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Comparative mapping of chalkiness components in rice using five populations across two environments

BACKGROUND: Chalkiness is a major constraint in rice production because it is one of the key factors determining grain quality (appearance, processing, milling, storing, eating, and cooking quality) and price. Its reduction is a major goal, and the primary purpose of this study was to dissect the ge...

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Autores principales: Peng, Bo, Wang, Lingqiang, Fan, Chuchuan, Jiang, Gonghao, Luo, Lijun, Li, Yibo, He, Yuqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4021085/
https://www.ncbi.nlm.nih.gov/pubmed/24766995
http://dx.doi.org/10.1186/1471-2156-15-49
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author Peng, Bo
Wang, Lingqiang
Fan, Chuchuan
Jiang, Gonghao
Luo, Lijun
Li, Yibo
He, Yuqing
author_facet Peng, Bo
Wang, Lingqiang
Fan, Chuchuan
Jiang, Gonghao
Luo, Lijun
Li, Yibo
He, Yuqing
author_sort Peng, Bo
collection PubMed
description BACKGROUND: Chalkiness is a major constraint in rice production because it is one of the key factors determining grain quality (appearance, processing, milling, storing, eating, and cooking quality) and price. Its reduction is a major goal, and the primary purpose of this study was to dissect the genetic basis of grain chalkiness. Using five populations across two environments, we also sought to determine how many quantitative trait loci (QTL) can be consistently detected. We obtained an integrated genetic map using the data from five mapping populations and further confirmed the reliability of the identified QTL. RESULTS: A total of 79 QTL associated with six chalkiness traits (chalkiness rate, white core rate, white belly rate, chalkiness area, white core area, and white belly area) were mapped on 12 chromosomes using five populations (two doubled haploid lines and three recombinant inbred lines) across two environments (Hainan in 2004 and Wuhan in 2004). The final integrated map included 430 markers; 58.3% of the QTL clustered together (QTL clusters), 71.4% of the QTL clusters were identified in two or more populations, and 36.1% of the QTL were consistently detected in the two environments. The QTL could be detected again and showed dominance (qWBR1, qWBR8, qWBR12, and qCR5) or overdominance effects (qWCR7) for the rate of the white belly or white core, respectively, and all four QTL clusters derived from Zhenshan 97 controlling white belly rate were stably and reliably identified in an F(2) population. CONCLUSIONS: Our results identified 79 QTL associated with six chalkiness traits using five populations across two environments and yielded an integrated genetic map, indicating most of the QTL clustered together and could be detected in different backgrounds. The identified QTL were stable and reliable in the F(2) population, and they may facilitate our understanding of the QTL related to chalkiness traits in different populations and various environments, the relationships among the various chalkiness QTL, and the genetic basis for chalkiness. Thus, our results may be immediately used for map-based cloning of important QTL and in marker-assisted breeding to improve grain quality in rice breeding.
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spelling pubmed-40210852014-05-16 Comparative mapping of chalkiness components in rice using five populations across two environments Peng, Bo Wang, Lingqiang Fan, Chuchuan Jiang, Gonghao Luo, Lijun Li, Yibo He, Yuqing BMC Genet Research Article BACKGROUND: Chalkiness is a major constraint in rice production because it is one of the key factors determining grain quality (appearance, processing, milling, storing, eating, and cooking quality) and price. Its reduction is a major goal, and the primary purpose of this study was to dissect the genetic basis of grain chalkiness. Using five populations across two environments, we also sought to determine how many quantitative trait loci (QTL) can be consistently detected. We obtained an integrated genetic map using the data from five mapping populations and further confirmed the reliability of the identified QTL. RESULTS: A total of 79 QTL associated with six chalkiness traits (chalkiness rate, white core rate, white belly rate, chalkiness area, white core area, and white belly area) were mapped on 12 chromosomes using five populations (two doubled haploid lines and three recombinant inbred lines) across two environments (Hainan in 2004 and Wuhan in 2004). The final integrated map included 430 markers; 58.3% of the QTL clustered together (QTL clusters), 71.4% of the QTL clusters were identified in two or more populations, and 36.1% of the QTL were consistently detected in the two environments. The QTL could be detected again and showed dominance (qWBR1, qWBR8, qWBR12, and qCR5) or overdominance effects (qWCR7) for the rate of the white belly or white core, respectively, and all four QTL clusters derived from Zhenshan 97 controlling white belly rate were stably and reliably identified in an F(2) population. CONCLUSIONS: Our results identified 79 QTL associated with six chalkiness traits using five populations across two environments and yielded an integrated genetic map, indicating most of the QTL clustered together and could be detected in different backgrounds. The identified QTL were stable and reliable in the F(2) population, and they may facilitate our understanding of the QTL related to chalkiness traits in different populations and various environments, the relationships among the various chalkiness QTL, and the genetic basis for chalkiness. Thus, our results may be immediately used for map-based cloning of important QTL and in marker-assisted breeding to improve grain quality in rice breeding. BioMed Central 2014-04-26 /pmc/articles/PMC4021085/ /pubmed/24766995 http://dx.doi.org/10.1186/1471-2156-15-49 Text en Copyright © 2014 Peng et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Peng, Bo
Wang, Lingqiang
Fan, Chuchuan
Jiang, Gonghao
Luo, Lijun
Li, Yibo
He, Yuqing
Comparative mapping of chalkiness components in rice using five populations across two environments
title Comparative mapping of chalkiness components in rice using five populations across two environments
title_full Comparative mapping of chalkiness components in rice using five populations across two environments
title_fullStr Comparative mapping of chalkiness components in rice using five populations across two environments
title_full_unstemmed Comparative mapping of chalkiness components in rice using five populations across two environments
title_short Comparative mapping of chalkiness components in rice using five populations across two environments
title_sort comparative mapping of chalkiness components in rice using five populations across two environments
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4021085/
https://www.ncbi.nlm.nih.gov/pubmed/24766995
http://dx.doi.org/10.1186/1471-2156-15-49
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