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Identification of QTL Associated with Nitrogen Uptake and Nitrogen Use Efficiency Using High Throughput Genotyped CSSLs in Rice (Oryza sativa L.)

Nitrogen (N) availability is a major factor limiting crop growth and development. Identification of quantitative trait loci (QTL) for N uptake (NUP) and N use efficiency (NUE) can provide useful information regarding the genetic basis of these traits and their associated effects on yield production....

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Autores principales: Zhou, Yong, Tao, Yajun, Tang, Dongnan, Wang, Jun, Zhong, Jun, Wang, Yi, Yuan, Qiumei, Yu, Xiaofeng, Zhang, Yan, Wang, Yulong, Liang, Guohua, Dong, Guichun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5504168/
https://www.ncbi.nlm.nih.gov/pubmed/28744289
http://dx.doi.org/10.3389/fpls.2017.01166
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author Zhou, Yong
Tao, Yajun
Tang, Dongnan
Wang, Jun
Zhong, Jun
Wang, Yi
Yuan, Qiumei
Yu, Xiaofeng
Zhang, Yan
Wang, Yulong
Liang, Guohua
Dong, Guichun
author_facet Zhou, Yong
Tao, Yajun
Tang, Dongnan
Wang, Jun
Zhong, Jun
Wang, Yi
Yuan, Qiumei
Yu, Xiaofeng
Zhang, Yan
Wang, Yulong
Liang, Guohua
Dong, Guichun
author_sort Zhou, Yong
collection PubMed
description Nitrogen (N) availability is a major factor limiting crop growth and development. Identification of quantitative trait loci (QTL) for N uptake (NUP) and N use efficiency (NUE) can provide useful information regarding the genetic basis of these traits and their associated effects on yield production. In this study, a set of high throughput genotyped chromosome segment substitution lines (CSSLs) derived from a cross between recipient 9311 and donor Nipponbare were used to identify QTL for rice NUP and NUE. Using high throughput sequencing, each CSSL were genotyped and an ultra-high-quality physical map was constructed. A total of 13 QTL, seven for NUP and six for NUE, were identified in plants under hydroponic culture with all nutrients supplied in sufficient quantities. The proportion of phenotypic variation explained by these QTL for NUP and NUE ranged from 3.16–13.99% and 3.76–12.34%, respectively. We also identified several QTL for biomass yield (BY) and grain yield (GY), which were responsible for 3.21–45.54% and 6.28–7.31%, respectively, of observed phenotypic variation. GY were significantly positively correlated with NUP and NUE, with NUP more closely correlated than NUE. Our results contribute information to NUP and NUE improvement in rice.
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spelling pubmed-55041682017-07-25 Identification of QTL Associated with Nitrogen Uptake and Nitrogen Use Efficiency Using High Throughput Genotyped CSSLs in Rice (Oryza sativa L.) Zhou, Yong Tao, Yajun Tang, Dongnan Wang, Jun Zhong, Jun Wang, Yi Yuan, Qiumei Yu, Xiaofeng Zhang, Yan Wang, Yulong Liang, Guohua Dong, Guichun Front Plant Sci Plant Science Nitrogen (N) availability is a major factor limiting crop growth and development. Identification of quantitative trait loci (QTL) for N uptake (NUP) and N use efficiency (NUE) can provide useful information regarding the genetic basis of these traits and their associated effects on yield production. In this study, a set of high throughput genotyped chromosome segment substitution lines (CSSLs) derived from a cross between recipient 9311 and donor Nipponbare were used to identify QTL for rice NUP and NUE. Using high throughput sequencing, each CSSL were genotyped and an ultra-high-quality physical map was constructed. A total of 13 QTL, seven for NUP and six for NUE, were identified in plants under hydroponic culture with all nutrients supplied in sufficient quantities. The proportion of phenotypic variation explained by these QTL for NUP and NUE ranged from 3.16–13.99% and 3.76–12.34%, respectively. We also identified several QTL for biomass yield (BY) and grain yield (GY), which were responsible for 3.21–45.54% and 6.28–7.31%, respectively, of observed phenotypic variation. GY were significantly positively correlated with NUP and NUE, with NUP more closely correlated than NUE. Our results contribute information to NUP and NUE improvement in rice. Frontiers Media S.A. 2017-07-11 /pmc/articles/PMC5504168/ /pubmed/28744289 http://dx.doi.org/10.3389/fpls.2017.01166 Text en Copyright © 2017 Zhou, Tao, Tang, Wang, Zhong, Wang, Yuan, Yu, Zhang, Wang, Liang and Dong. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Plant Science
Zhou, Yong
Tao, Yajun
Tang, Dongnan
Wang, Jun
Zhong, Jun
Wang, Yi
Yuan, Qiumei
Yu, Xiaofeng
Zhang, Yan
Wang, Yulong
Liang, Guohua
Dong, Guichun
Identification of QTL Associated with Nitrogen Uptake and Nitrogen Use Efficiency Using High Throughput Genotyped CSSLs in Rice (Oryza sativa L.)
title Identification of QTL Associated with Nitrogen Uptake and Nitrogen Use Efficiency Using High Throughput Genotyped CSSLs in Rice (Oryza sativa L.)
title_full Identification of QTL Associated with Nitrogen Uptake and Nitrogen Use Efficiency Using High Throughput Genotyped CSSLs in Rice (Oryza sativa L.)
title_fullStr Identification of QTL Associated with Nitrogen Uptake and Nitrogen Use Efficiency Using High Throughput Genotyped CSSLs in Rice (Oryza sativa L.)
title_full_unstemmed Identification of QTL Associated with Nitrogen Uptake and Nitrogen Use Efficiency Using High Throughput Genotyped CSSLs in Rice (Oryza sativa L.)
title_short Identification of QTL Associated with Nitrogen Uptake and Nitrogen Use Efficiency Using High Throughput Genotyped CSSLs in Rice (Oryza sativa L.)
title_sort identification of qtl associated with nitrogen uptake and nitrogen use efficiency using high throughput genotyped cssls in rice (oryza sativa l.)
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5504168/
https://www.ncbi.nlm.nih.gov/pubmed/28744289
http://dx.doi.org/10.3389/fpls.2017.01166
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