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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: 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.