Genome-wide association for grain morphology in synthetic hexaploid wheats using digital imaging analysis

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