| The sclerotinia sclerotiorum is one of the three diseases(Sclerotinia disease, clubroot disease and viral disease) for Brassica napus in our country. It severely reduces the yield and quality of rape and has caused losses by up to 5%~30% every year. Although the use of chemical pesticides and improvements in cultivation practices to some extent can mitigate the impact of Sclerotinia, but with limited effect, chemical pesticides can also pollute the environment. Therefore, researchers pay more attention to the studies about the comprehensive control to the sclerotinia sclerotiorum and disease-resistant breeding. Currently, there are many researches on the disease-resistant mechanism of rapeseed to the sclerotinia sclerotiorum. As lignin being a macromolecular structure material of a secondary cell wall, it plays a very important role of plants coping with the infection to the fungi. This study explores the relations between sclerotinia sclerotiorum disease-resistance and lignin content, monomer ratio in rapeseed, and QTL mapping on lesion size, lignin content and monomer G/S by using the high density genetic map of SNP. The results are as follows:1. The stems resistant to Sclerotinia sclerotiorum of RIL populations in 2013 and 2014, F2 population in 2014 were analyzed, the results showed that the relative susceptibility of RIL population in 2013 was between 0.28 and 1.36, with the average value being 0.83, and the coefficient of variation was 25.9%; the relative susceptibility of RIL population in 2014 was between 0.34 and 1.33, with the average value being 0.85, and the coefficient of variation was 23.6%; the relative susceptibility of F2 population in 2014 was between 0.25 and 1.90, with the average value being 0.96, and the coefficient of variation was 32.9%.Three tests appeared a continuously normal distribution which suggesting that the trait was typical quantitative trait controlled by several genes.2. After the NIRS collection, 75 stem samples were selected by WINSI for accurate chemical measurement. All the calibration materials were measured with thioacidolysis combined with Gas chromatography(GC-MS) method which is a chemical method for measuring G- lignin and S-lignin content. Comparative figures showed that the data measured had little difference for three times repeats, and the range of variation in the calibration samples was wide enough for building the NIRS models. The NIRS model of G/S in rapeseed stem can predict monomer G/S. The results of texting the validation set showed that standard error of prediction(SEP) was 0.054, the system bias(Bias) was 0.009, the correlation coefficient was 0.935, which meaned the higher reliability of the model.3. Using the near infrared model of fiber component content in rapeseed built by Yang Xiao(2014) to predict lignin content in stem for RIL populations and F2 population and the model established in this study to forecast monomer G/S for RIL populations and F2 population, the results showed continuously normal distribution, which suggesting that these traits were typical quantitative traits controlled by several genes. Wherein the lignin content of RIL population in 2013 ranged from 4.20 to 11.80, with the average and coefficient of variation respectively being 8.94 and 18%; the lignin content of RIL population in 2014 ranged from 6.02 to 11.63, with the average and coefficient of variation respectively being 9.55 and 10%; the lignin content of F 2 population in 2014 ranged from 4.23 to 13.44, with the average and coefficient of variation respectively being 10.48 and 12%. The monomer G/S of RIL population in 2013 ranged from 0.75 to 1.40, with the average and coefficient of variation respectively being 1.10 and 10%; the monomer G/S of RIL population in 2014 ranged from 0.30 to 1.30, with the average and coefficient of variation respectively being 0.80 and 23%; the monomer G/S of F2 population in 2014 ranged from 0.45 to 1.25, with the average and coefficient of variation respectively being 0.93 and 16%.4. With the study of correlation on lesion size, lignin content and monomer G/S, the results showed that the lesion size of RIL in 2013 and 2014 had a significantly negative correlation with lignin content in stem with the correlation coefficient being respectively-0.348 and-0.286, and had a positive correlation with monomer G/S with the correlation coefficient being respectively 0.198 and 0.167. Analysis for the correlation of lesion size, lignin content and monomer G/S for RIL populations in 2013 and 2014 showed a significantly positive correlation. The coefficient of lesion size was 0.865, with that of lignin content and monomer G/S being 0.219 and 0.206 respectively. Therefore, the results of tests were more accurate with less affection of the environment. During the analysis for the correlation of lignin content in seed and stem of RIL populations, there were no significant correlation in 2013 and 2014, however, there were significantly positive correlation on lignin content in seed of the two years, with the correlation coefficient being 0.724, the lignin content in stem of the two years also had significantly positive correlation, with the correlation coefficient being 0.219. The lesion size of F2 in 2014 was significantly negative correlatio n with lignin content in stem and the correlation coefficient was-0.306, showing no significant correlation with monomer G/S. In order to further study the relationship between the lignin content and Sclerotinia-resistance, two samples of both the Sclerotinia-resistant and susceptible materials were picked to be frozen sections and stained in the F3 population, the result showed that lignin content in Sclerotinia-susceptible materials(A,C) was significantly lower than in Sclerotinia-resistant plants(B, D).5. With the high-density SNP genetic map and the lesion size, lignin content and monomer G/S of stem in RIL population, 20 QTL which located on the A04, A05, A06, A08, C01, C03, C04, C06 and C07 chromosomes, including 9 Q TL for lesion size, 3 QTL for lignin content, 8 QTL for monomer G/S were found in the QTL analysis. The confidence intervals of q2013A05LS-2 and q2014A05LS-2 overlapped, and their additive effects were from female parent GH06, possibly they were the same QTL. The confidence intervals o f q2013C07LigG/S-1 and q2013C07LigG/S-2 overlapped. The q2013C07LigG/S-2 and q2014C07LigG/S had the same part of the confidence interval. Because additive effects of 3 QTL were from the male parent, so that they may be the same QTL. |
PDF Full Text Request