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Identification and allele mining of new candidate genes underlying rice grain weight and grain shape by genome-wide association study

BACKGROUND: Grain weight and grain shape are important agronomic traits that affect the grain yield potential and grain quality of rice. Both grain weight and grain shape are controlled by multiple genes. The 3,000 Rice Genomes Project (3 K RGP) greatly facilitates the discovery of agriculturally im...

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Autores principales: Niu, Yanan, Chen, Tianxiao, Wang, Chunchao, Chen, Kai, Shen, Congcong, Chen, Huizhen, Zhu, Shuangbing, Wu, Zhichao, Zheng, Tianqing, Zhang, Fan, Xu, Jianlong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8349016/
https://www.ncbi.nlm.nih.gov/pubmed/34362301
http://dx.doi.org/10.1186/s12864-021-07901-x
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author Niu, Yanan
Chen, Tianxiao
Wang, Chunchao
Chen, Kai
Shen, Congcong
Chen, Huizhen
Zhu, Shuangbing
Wu, Zhichao
Zheng, Tianqing
Zhang, Fan
Xu, Jianlong
author_facet Niu, Yanan
Chen, Tianxiao
Wang, Chunchao
Chen, Kai
Shen, Congcong
Chen, Huizhen
Zhu, Shuangbing
Wu, Zhichao
Zheng, Tianqing
Zhang, Fan
Xu, Jianlong
author_sort Niu, Yanan
collection PubMed
description BACKGROUND: Grain weight and grain shape are important agronomic traits that affect the grain yield potential and grain quality of rice. Both grain weight and grain shape are controlled by multiple genes. The 3,000 Rice Genomes Project (3 K RGP) greatly facilitates the discovery of agriculturally important genetic variants and germplasm resources for grain weight and grain shape. RESULTS: Abundant natural variations and distinct phenotic differentiation among the subgroups in grain weight and grain shape were observed in a large population of 2,453 accessions from the 3 K RGP. A total of 21 stable quantitative trait nucleotides (QTNs) for the four traits were consistently identified in at least two of 3-year trials by genome-wide association study (GWAS), including six new QTNs (qTGW3.1, qTGW9, qTGW11, qGL4/qRLW4, qGL10, and qRLW1) for grain weight and grain shape. We further predicted seven candidate genes (Os03g0186600, Os09g0544400, Os11g0163600, Os04g0580700, Os10g0399700, Os10g0400100 and Os01g0171000) for the six new QTNs by high-density association and gene-based haplotype analyses. The favorable haplotypes of the seven candidate genes and five previously cloned genes in elite accessions with high TGW and RLW are also provided. CONCLUSIONS: Our results deepen the understanding of the genetic basis of grain weight and grain shape in rice and provide valuable information for improving rice grain yield and grain quality through molecular breeding. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-021-07901-x.
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spelling pubmed-83490162021-08-09 Identification and allele mining of new candidate genes underlying rice grain weight and grain shape by genome-wide association study Niu, Yanan Chen, Tianxiao Wang, Chunchao Chen, Kai Shen, Congcong Chen, Huizhen Zhu, Shuangbing Wu, Zhichao Zheng, Tianqing Zhang, Fan Xu, Jianlong BMC Genomics Research Article BACKGROUND: Grain weight and grain shape are important agronomic traits that affect the grain yield potential and grain quality of rice. Both grain weight and grain shape are controlled by multiple genes. The 3,000 Rice Genomes Project (3 K RGP) greatly facilitates the discovery of agriculturally important genetic variants and germplasm resources for grain weight and grain shape. RESULTS: Abundant natural variations and distinct phenotic differentiation among the subgroups in grain weight and grain shape were observed in a large population of 2,453 accessions from the 3 K RGP. A total of 21 stable quantitative trait nucleotides (QTNs) for the four traits were consistently identified in at least two of 3-year trials by genome-wide association study (GWAS), including six new QTNs (qTGW3.1, qTGW9, qTGW11, qGL4/qRLW4, qGL10, and qRLW1) for grain weight and grain shape. We further predicted seven candidate genes (Os03g0186600, Os09g0544400, Os11g0163600, Os04g0580700, Os10g0399700, Os10g0400100 and Os01g0171000) for the six new QTNs by high-density association and gene-based haplotype analyses. The favorable haplotypes of the seven candidate genes and five previously cloned genes in elite accessions with high TGW and RLW are also provided. CONCLUSIONS: Our results deepen the understanding of the genetic basis of grain weight and grain shape in rice and provide valuable information for improving rice grain yield and grain quality through molecular breeding. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-021-07901-x. BioMed Central 2021-08-06 /pmc/articles/PMC8349016/ /pubmed/34362301 http://dx.doi.org/10.1186/s12864-021-07901-x Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Niu, Yanan
Chen, Tianxiao
Wang, Chunchao
Chen, Kai
Shen, Congcong
Chen, Huizhen
Zhu, Shuangbing
Wu, Zhichao
Zheng, Tianqing
Zhang, Fan
Xu, Jianlong
Identification and allele mining of new candidate genes underlying rice grain weight and grain shape by genome-wide association study
title Identification and allele mining of new candidate genes underlying rice grain weight and grain shape by genome-wide association study
title_full Identification and allele mining of new candidate genes underlying rice grain weight and grain shape by genome-wide association study
title_fullStr Identification and allele mining of new candidate genes underlying rice grain weight and grain shape by genome-wide association study
title_full_unstemmed Identification and allele mining of new candidate genes underlying rice grain weight and grain shape by genome-wide association study
title_short Identification and allele mining of new candidate genes underlying rice grain weight and grain shape by genome-wide association study
title_sort identification and allele mining of new candidate genes underlying rice grain weight and grain shape by genome-wide association study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8349016/
https://www.ncbi.nlm.nih.gov/pubmed/34362301
http://dx.doi.org/10.1186/s12864-021-07901-x
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