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Identification of quantitative trait loci for salinity tolerance in rice (Oryza sativa L.) using IR29/Hasawi mapping population
Salinity is the second most important abiotic stress after drought that hampers rice production, especially in south and Southeast Asia. Breeding approach supplemented with molecular markers-assisted selection is the most promising approach in terms of efficiency to increase the productivity under s...
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Published in: | Journal of genetics 2017-09, Vol.96 (4), p.571-582 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Salinity is the second most important abiotic stress after drought that hampers rice production, especially in south and Southeast Asia. Breeding approach supplemented with molecular markers-assisted selection is the most promising approach in terms of efficiency to increase the productivity under salt-affected soils. Thirty-day-old rice seedlings of 300
F
5
:
6
recombinant-inbred lines derived from a cross between the salt sensitive, IR29 (
indica
), and a salt tolerant, Hasawi (
aus
), were used to identify quantitative trait loci (QTLs) linked to salinity tolerance. One hundred and ninety four polymorphic SNP markers were used to construct a genetic linkage map involving 142 selected RILs that covered 1441.96 cM genome with an average distance of 7.88 cM between loci. Twenty new QTLs (LOD > 3) were identified on chromosomes 1, 2, 4, 6, 8, 9 and 12 using composite interval mapping with
R
2
as high as >20% with LOD value of 7.21. Many earlier studies reported big
qSaltol
for seedling stage salinity tolerance in rice is on short arm of chromosome 1 but none of the QTL in our study was on
qSaltol
or nearby position, therefore, Hasawi conferred salinity tolerance in RILs due to novel QTLs. It is suggested to fine map the novel QTLs so that the level of salinity tolerance could be further enhanced by pyramiding of the different QTLs in one genetic background through marker-assisted selection. |
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ISSN: | 0022-1333 0973-7731 |
DOI: | 10.1007/s12041-017-0803-x |