Rice sheath blight (ShB) is one of the most serious fungal diseases caused by Rhizoctonia solani, instigating significant yield losses in many rice-growing regions of the world. Intensive studies indicated that resistance for sheath blight is controlled possibly by polygenes. Because of complex inheritance, it’s very difficult to exploit and tap all the genomic regions conferring resistance using classical approaches of QTL mapping, it’s very important to have a different strategy to harness such resistance mechanism. One promising approach that can potentially provide accurate predictions of the resistance phenotypes is genomic selection (GS). The research was undertaken with an objective to validate genomic selection approach for predicting sheath blight resistance involving 1545 Recombinant inbred lines (RILs) derived from eleven crosses between resistant and susceptible parents (Jasmine 85XTN1, Jasmine 85XSwarnaSub1, Jasmine 85XII32B, Jasmine 85XIR54, TetepXTN1, TetepXSwarna Sub1, TetepXII32B, TetepXIR54, MTU 9992XTN1, MTU 9992XII32B and MTU 9992XIRBB4). Where, Jasmine 85, Tetep & MTU 9992 were resistant parents and TN1, Swarna Sub1, II32B, IR54 & IRBB4 were susceptible parents. During rainy season (2020) the F7 RILs were screened for their reaction to sheath blight in two hot spot locations. The genotyping was done with Illumina platform having 6564 SNP markers. Bayesian B approach was used to train the statistical model for calculation of marker effects and GEBVs. The prediction accuracy of training set (data fit analysis) obtained was 0.70 and random cross validation with different approaches, the prediction accuracy ranged from 0.67 to 0.74. The results are lucrative, all in all, high prediction accuracies observed in this study suggest genomic selection as a very promising breeding strategy for predicting sheath blight resistance in Rice.
Validation of Genomic Selection Approach for Predicting Sheath Blight Resistance in Rice (Oryza sativa L.,)
