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

• Published in: Plants (Basel) Vol. 9; no. 12; p. 1695
• Main Authors: Zhao, Shuyu, Jang, Su, Lee, Yoon Kyung, Kim, Dong-Gwan, Jin, Zhengxun, Koh, Hee-Jong
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 02.12.2020; MDPI
• Subjects: Biomass; Crop yield; Cultivars; Deoxyribonucleic acid; DNA; Genes; Genetic analysis; Genome-wide association studies; genome-wide association study; Genomes; heading date; Nucleotides; Optimization; phase transition; Phase transitions; Plant breeding; Plant growth; Polymorphism; Prediction models; productive tiller number; Regression analysis; Regression models; Rice; rice tillering; Single-nucleotide polymorphism; tiller number; Transcription factors; United States > US; South Korea; China; productive tiller number; rice tillering; phase transition; heading date; genome-wide association study; tiller number
• ISSN: 2223-7747; 2223-7747
• DOI: 10.3390/plants9121695

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.