Association Analysis Of Functional Nutrition Quality With SSR Markers And Screening Of Japonica Rice In Cold Region

Rice plays an important role in the world food crops,more than 50% of the population on rice as the staple food. China is the world’s largest rice producer and consumer,with the improving of people’s living standards and the unreasonable diet leads to various diseases. Functional rice has been paid more and more attention due to the function of regulate physiological, prevention specific diseases, aging, help specific diseases restore and control the physical strength and energy. Therefore, screening the existing varieties and studied the loci of each functional quality to cultivate functional rice varieties has become a new trend. In this research, 226 varieties of japonica rice in cold region as the research objects, determine the functional nutrition contents(lysine, gluten, γ- aminobutyric acid, total flavonoids) and the embryo size, studied at the analysis of genetic variation, correlation and principal components to screening some high quality strains; providing the basis for functional rice quality varieties breeding and industrialization. Using 118 SSR markers to association analysis the above five traits, detection the SSR marker loci related to functional nutrients; providing the theoretical and material basis for functional rice quality varieties breeding and molecular marker-assisted breeding. The main results are as follows:(1)Determine the functional nutrition content of 226 japonica rice in cold region, the results show that the content of lysine, gluten, γ-aminobutyric acid, total flavonoids and embryo size were relatively stable between varieties and two years(2014,2015); addition to GABA,the range of variation of the functional nutrition reached significant levels.(2)Correlation analysis between each functional nutrition traits of 226 materials shows the result was same in two years; lysine content and average embryo weight, embryo of brown rice were all have extremely significant positive correlation; flavonoids content was significant negative correlative with GABA and significant positive correlative with gluten, average embryo weight and embryo of brown rice have extremely significant positive correlation.(3)Principal components analysis shows the cumulative contribution of the embryo factor, flavonoids and gluten factor, GABA factor was 69.2%. The first three principal components can reflect the characteristics of functional nutritional quality in rice, it ca n be used to evaluation different materials.(4)Using the 226 japonica rice’s average value of function nutrient contents screened 4 representative varieties of relatively higher lysine content, 4 representative varieties of relatively lower gluten content, 4 representative varieties of relatively higher γ-aminobutyric acid content, 4 representative varieties of relatively higher total flavonoids acid content, 4 representative varieties of relatively higher average embryo weight and embryo of brown rice. Additional, screen out of seven varieties(Suijing 3,Sujing 5,Mudanjing 21,Hejing 1,Mudanjiang 22,Longnuo 2,Xixuan 1) which have two higher functional nutrition components.(5)Association analysis shows that detected 85 significantly associated loci w ith different traits at p<0.01 conditions in two years,it can explain 1.93 %~15.47% of the phenotypic variation. In two years, detected 3,4,4,2 significantly associated loci with lysine, gluten, flavonoids and embryo size trait; in two methods, detected 3,2,4,4,3 significantly associated loci with lysine, gluten, γ- aminobutyric acid,flavonoids and embryo size trait; in two years and two methods, detected 1,1 significantly associated loci with lysine and flavonoids trait.(6)By anglicizing the 13 associated markers, 20 excellent alleles were screened out.At the same time, some carrier materials which carried multiple elite alleles were screened out. Such as Mudanjiang 3 carried 4 multiple elite alleles,Hejing 3 and Xixuan 1 each carried 3 multiple elite alleles, Dodong 420, Suijing 9, Songjing 9, Longdao 5, Dongnong 423, Songjing 13, Suinuo 1, Zhonglongdao 1, Heijing 8 and Mudanjing 9 each carried 3 multiple elite alleles.