Study On The Genetic Basis Of Heat Tolerance At Florwering Stage And Main Agronomic Traits In Rice

Study on heat tolerance in rice is getting more and more important, for high temperature stress has become one of the major factors exerting serious influence on rice production. And the genetic basis of heat tolerance in rice is very complex due to different mechanisms mixed together which resulted in slow progress on heat tolerance breeding in rice. Most of the important agronomic traits in rice are quantitatively inherited. Improvement of these quantitative traits is one of the major objectives in rice genetic breeding program. By now, progress on the reseach of the genetic basis and improvement of the major agronomic traits was not significant because of their complex mechanisms and environment effect. So researches on the genetic basis of the major agronomic traits in rice are always given much attention. In this study, we have developed a set of novel population with 202 recombinant inbred lines (RIL) derived from a cross between two indica varieties, T226 and T219, and then treated the RIL population under high temperature regimes in growth chamber during flowering stage, so as to assess the genetic effect of quantitative trait loci (QTLs) conferring heat tolerance at flowering stage in rice with coefficient of heat tolerance. And to dissect the genetic basis of the major agronomic traits in rice, genotype by environment (GxE) interaction and QTLs for ten agronomic traits under various environments including local, year, soil type and nurse manner were analyzed using the population with 202 RILs. The main results are summarized as following:1. A genetic linkage map consisting of 189 SSR markers, covering 1559.6 cM in whole genome, was constructed using the RIL population, with an average interval of 8.3 cM. 189 SSR markers were separated into fourteen groups. The linear order of markers in the linkage map was in good agreement with that published previously.2. Treated the RIL population under high temperature regimes in growth chamber during flowering stage and measured heat tolerance with the relative ratio of spikelet fertility of treated plants with high temperature in growth chamber and with optimal temperature in natural environment during flowering time, QTLs for heat tolerance at flowering stage were analysed by using a mixed linear-model. Seven main effect QTLs controlling heat tolerance during flowering time, located in chromosome 2, 3, 8, 9 and 12were detected in two-year experiments. A QTL, qHT3, located at RM570-RM148 on chromosome 3, was detected in two years, respectively.3. Epistatic interaction analysis showed seven pairs of epistatic QTL which involved 12 loci located in chromosome 2, 3,4, 7, 8 and 9 were detected.4. The correlation between traits was also analyzed. Most of the correlation coefficient between traits were significant at least at one environment. Eleven pairs of traits were with the same significant positive correlation and five pairs with the same significant negative correlation under all five environments. However there were four pairs with different direction of correlation at various environments. The direction of correlation between some traits was stable and some were changeable at different environment.5. GxE interaction was detected using AMMI statistical model. GxE interaction for all ten traits under five environments was significant. The AMMI model dissected the interaction component in two sects and explained the extent of interaction. Plant height (PH), heading date (HD) and 1000 grains weight (KGW) had the least GxE interaction, while Tillers per plant (TP), seed setting ratio(SR), spikelet density (SD) and yield per plant (YD) had higher GxE interaction. Of the total GxE interaction effect, the AMMI model explained 80.24% for PH, 80.09% for HD and 77.33% for panicle length (PL) and 70.72% for grains per panicle (GP). This model explained at least 55.59% of the total interaction effects for the traits observed.6. Interval mapping was used to detect QTL. 129 QTL for ten traits were detected under all various envirnments. The number and location of QTLs for defferent traits varied with various environments.7. Of QTL numbers, medium season at Wuhan in 2005 (E4) had detected forty five QTLs, the most in all various environments; Field environment at Lingshui in 2005 (E2) had detected forty one QTLs, the least in all various environments.. Of all traits, the most QTLs were for PL with nineteen, and the least QTLs was for KGW with seven. To the difference of detected location of QTL in all traits, PL and YD were larger and KGW was the least.8. The QTLs in some agronomic traits with biger LOD value and explanning higher parts of the variation, such as the QTLs for SR at qSR3-1, HD at qHD12-1 and KGW at qKGW5-1, were stable and detected under various environments. Some QTLs were only detected under special environments. The QTLs for KGW had little difference among environments.