QTL Mapping Of Rice Quality Traits Using Koshihikari×Guichao2 RIL Population

The demand for superior grain quality is increasingly becoming a priority for international export markets in all of the cultivated rice-producing areas worldwide. The primary components of rice grain quality include appearance, eating, cooking, milling and nutritional qualities. All values are determined by their physical-chemical properties and other socio-cultural factors. In this study, we have analyzed the quantitative trait loci, that are involved in the control of grain length, grain width, length-width ratio, percentage of grains with chalkiness, thousand-seed weight, fat content, protein content, amylose content and RVA profile properties. Further, we are preparing to construct the chromosome segment substitution lines derived from Koshihikari/Guichao2, in two successive years. The results are as follows:1. In this study,we characterized QTLs of rice quality, including grain length, grain width, length-width ratio, percentage of grains with chalkiness, thousand-seed weight, fat content, protein content, amylose content using 184 Koshihikari/Guichao2 RIL population. Thirteen additive QTLs were analyzed, which were distributed on chromosome 2,3,4,6,7, 11 respectively. Seven QTLs, qGL-3a, qGL-3b, qGW-6, qLWR-4, qLWR-6, qRFC-6 and qAC-6 were detected both in 2009 and 2010, which conformed to be stable QTLs. Furthermore, there were no reports about qLWR-4 and qLWR-6 previously. They may be two new QTLs controlling length-width ratio. These QTLs can be separated by marker-assisted selection, and then introgressed into other cultivars to improve their quality.2. The RIL population showed bimodal segregations for amylose content, indicating the involvement of a major gene for it, whereas normal distributions for the others, indicating quantitative-inherited.3. Correlations between RVA profile properties and other rice quality and QTLs for RVA profile properties analysis were characterized using 184 Koshihikari/Guichao2 RIL population in 2009 and 2010. The results showed that the correlation between RVA profile properties and fat content, as well as protein content and amylose content were highly significant, whereas there were no apparently significant correlations between RVA profile properties and apparence quality. Twenty additive QTLs were detected for RVA profile characteristics, eight QTLs were detected both in 2009 and 2010. A QTL for five RVA profile properties located in the same interval, between SSR marker RM508 and RM190, had been detected in both two years. This position includes the gene Wx, which indicates that the amylose content significantly affects the RVA profile properties.