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

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...

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Autores principales: Zhao, Shuyu, Jang, Su, Lee, Yoon Kyung, Kim, Dong-Gwan, Jin, Zhengxun, Koh, Hee-Jong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7761586/
https://www.ncbi.nlm.nih.gov/pubmed/33276582
http://dx.doi.org/10.3390/plants9121695
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author Zhao, Shuyu
Jang, Su
Lee, Yoon Kyung
Kim, Dong-Gwan
Jin, Zhengxun
Koh, Hee-Jong
author_facet Zhao, Shuyu
Jang, Su
Lee, Yoon Kyung
Kim, Dong-Gwan
Jin, Zhengxun
Koh, Hee-Jong
author_sort Zhao, Shuyu
collection PubMed
description 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, HD1 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 (R(2)) 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.
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spelling pubmed-77615862020-12-26 Genetic Basis of Tiller Dynamics of Rice Revealed by Genome-Wide Association Studies Zhao, Shuyu Jang, Su Lee, Yoon Kyung Kim, Dong-Gwan Jin, Zhengxun Koh, Hee-Jong Plants (Basel) Article 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, HD1 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 (R(2)) 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. MDPI 2020-12-02 /pmc/articles/PMC7761586/ /pubmed/33276582 http://dx.doi.org/10.3390/plants9121695 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhao, Shuyu
Jang, Su
Lee, Yoon Kyung
Kim, Dong-Gwan
Jin, Zhengxun
Koh, Hee-Jong
Genetic Basis of Tiller Dynamics of Rice Revealed by Genome-Wide Association Studies
title Genetic Basis of Tiller Dynamics of Rice Revealed by Genome-Wide Association Studies
title_full Genetic Basis of Tiller Dynamics of Rice Revealed by Genome-Wide Association Studies
title_fullStr Genetic Basis of Tiller Dynamics of Rice Revealed by Genome-Wide Association Studies
title_full_unstemmed Genetic Basis of Tiller Dynamics of Rice Revealed by Genome-Wide Association Studies
title_short Genetic Basis of Tiller Dynamics of Rice Revealed by Genome-Wide Association Studies
title_sort genetic basis of tiller dynamics of rice revealed by genome-wide association studies
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7761586/
https://www.ncbi.nlm.nih.gov/pubmed/33276582
http://dx.doi.org/10.3390/plants9121695
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