Weedy rice has been becoming a notorious weed in the paddy field of China in recent decades due to its increasing damage to rice yield and rice quality. In this study, a microsatellite technique with 21 pairs of SSR markers was utilized to estimate the genetic structure of two biotypes of weedy rice with Japonica and Indica rice characteristics, collected from Liaoning and Guangdong provinces, respectively. The genetic diversity of the weedy rice in the two provinces was relatively low (Liaoning h = 0.086; Guangdong h = 0.160), and distinctly large genetic differences existed between these two provinces (Gcs = 0.623). The genetic diversity was found primarily within populations, and genetic differentiation was relatively low within the same province. Both cluster analysis (UPGMA) and principle component analysis (PCA) showed that weedy rice had a closer relationship with the cultivated rice collected from the sample field than with other cultivated rice and common wild rice varieties in China. Thus, the results of this study on samples from the Liaoning and Guangdong provinces in China support the de-domestication hypothesis that weedy rice most probably originated from local cultivated rice.
From this study, it is concluded that the likelihood of gene flow between transgenic rice and weedy rice biotypes is primarily determined by floral synchronisation and secondarily influenced by genetic compatibility and some morphological characteristics.
In traditional Chinese medicine (TCM) studies, it is difficult to choose evaluation markers for the strict quality control of herbs. A high performance liquid chromatography coupled with metabolomics for simultaneous quantitative analysis of quality markers (Q-markers) in Glycyrrhiza uralensis Fisch was established, which could not only ensure the quality and batch-to-batch consistency of TCMs, but also achieve a quantitative analysis of multi-components by the single reference standard. Based on the construction of chromatographic profiles by high performance liquid chromatography (HPLC) and HPLC-Q-Exactive/MS methods, different multivariate analyses were employed. Seven quantitative indices were selected as the Q-markers, and a reliable quantification method was established. The quantitative method was acceptable with good linearity with correlation coefficients >0.9993 and satisfactory repeatability (relative standard deviation (RSD) < 0.05%), precision (RSD < 0.24%), reproducibility (RSD < 0.97%), stability (RSD < 2.52%) and recoveries (96.96%—98.52%, RSD < 3.24%), and no significant differences were observed between the external standard method and the new method as determined by calculating standard method difference. Overall, the study suggests that the simultaneous quantitative analysis of main Q-marker in G. uralensis Fisch with one single marker can be considered good quality criteria for performing quality control of G. uralensis Fisch.
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