and TaGw2-6A, were also associated with TKW, grain width and thickness. In silico functional analysis predicted a range of biological functions for 32 DArT loci and receptor like kinase, known to affect plant development, appeared to be common protein family encoded by several loci responsible for grain size and shape. Conclusion Conclusively, we demonstrated the application and integration of multiple approaches including high throughput phenotyping using DI, genome wide association studies (GWAS) and in silico functional analysis of candidate loci to analyze target traits, and identify candidate genomic regions underlying these traits. These approaches provided great opportunity to understand the breeding value of SHWs for improving grain weight and enhanced our deep understanding on molecular genetics of grain weight in wheat. [ABSTRACT FROM AUTHOR]

Background: Low-molecular-weight glutenin subunits (LMW-GS) strongly influence the bread-making quality of bread wheat. These proteins are encoded by a multi-gene family located at the Glu-A3, Glu-B3 and Glu-D3 loci on the short arms of homoeologous group 1 chromosomes, and show high allelic variation. To characterize the genetic and protein compositions of LMW-GS alleles, we investigated 16 Aroona near-isogenic lines (NILs) using SDS-PAGE, 2D-PAGE and the LMW-GS gene marker system. Moreover, the composition of glutenin macro-polymers, dough properties and pan bread quality parameters were determined for functional analysis of LMW-GS alleles in the NILs. Results: Using the LMW-GS gene marker system, 14-20 LMW-GS genes were identified in individual NILs. At the Glu-A3 locus, two m-type and 2-4 i-type genes were identified and their allelic variants showed high polymorphisms in length and nucleotide sequences. The Glu-A3d allele possessed three active genes, the highest number among Glu-A3 alleles. At the Glu-B3 locus, 2-3 m-type and 1-3 s-type genes were identified from individual NILs. Based on the different compositions of s-type genes, Glu-B3 alleles were divided into two groups, one containing Glu-B3a, B3b, B3f and B3g, and the other comprising Glu-B3c, B3d, B3h and B3i. Eight conserved genes were identified among Glu-D3 alleles, except for Glu-D3f. The protein products of the unique active genes in each NIL were detected using protein electrophoresis. Among Glu-3 alleles, the Glu-A3e genotype without i-type LMW-GS performed worst in almost all quality properties. Glu-B3b, B3g and B3i showed better quality parameters than the other Glu-B3 alleles, whereas the Glu-B3c allele containing s-type genes with low expression levels had an inferior effect on bread-making quality. Due to the conserved genes at Glu-D3 locus, Glu-D3 alleles showed no significant differences in effects on all quality parameters. Conclusions: This work provided new insights into the composition and function of 18 LMW-GS alleles in bread wheat. The variation of i-type genes mainly contributed to the high diversity of Glu-A3 alleles, and the differences among Glu-B3 alleles were mainly derived from the high polymorphism of s-type genes. Among LMW-GS alleles, Glu-A3e and Glu-B3c represented inferior alleles for bread-making quality, whereas Glu-A3d, Glu-B3b, Glu-B3g and Glu-B3i were correlated with superior bread-making quality. Glu-D3 alleles played minor roles in determining quality variation in bread wheat. Thus, LMW-GS alleles not only affect dough extensibility but greatly contribute to the dough resistance, glutenin macro-polymers and bread quality. [ABSTRACT FROM AUTHOR]

Background: Low-molecular-weight glutenin subunits (LMW-GS) play a crucial role in determining end-use quality of common wheat by influencing the viscoelastic properties of dough. Four different methods - sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE), two-dimensional gel electrophoresis (2-DE, IEF × SDS-PAGE), matrixassisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) and polymerase chain reaction (PCR), were used to characterize the LMW-GS composition in 103 cultivars from 12 countries. Results: At the Glu-A3 locus, all seven alleles could be reliably identified by 2-DE and PCR. However, the alleles Glu-A3e and Glu-A3d could not be routinely distinguished from Glu-A3f and Glu-A3g, respectively, based on SDS-PAGE, and the allele Glu-A3a could not be differentiated from Glu-A3c by MALDI-TOF-MS. At the Glu-B3 locus, alleles Glu-B3a, Glu-B3b, Glu-B3c, Glu-B3g, Glu-B3h and Glu-B3j could be clearly identified by all four methods, whereas Glu-B3ab, Glu-B3ac, Glu- B3ad could only be identified by the 2-DE method. At the Glu-D3 locus, allelic identification was problematic for the electrophoresis based methods and PCR. MALDI-TOF-MS has the potential to reliably identify the Glu-D3 alleles. Conclusions: PCR is the simplest, most accurate, lowest cost, and therefore recommended method for identification of Glu-A3 and Glu-B3 alleles in breeding programs. A combination of methods was required to identify certain alleles, and would be especially useful when characterizing new alleles. A standard set of 30 cultivars for use in future studies was chosen to represent all LMW-GS allelic variants in the collection. Among them, Chinese Spring, Opata 85, Seri 82 and Pavon 76 were recommended as a core set for use in SDS-PAGE gels. Glu-D3c and Glu-D3e are the same allele. Two new alleles, namely, Glu-D3m in cultivar Darius, and Glu-D3n in Fengmai 27, were identified by 2-DE. Utilization of the suggested standard cultivar set, seed of which is available from the CIMMYT and INRA Clermont-Ferrand germplasm collections, should also promote information sharing in the identification of individual LMW-GS and thus provide useful information for quality improvement in common wheat. [ABSTRACT FROM AUTHOR]