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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, itâs very difficult to exploit and tap all the genomic regions conferring resistance using classical approaches of quantitative trait loci (QTL) mapping, itâs very important to have a planned strategy to harness such resistance mechanism. One of the most promising approach 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 bi-parental populations from crosses between resistant and susceptible parents. Where, Jasmine 85, Tetep and MTU 9992 were resistant parents and TN1, Swarna Sub1, II32B, IR54 and IRBB4 were susceptible parents. During rainy season (2020) the F7 recombinant inbred lines (RIL) were screened for their reaction to sheath blight in two hot spot locations. The genotyping was done with Illumina platform having 6564 SNP markers. Three Bayesian models were used, Bayesian A, Bayesian B and Bayesian CPi to train the statistical model for calculation of marker effects and genomic estimated breeding values (GEBV). The prediction accuracy of training set across models ranged from 0.69 to 0.72, lowest and highest prediction accuracies were observed with Bayesian A and Bayesian B models respectively and the average prediction accuracy of tenfold cross validation with different models was 0.60. Bayesian B model exhibited higher prediction accuracies compared to other models studied. The results are lucrative, all in all, higher prediction accuracies across the models studied suggest genomic selection as a promising breeding strategy for predicting sheath blight resistance in Rice.

EVALUATION OF THE EFFICIENCY OF GENOMIC SELECTION APPROACH FOR PREDICTING SHEATH BLIGHT RESISTANCE IN RICE (ORYZA SATIVA L.) USING BAYESIAN MODELS