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全基因组关联研究揭示水稻分蘖动态的遗传基础

Genetic Basis of Tiller Dynamics of Rice Revealed by Genome-Wide Association Studies.

作者信息

Zhao Shuyu, Jang Su, Lee Yoon Kyung, Kim Dong-Gwan, Jin Zhengxun, Koh Hee-Jong

机构信息

Department of Plant Science, Plant Genomics and Breeding Institute, Research Institute for Agriculture and Life Sciences, Seoul National University, Seoul 08826, Korea.

Department of Agronomy, College of Agriculture, Northeast Agricultural University, Harbin 150030, China.

出版信息

Plants (Basel). 2020 Dec 2;9(12):1695. doi: 10.3390/plants9121695.

Abstract

A tiller number is the key determinant of rice plant architecture and panicle number and consequently controls grain yield. Thus, it is necessary to optimize the tiller number to achieve the maximum yield in rice. However, comprehensive analyses of the genetic basis of the tiller number, considering the development stage, tiller type, and related traits, are lacking. In this study, we sequence 219 Korean rice accessions and construct a high-quality single nucleotide polymorphism (SNP) dataset. We also evaluate the tiller number at different development stages and heading traits involved in phase transitions. By genome-wide association studies (GWASs), we detected 20 significant association signals for all traits. Five signals were detected in genomic regions near known candidate genes. Most of the candidate genes were involved in the phase transition from vegetative to reproductive growth. In particular, was simultaneously associated with the productive tiller ratio and heading date, indicating that the photoperiodic heading gene directly controls the productive tiller ratio. Multiple linear regression models of lead SNPs showed coefficients of determination () of 0.49, 0.22, and 0.41 for the tiller number at the maximum tillering stage, productive tiller number, and productive tiller ratio, respectively. Furthermore, the model was validated using independent japonica rice collections, implying that the lead SNPs included in the linear regression model were generally applicable to the tiller number prediction. We revealed the genetic basis of the tiller number in rice plants during growth, By GWASs, and formulated a prediction model by linear regression. Our results improve our understanding of tillering in rice plants and provide a basis for breeding high-yield rice varieties with the optimum the tiller number.

摘要

分蘖数是水稻株型和穗数的关键决定因素,进而控制着谷物产量。因此,有必要优化分蘖数以实现水稻的最高产量。然而,目前缺乏对分蘖数遗传基础的综合分析,未考虑发育阶段、分蘖类型及相关性状。在本研究中,我们对219份韩国水稻种质进行了测序,并构建了一个高质量的单核苷酸多态性(SNP)数据集。我们还评估了不同发育阶段的分蘖数以及参与阶段转变的抽穗性状。通过全基因组关联研究(GWAS),我们检测到了所有性状的20个显著关联信号。在已知候选基因附近的基因组区域检测到了5个信号。大多数候选基因参与了从营养生长到生殖生长的阶段转变。特别是, 与有效分蘖率和抽穗期同时相关,表明光周期抽穗基因直接控制有效分蘖率。领先SNP的多元线性回归模型显示,最大分蘖期的分蘖数、有效分蘖数和有效分蘖率的决定系数( )分别为0.49、0.22和0.41。此外,该模型使用独立的粳稻品种进行了验证,这意味着线性回归模型中包含的领先SNP通常适用于分蘖数预测。我们通过GWAS揭示了水稻植株生长过程中分蘖数的遗传基础,并通过线性回归建立了预测模型。我们的结果增进了我们对水稻分蘖的理解,并为培育具有最佳分蘖数的高产水稻品种提供了依据。

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