Influence of Multi-Gene Allele Combinations on Grain Size of Rice and Development of a Regression Equation Model to Predict Grain Parameters.
Influence of Multi-Gene Allele Combinations on Grain Size of Rice and Development of a Regression Equation Model to Predict Grain Parameters.
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DOI：
10.1186/s12284-015-0066-1
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发表时间：
2015-12
期刊：
影响因子：
--
通讯作者：
Koh HJ
中科院分区：
文献类型：
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作者：
Lee CM;Park J;Kim B;Seo J;Lee G;Jang S;Koh HJ
粒度是决定水稻产量和品质的关键因素之一。大量基因参与晶粒长度和晶宽等晶粒尺寸参数的调控。这些基因的不同等位基因对其控制下的粒级性状有不同的影响。然而，不同基因的多个等位基因对籽粒大小的综合影响仍有待研究。本研究研究了已知影响晶粒大小的 6 个关键基因：GS3、GS5、GS6、GW2、qSW5/GW5 和 GW8/OsSPL16。等位基因和谷物测量数据被用来开发回归方程模型，该模型可用于具有所需谷物特性的水稻的分子育种。本研究共使用了 215 个不同的水稻种质，它们源自或在 28 个水稻消费国开发。基因分型分析表明，在不同群体中保留了相对少量的等位基因组合，并且这些等位基因组合与谷物大小的差异显着相关。此外，在一些情况下，即使其他基因的等位基因保持不变，单个基因的变异也足以影响籽粒大小。这些数据被用来建立一个回归方程模型来预测水稻颗粒大小，并使用来自另外 34 个种质的数据进行了测试。该模型与本研究中检查的四个粒度相关性状中的三个显着相关。水稻籽粒大小受到六个不同基因等位基因特定组合的强烈影响。根据等位基因和谷物测量数据开发的回归方程模型可用于水稻育种计划，以开发具有所需谷物大小和形状的新水稻品种。本文的在线版本 (doi:10.1186/s12284-015-0066-1) 包含补充材料，可供授权用户使用。
Grain size is one of the key factors determining yield and quality in rice. A large number of genes are involved in the regulation of grain size parameters such as grain length and grain width. Different alleles of these genes have different impacts on the grain size traits under their control. However, the combined influence of multiple alleles of different genes on grain size remains to be investigated. Six key genes known to influence grain size were investigated in this study: GS3, GS5, GS6, GW2, qSW5/GW5, and GW8/OsSPL16. Allele and grain measurement data were used to develop a regression equation model that can be used for molecular breeding of rice with desired grain characteristics. A total of 215 diverse rice germplasms, which originated from or were developed in 28 rice-consuming countries, were used in this study. Genotyping analysis demonstrated that a relatively small number of allele combinations were preserved in the diverse population and that these allele combinations were significantly associated with differences in grain size. Furthermore, in several cases, variation at a single gene was sufficient to influence grain size, even when the alleles of other genes remained constant. The data were used to develop a regression equation model for prediction of rice grain size, and this was tested using data from a further 34 germplasms. The model was significantly correlated with three of the four grain size-related traits examined in this study. Rice grain size is strongly influenced by specific combinations of alleles from six different genes. A regression equation model developed from allele and grain measurement data can be used in rice breeding programs for the development of new rice varieties with desired grain size and shape. The online version of this article (doi:10.1186/s12284-015-0066-1) contains supplementary material, which is available to authorized users.