Evaluating Multiple Allelic Combination to Determine Tiller Angle Variation in Rice
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 polymor...
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doaj-ffa016aa10d24df7b4c522b4d5f622022021-04-02T12:31:18ZengMDPI AGAgriculture2077-04722020-09-011042842810.3390/agriculture10100428Evaluating Multiple Allelic Combination to Determine Tiller Angle Variation in RiceSu Jang0Yoo Seok Kang1Yoon Kyung Lee2Hee-Jong Koh3Plant Genomics and Breeding Institute, Seoul National University, Seoul 08826, KoreaPlant Genomics and Breeding Institute, Seoul National University, Seoul 08826, KoreaPlant Genomics and Breeding Institute, Seoul National University, Seoul 08826, KoreaPlant Genomics and Breeding Institute, Seoul National University, Seoul 08826, KoreaTiller 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 <i>R<sup>2</sup></i> of 0.51 and exhibited consistent predictive accuracy with an <i>R<sup>2</sup></i> 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.https://www.mdpi.com/2077-0472/10/10/428ricetiller angleplant architectureDNA markermultiple linear regression modelmarker-assisted breeding (MAB) |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Su Jang Yoo Seok Kang Yoon Kyung Lee Hee-Jong Koh |
spellingShingle |
Su Jang Yoo Seok Kang Yoon Kyung Lee Hee-Jong Koh Evaluating Multiple Allelic Combination to Determine Tiller Angle Variation in Rice Agriculture rice tiller angle plant architecture DNA marker multiple linear regression model marker-assisted breeding (MAB) |
author_facet |
Su Jang Yoo Seok Kang Yoon Kyung Lee Hee-Jong Koh |
author_sort |
Su Jang |
title |
Evaluating Multiple Allelic Combination to Determine Tiller Angle Variation in Rice |
title_short |
Evaluating Multiple Allelic Combination to Determine Tiller Angle Variation in Rice |
title_full |
Evaluating Multiple Allelic Combination to Determine Tiller Angle Variation in Rice |
title_fullStr |
Evaluating Multiple Allelic Combination to Determine Tiller Angle Variation in Rice |
title_full_unstemmed |
Evaluating Multiple Allelic Combination to Determine Tiller Angle Variation in Rice |
title_sort |
evaluating multiple allelic combination to determine tiller angle variation in rice |
publisher |
MDPI AG |
series |
Agriculture |
issn |
2077-0472 |
publishDate |
2020-09-01 |
description |
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 <i>R<sup>2</sup></i> of 0.51 and exhibited consistent predictive accuracy with an <i>R<sup>2</sup></i> 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. |
topic |
rice tiller angle plant architecture DNA marker multiple linear regression model marker-assisted breeding (MAB) |
url |
https://www.mdpi.com/2077-0472/10/10/428 |
work_keys_str_mv |
AT sujang evaluatingmultiplealleliccombinationtodeterminetilleranglevariationinrice AT yooseokkang evaluatingmultiplealleliccombinationtodeterminetilleranglevariationinrice AT yoonkyunglee evaluatingmultiplealleliccombinationtodeterminetilleranglevariationinrice AT heejongkoh evaluatingmultiplealleliccombinationtodeterminetilleranglevariationinrice |
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1721568676636786688 |