摘要
米饭谷物的生理的性质对消费者立即明显。米饭差异研究集合的高范围的 metabolomic 描述预言了在丰满的酸和类脂化合物之间的否定关联层次和直链淀粉 / 总数淀粉比率(直链淀粉比率) ，而是为这的原因是不清楚的。为了在米饭核，淀粉小粒结构，直链淀粉比率，和代谢物的视觉显型之中获得新卓见进关系，变化，我们与各种各样的直链淀粉比率和二猛烈异种调查了五装饰用的梨树栽培变种的代谢物变化( e1 ，淀粉 synthase IIIa ( SSIIIa )缺乏的异种和 SSIIIa/starch 分叉的酶()双大美人异种 4019 )由使用集体 基于spectrometry 的 metabolomics 技术。扫描电子显微镜学清楚地证明二异种有不平常的淀粉小粒结构。，有高直链淀粉比率(Hoshiyutaka 和 Yumetoiro ) 的二栽培变种的 metabolomic 作文展出了类似的模式双大美人异种，它有极其高的直链淀粉比率，不同。栽培变种和异种的瑞斯家谱网络分析在在日本繁殖的米饭提供了卓见进在新陈代谢特点的性质和他们的内在的基因基础之间的协会。多维的可伸缩分析表明 Hoshiyutaka 和 Yumetoiro 栽培变种是象 Indica 一样，然而，他们作为装饰用的梨树 subpopulations 被分类。探索 metabolomic 特点是跟随米饭的一个强大的方法基因踪迹和繁殖历史。
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 （e 1, a Starch synthase Ilia （SSIIla）-deficient mutant and the SSIIla/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.
