Studies On Physiological Genetics Of Rice

In this study, a linkage map consisting of 207 DNA markers were constructed by using 247 recombinant inbred lines derived from an indica-indica rice cross Zhenshan 97B/Milyang46. Quantitative trait loci(QTLs) conditioning physiological and biochemical traits related to growth and development of rice were determined by composite interval mapping and genotype-by environment(GE) interactions were analyzed. The main results were summaried as follows.1. Mapping QTLs conditioning leaf traits and root vitality in a recombinant inbredline population of riceAt initial heading, the leaf traits, such as leaf area, leaf length, leaf width, leaf perimeter, leaf length/width ratio, were measured on top first leaf,top second and top third leaves, as well as root vitality measured by root exudates. The linkage map of RIL populations was used for the determination of QTLs conditioning five leaf traits and root exudates. A total of 25 QTLs located in 15 intervals were detected to have significant additive effects for leaf traits and root vitality, with LOD scores ranging 3.0-13.0 and 3.4%～20.1% phenotypic variation explained for a single QTL. Epistasis analysis detected 65 and 3 significant additive-by-additive interactions for leaf traits and root vitality respectively, of which 3 occurred between QTLs with the additive effects, 34 occurred between QTLs with the additive effects and epistatic effects. On comparison with QTLs for yield traits detected in the same population previously, it was found that the majority of QTLs for leaf traits and root vitality and those for yield traits were located in similar intervals.2. Genetic analysis of starch branching enzyme activity in rice grainIn two years, the activities of starch branching enzyme of the parents and 247 RILs were measured 10 d and 20 d respectively after flowering. A total of 3 quantitative trait loci(QTLs) were detected to have significant additive effects on Q enzyme activities 10 d after flowering with 9. 99% phenotypic variations explained for the three QTLs. Meanwhile, qQ10-6 with significant QTL X environment interaction was detected. Epistasis analysis detected 5 and 2 significant additive-by-additive interactions for Q enzyme 10 d and 20 d respectively after flowering, and three pairs of QTLs 10 d after flowering with significant epistasis X environment interactions were detected, explaining 3% to 12% of the phenotypic variation. The results showed that the environmental factors had obvious effect on the gene expression of Q enzyme activity in rice grain.3. Analysis of QTL x environment interaction for chlorophyll contents in riceIn two years, the chlorophyll a,b contents and chlorophyll a/b ratio of the parents and 247 RILs were measured on top first leaf, top second and top third leaves respectively. The software QTLMapper 1.6 was applied to detect quantitative trait loci(QTLs), additive by environment interactions and epistatic by environment interactions. A total of 12 QTLs in 8 intervals were detected to have significant additive effects for chlorophyll a,b contents and chlorophyll a/b ratio at different leaf positions with 1.96%～9.77% phenotypic variations explained for a single QTL, and 3 QTLs with significant AE interactions were detected. Epistasis analysis detected 18 significant additive by additive interactions for chlorophyll a,b contents and chlorophyll a/b ratio , and two pair of QTLs with significant AAE interactions was detected. On comparison with QTLs for yield traits detected in the same populations, it was frequently found that QTLs for chlorophyll a,b contents and chlorophyll a/b ratio and those for yield traits were located in same intervals.4. QTL analysis of chlorophyll contents in rice under different water supplyTo make an genetic analysis of chlorophyll contents and stress sensitive index inheriiitance under different water supply, the parents and 247 RILs were respectively planted under water stress and non-water stress, and chlorophyll contents were continuely measured on the same leaf at seedling and grain filling respectively. Under different water supply, a total of 13 QTLs for chlorophyll contents was detected to have significant additive effects at different growth stages. Among the QTLs detected, 6 QTLs were detected under water stress, explaining 4.74% to 19.86% of the phenotypic variation, 7 QTLs detected under paddy field, explaining 4.92% to 14.02% of the phenotypic variation. 7 QTLs were detected for stress sensitive index, of which 2 QTLs, qkhChl-2a and qkhChl-6, explained 25.29% and 38.7% of phenotypic variations at the first stage of seedling and grain filling. The alleles for increasing trait values were from Zhenshan 97B. Epistasis analysis detected 50 significant additive-by-additive interactions for chlorophyll contents and stress sensitive index respectively under different water supply, with 3.41%～16.02% phenotypic variations explained for one pair epistasis.5. Genetic dissection of anti-oxidation enzyme activity in rice under different watersupplyThe parents and 247 RILs were respectively planted under water stress and non-water stress, and seedling leaves were sampled to measure protein contents, malondialdehyde contents, activities of superoxide dismutase and catalase. A linkage map consisting of 207 DNA markers was used for the determination of QTLs conditioning the above traits under different water supply. Under water stress and non-water stress, a total of 10 QTLs for protein contents, malondialdehyde contents, activities of superoxide dismutase and catalase was detected to have significant additive effects with 6.09%～24.44% phenotypic variations explained for a single QTL. Among the QTLs detected, one QTL for protein contents(qstPRO-11) and one QTL for malondialdehyde contents(qstMDA-11) were detected in interval RZ816-RG118 on chromosome 11 in paddy field; one QTL for protein contents(qghPRO-5) and one QTL for SOD activity(qghSOD-5) were identified in interval RZ296-RG776B on chromosome 5 under water stress. Epistasis analysis detected 22 significant additive-by-additive interactions for protein contents, malondialdehyde contents, activities of superoxide dismutase and catalase under different water supply respectively, with 4.54%～27.31% phenotypic variations explained for one pair epistasis.It was found that some QTLs conditioning different traits studied in Zhenshan 97B/Milyang46 RIL populations often located in the same intervals. For example, the QTLs for yield components, leaf traits, chlorophyll contents, silicon contents and stress sensitive index were detected to be located in the interval RM196-RZ516 on chromosome 1. Then , these different agronomic and physiological traits were mapped in the same molecular linkage map to construct a functional map. We could intergrate the agronomy and physiology research by molecular markers in the functional map and identify the key or controling loci for the expression of quantitative traits. The genetic relationship between agronomic and physiological traits could be analysed.