Full
Outline
INTRODUCTION Due to differences in breeding objectives, northeast japonica rice (Oryza sativa subsp. geng or japonica) is more advantageous than Japanese japonica rice in terms of yield level, whereas Japanese japonica rice is significantly better than Chinese japonica rice in terms of eating quality. Clarifying the genetic basis of the differences in eating quality between Chinese and Japanese japonica rice is highly valuable for the cultivation of high-yield and high-quality japonica rice.
RATIONALEA total of 274 Chinese and Japanese japonica rice varieties were used as research materials to quantify the eating quality of the rice and to analyze the genetic basis of the taste differences between Chinese and Japanese japonica rice by combining genome-wide association analysis with the downscaling of many parameters.
RESULTSThe results revealed that the significant differences in the taste values of Chinese and Japanese japonica rice were reflected in three textural parameters: the adhesion force (ADF), first recoverable deformation cycle (FRDC), and elasticity index (EI). Moreover, the correlation analysis between the taste values and 30 textural characters showed that 24 characters were significantly correlated with the taste value of rice. The 30 metrics of textural characterization were downscaled to four principal components that explained 80% of the phenotypic variation in the population, and the genome-wide associations of their eigenvalues were mined to two primary effector loci affecting the textural characterization of Chinese-Japanese japonica rice, qFPC4.3 and qFPC9.2.
CONCLUSION In this study, we quantified the parameters of eating quality from a qualitative perspective, and thus analyzed the genetic basis of the differences in eating quality between Chinese and Japanese rice, which provided valuable genetic information and a theoretical basis for the genetic improvement of the eating quality of japonica rice in China.
PCA analysis and genome-wide association studies based on principal component eigenvalues of texture characteristics indicators. PCA analysis was performed using 2021 data.
31
14
| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
关闭全屏
No. 86 Xueyuan South Road, Haidian District, Beijing
010-62662699(Operation and Technical Support)
qkjq@cast.org.cn
Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House
