Literature DB >> 18622741

Dissection of genetic overlap of salt tolerance QTLs at the seedling and tillering stages using backcross introgression lines in rice.

Jinping Zang1, Yong Sun, Yun Wang, Jing Yang, Fang Li, Yongli Zhou, Linghua Zhu, Reys Jessica, Fotokian Mohammadhosein, Jianlong Xu, Zhikang Li.   

Abstract

QTLs for salt-tolerance (ST) related traits at the seedling and tillering stages were identified using 99 BC(2)F(8) introgression lines (IL) derived from a cross between IR64 (indica) as a recurrent parent and Binam (japonica) from Iran as the donor parent. Thirteen QTLs affecting survival days of seedlings (SDS), score of salt toxicity of leaves (SST), shoot K(+) concentration (SKC) and shoot Na(+) concentration (SNC) at the seedling stage and 22 QTLs underlying fresh weight of shoots (FW), tiller number per plant (TN) and plant height (PH) at the tillering stage were identified. Most QTLs detected at the tillering stage showed obvious differential expression to salt stress and were classified into three types based on their differential behaviors. Type I included 11 QTLs which were expressed only under the non-stress condition. Type II included five QTLs expressed in the control and the salt stress conditions, and three of them (QPh5, QPh8 and QTn9) had similar quantity and the same direction of gene effect, suggesting their expression was less influenced by salt stress. Type III included six QTLs which were detectable only under salt stress, suggesting that these QTLs were apparently induced by the stress. Thirteen QTLs affecting trait difference or trait stability of ILs between the stress and non-stress conditions were identified and the Binam alleles at all loci except QPh4, QTn2 and QFw2a decreased trait difference. The three QTLs less influenced by the stress and 13 QTLs affecting trait stability were considered as ST QTLs which contributed to ST. Comparing the distribution of QTLs detected at the seedling and tillering stages, most (69%) of them were genetically independent. Only four were the same or adjacent regions on chromosomes 1, 2, 8 and 11 harboring ST QTLs detected at the two stages, suggesting that partial genetic overlap of ST across the two stages occurs. It is likely, therefore, to develop ST rice variety for both stages by pyramiding of ST QTLs of different stages or selection against the overlapping QTLs between the two stages via marker-assisted selection (MAS).

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Year:  2008        PMID: 18622741     DOI: 10.1007/s11427-008-0081-1

Source DB:  PubMed          Journal:  Sci China C Life Sci        ISSN: 1006-9305


  18 in total

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Journal:  Mol Biol Rep       Date:  2011-12-30       Impact factor: 2.316

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Journal:  Mol Genet Genomics       Date:  2010-07-03       Impact factor: 3.291

3.  Identification of genetic factors influencing salt stress tolerance in white clover (Trifolium repens L.) by QTL analysis.

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4.  Mapping quantitative trait loci associated with yield and yield components under reproductive stage salinity stress in rice (Oryza sativa L.).

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7.  Fine mapping of qSKC-1, a major quantitative trait locus for shoot K+ concentration, in rice seedlings grown under salt stress.

Authors:  Wen Jing; Ping Deng; Chengjuan Cao; Wenhua Zhang
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8.  Simultaneous Improvement and Genetic Dissection of Salt Tolerance of Rice (Oryza sativa L.) by Designed QTL Pyramiding.

Authors:  Yunlong Pang; Kai Chen; Xiaoqian Wang; Wensheng Wang; Jianlong Xu; Jauhar Ali; Zhikang Li
Journal:  Front Plant Sci       Date:  2017-07-20       Impact factor: 5.753

9.  Salinity tolerance, Na+ exclusion and allele mining of HKT1;5 in Oryza sativa and O. glaberrima: many sources, many genes, one mechanism?

Authors:  John Damien Platten; James A Egdane; Abdelbagi M Ismail
Journal:  BMC Plant Biol       Date:  2013-02-27       Impact factor: 4.215

10.  Joint Mapping and Allele Mining of the Rolled Leaf Trait in Rice (Oryza sativa L.).

Authors:  Qiang Zhang; Tianqing Zheng; Long Hoang; Chunchao Wang; Charles Joseph; Wenzhong Zhang; Jianlong Xu; Zhikang Li
Journal:  PLoS One       Date:  2016-07-21       Impact factor: 3.240

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