Screening for putative quantitative trait loci for salinity tolerance at the reproductive stage in rice
2008
Calapit-Palao, C.P.O., International Rice Research Inst., DAPO Box 7777, Metro Manila (Philippines) | de la Viña, C.B., Philippines Univ. Los Banos, College, Laguna (Philippines). Genetics and Molecular Biology Div. | Tecson-Mendoza, E.M., Philippines Univ. Los Banos, College, Laguna (Philippines). Inst. of Plant Breeding | Sajise, A.G. | Singh, R.K., International Rice Research Inst., DAPO Box 7777, Metro Manila (Philipines)
Salt tolerance is a complex trait and varies with the growth stages in rice. The most vulnerable to salt stress are the seedling and reproductive stages, the latter being considered more crucial as it ultimately determines yield. Contrasting parents IR64 (improved, salt-sensitive variety) and IR4630-22-2-5-1-3 (improved, salt-tolerant variety) were evaluated for reproductive stage salinity tolerance. Each plant was pruned at booting stage, leaving only the penultimate and the flag leaves. Analysis of variance showed that pruning at this stage did not affect grain yield and thus can effectively be used as part of the method for screening for reproductive stage salinity tolerance. Two hundred and 39 plants from the F2 mapping population derived from the cross between IR64 and IR4630-22-2-5-1-3 were grown to maturity in the screened house to test performance at 100 mM salt concentration for reproductive stage tolerance. Physical parameters such as plant height, panicle length, panicle number, tiller number, shoot and root dry weight, grain weight, and yield were gathered to test the correlation with the observed pollen fertility. Shoot dry weight and plant height were correlated with pollen fertility at alpha=0.05 whereas panicle length and grain yield were correlated at alpha=0.01. Only 133 of the 640 SSR markers used in the parental survey were found polymorphic and were used for profiling of the F2S. More SSR markers are being run to fill the gaps at different linkage groups. Work is in progress; the plan is to run at least 150 SSR markers in the mapping population to cover the entire genome with 10-12 cM average distance between markers. QTL cartographer would be used to identify the putative QTLs based on LOD score.
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