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Identification of new QTL for salt tolerance from rice variety Pokkali


Chen, T and Zhu, Y and Chen, K and Shen, C and Zhao, X and Shabala, S and Shabala, L and Meinke, H and Venkataraman, G and Chen, Z-H and Xu, J and Zhou, M, Identification of new QTL for salt tolerance from rice variety Pokkali, Journal of Agronomy and Crop Science, 2, (202-213) pp. 1-12. ISSN 0931-2250 (2020) [Refereed Article]

Copyright Statement

Copyright 2020 Blackwell Verlag GmbH

DOI: doi:10.1111/jac.12387


Salt stress is an ever‐present threat to rice production worldwide. Rice salinity tolerance is complex, both genetically and physiologically. The success and effectiveness in selecting salt‐tolerant rice variety require the identification of QTL for the tolerance and closely linked molecular markers. In the present study, a RIL population consisting of 148 lines, derived from a cross between IR29 (salt‐sensitive) and Pokkali (salt‐tolerant), was used to identify new QTL for salt tolerance and investigate the relationships between salt stress caused injury and the changes in different physiological and morphological traits at the seedling stage. 14,470 high‐quality SNP markers generated by the Rice 56K SNP array were converted to 1,467 bin markers for linkage mapping. A high‐density genetic linkage map covering 1,680.9 cM was constructed, with the physical to genetic distance ratio being 222 Kb/cM. In total, 23 QTL for different salt tolerance indices were identified, including the previously reported Saltol which is currently used in breeding programmes. Three QTL for salt injury score (SIS) were located on chromosomes 1, 4 and 12, all being closely related to the long‐distant Na+ transport from roots to shoots. These QTL showed additive effects, thus can be effectively used in breeding programme to pyramid various tolerance genes.

Item Details

Item Type:Refereed Article
Keywords:bin map, linkage mapping, long-distant Na+ transport, QTL pyramiding, salt injury score
Research Division:Agricultural, Veterinary and Food Sciences
Research Group:Crop and pasture production
Research Field:Agro-ecosystem function and prediction
Objective Division:Plant Production and Plant Primary Products
Objective Group:Grains and seeds
Objective Field:Barley
UTAS Author:Chen, T (Mr Tianxiao Chen)
UTAS Author:Shabala, S (Professor Sergey Shabala)
UTAS Author:Shabala, L (Associate Professor Lana Shabala)
UTAS Author:Meinke, H (Professor Holger Meinke)
UTAS Author:Zhou, M (Professor Meixue Zhou)
ID Code:137713
Year Published:2020
Web of Science® Times Cited:21
Deposited By:TIA - Research Institute
Deposited On:2020-02-28
Last Modified:2020-06-12

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