title: Deciphering starch quality of rice kernels using metabolite profiling and pedigree network analysis.
abstract: The physiological properties of rice grains are immediately obvious to consumers. High-coverage metabolomic characterization of the rice diversity research set predicted a negative correlation between fatty acid and lipid levels and amylose/total starch ratio (amylose ratio), but the reason for this is unclear. To obtain new insight into the relationships among the visual phenotypes of rice kernels, starch granule structures, amylose ratios, and metabolite changes, we investigated the metabolite changes of five Japonica cultivars with various amylose ratios and two knockout mutants (e1, a Starch synthase IIIa (SSIIIa)-deficient mutant and the SSIIIa/starch branching enzyme (BE) double-knockout mutant 4019) by using mass spectrometry-based metabolomics techniques. Scanning electron microscopy clearly showed that the two mutants had unusual starch granule structures. The metabolomic compositions of two cultivars with high amylose ratios (Hoshiyutaka and Yumetoiro) exhibited similar patterns, while that of the double-knockout mutant, which has an extremely high amylose ratio, differed. Rice pedigree network analysis of the cultivars and the mutants provided insight into the association between metabolic-trait properties and their underlying genetic basis in rice breeding in Japan. Multidimensional scaling analysis revealed that the Hoshiyutaka and Yumetoiro cultivars were Indica-like, yet they are classified as Japonica subpopulations. Exploring metabolomic traits is a powerful way to follow rice genetic traces and breeding history.
authors.affiliation: RIKEN Plant Science Center, Tsurumi, Yokohama 230-0045, Japan. mkusano005@psc.riken.jp
authors.forename: Miyako
authors.initials: M
authors.lastname: Kusano
authors.forename: Atsushi
authors.initials: A
authors.lastname: Fukushima
authors.forename: Naoko
authors.initials: N
authors.lastname: Fujita
authors.forename: Yozo
authors.initials: Y
authors.lastname: Okazaki
authors.forename: Makoto
authors.initials: M
authors.lastname: Kobayashi
authors.forename: Naoko Fujita
authors.initials: NF
authors.lastname: Oitome
authors.forename: Kaworu
authors.initials: K
authors.lastname: Ebana
authors.forename: Kazuki
authors.initials: K
authors.lastname: Saito
mesh_terms: D016000:Cluster Analysis; D056625:Endosperm / Q000378:metabolism / Q000648:ultrastructure; D008401:Gas Chromatography-Mass Spectrometry; D055786:Gene Knockout Techniques; D007564:Japan; D055442:Metabolome; D055432:Metabolomics / Q000379:methods*; D009154:Mutation / Q000235:genetics; D012275:Oryza / Q000378:metabolism* / Q000648:ultrastructure; D010375:Pedigree; D010641:Phenotype; D019655:Quantitative Trait, Heritable; D012639:Seeds / Q000378:metabolism* / Q000648:ultrastructure; D013213:Starch / Q000378:metabolism* / Q000648:ultrastructure
chemical_list: D013213:Starch