Analysis For Protein Content And QTL Mapping Of Four Protein Fraction In Rice

1,Analysis for Protein Content in Rice by Near Infrared Reflectance Spectroscopy(NIRS) TechniqueThe technology of near infrared reflectance spectroscopy which has the advantage of quickness, no-pollution and no-preparetion has been developed from 20th century 1980's and has been used in many aspects such as food quality analysis, crop quality breeding and analysis and so on. This research use three different near infrared spectroscopy to analyze protein content in rice.Six predicted mathematic models for analysis of protein content in brown and milled rice were established, with the technique of near infrared reflectance spectroscopy(NIRS) and partial least square(PLS) algorithm. The protein content of brown rice and milled rice was determined by chemical methods. The different predicted models were established with the near infrared spectroscopy of paddy, whole grain and rice flour, which was to research the effect of sample forms on predicting veracity of NIR models. The determination coefficients (R_c²) of calibration of NIR models of brown rice protein content for paddy, whole grain and flour were 0.893, 0.971 and 0.987 respectively, the root mean square errors of calibration(RMSEC) was 0.507, 0.259 and 0.183. The R_c² of NIR models of milled rice protein content for paddy, whole grain and flour were 0.897, 0.984 and 0.986, the RMSEC was 0.497, 0.186 and 0.190 respectively. The veracity of models were estimated by the determination coefficients (R_cv²) and the root mean square errors (RMSECV) of cross-validation, the determination coefficients(R_v²) and the root mean square errors(RMSEV) of external validation. The R_cv² of NIR models of brown rice protein content were 0.865, 0.962 and 0.984 respectively, the RMSECV 0.557, 0.290 and 0.205. The R_cv² of NIR models of milled rice protein content were 0.845, 0.951 and 0.979, the RMSECV 0.594, 0.316 and 0.233. The R_v² of the NIR models for brown rice protein content were 0.683, 0.801 and 0.939, the RMSEV 0.962, 0.799 and 0.434. The R_V² of the NIR models for milled rice protein content were 0.673, 0.921 and 0.959, the RMSEV 0.976, 0.513 and 0.344. From the above results, we concluded that the veracity of flour NIR models is the best, that of whole grain better, while that of paddy poor. The NIR method can substitute the chemical method and be widely used in the breeding and quality analysis of rice.2,Detection of QTL for four protein fraction in rice using using recross inbred linesA recombinant inbred line(RIL) population derived from the cross of Asominori (japonica) and IR24(indica) were used to detect quantitative trait loci(QTLs) for four protein content in rice. A total of 16 QTL controlling four different protein were detected. Two OTL controlling albumin in rice were detected and named qALB-land qALB-2. The qALB-1 and qALB-2 were detected on chromosomesl, 2 with LOD of 4.15 and 2.07, and the individual QTL accounted for 19.42ï¼…and 9.12ï¼…of the total phenotypic variance, respectively. The positive effects of qALB-land qALB-2 came from indica variety IR24 and japonica variety Asominofi, respectively.Six QTL controlling globulin in rice were detected and named qGLB-1.1, qGLB-1.2, qGLB-2.1, qGLB-2.2, qGLB-5.1and qGLB-5.2. The qGLB-1.1, and qGLB-1. 2 were detected on chromosomesl, with LOD of 4.02 and 3.61, and the individual QTL accounted for 18.09ï¼…and 17.27ï¼…of the total phenotypic variance, respectively. The qGLB-2.1, and qGLB-2.2 were detected on chromosomes2, with LOD of 2.97 and 2.42, and the individual QTL accounted for 13.43ï¼…and 10.56ï¼…of the total phenotypic variance, respectively. The qGLB-5.1, and qGLB-5.2 were detected on chromosomesS, with LOD of 3.68 and 2.75, and the individual QTL accounted for 18.04ï¼…and 12.20ï¼…of the total phenotypic variance, respectively. The positive effects of all six QTL for globulin came from japonica variety Asominori.Four QTL controlling prolamin in rice were detected and named qPLA-1, qPLA-3, qPLA-10.1, qPLA-10.2, qPLA-1 and qPLA-3 were detected on chromosome 1, 3, with LOD of 2.83, 2.72 and the individual QTL accounted for 16.38ï¼…and 11.52ï¼…of the total phenotypic variance, respectively. The positive effects of qPLA-1 and qPLA-3 both came from indica variety 1R24. qPLA-10.1 and qPLA-10.2 were detected on chromosome 10, with LOD of 3.64 and 4.52 and the individual QTL accounted for 26.98ï¼…and 23.26ï¼…of the total phenotypic variance, respectively. The positive effects of qPLA-10.1 and qPLA-10.2 both came from japonica variety Asominori.Four QTL controlling glutelin in rice were detected and named qGLT-2, qGLT-10, qGLT-11, qGLT-12, qGLT-2, qGLT-10, qGLT-12 were detected on chromosome 2, 10, 12, with LOD of 2.16, 2.97, 3.15, andthe individual QTL accounted for 9.28ï¼…, 14.57ï¼…, ï¼…14.60ï¼…of the total phenotypic variance, respectively. The positive effects of qGLT-2, qGLT-10 and qGLT-12 came from japonica variety Asominori. qGLT-11 were detected on chromosome 11, with LOD of 2.21, and accounted for 8.56ï¼…of the total phenotypic variance. The positive effects qGLT-11 came from the indica variety IR24.