Evaluating Multiple Allelic Combination to Determine Tiller Angle Variation in Rice

Su Jang, Yoo Seok Kang, Yoon Kyung Lee and Hee-Jong Koh
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Su Jang: Plant Genomics and Breeding Institute, Seoul National University, Seoul 08826, Korea
Yoo Seok Kang: Plant Genomics and Breeding Institute, Seoul National University, Seoul 08826, Korea
Yoon Kyung Lee: Plant Genomics and Breeding Institute, Seoul National University, Seoul 08826, Korea
Hee-Jong Koh: Plant Genomics and Breeding Institute, Seoul National University, Seoul 08826, Korea

Agriculture, 2020, vol. 10, issue 10, 1-8

Abstract: Tiller angle is an important influencing factor in rice plant architecture that affects planting density and yield per unit area. Molecular tools to predict tiller angle contribute to breeding programs, which aim at optimizing rice plant architecture. In this study, several single-nucleotide polymorphism (SNP) markers related to tiller angle were developed and used with a model population to define a linear regression model for the prediction of tiller angle in rice. The resulting linear regression model, consisting of eight SNP markers as independent variables, was assessed using an independent test population. Overall, the regression model achieved an adjusted R 2 of 0.51 and exhibited consistent predictive accuracy with an R 2 of 0.61. Three of the eight independent variables, namely, PIN2-1, LIC1-1, and TAC1, contributed substantially to the linear regression model. These three major effect markers were also major determinants of tiller angle in the independent test population. Allelic combinations of the three major effect markers modulated tiller angle in the range of 5.6–19°. The DNA markers and linear regression model developed in this study will facilitate rice breeding programs for improving plant architecture.

Keywords: rice; tiller angle; plant architecture; DNA marker; multiple linear regression model; marker-assisted breeding (MAB) (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2020
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