Analysis of the Efficiency of Genomic Selection Models for Predicting Sheath Blight Resistance in Rice (Oryza sativa L.,)
نویسندگان
چکیده
The research was undertaken during June-October 2020 at Seethanagaram and Draksharam villages of East Godavari district, Andhra Pradesh, India with an objective to evaluate efficiency genomic selection models involving 1545 recombinant inbred lines (RILs) derived from eleven bi-parental populations in Rice. During 2020, the F7 RILs were screened two hot spot locations. genotyping done Infinium platform having 6564 SNP markers. Five used rrBLUP, BayesA, BayesB, BayesCPi GBLUP train statistical model for calculation marker effects estimated breeding values (GEBVs). prediction accuracy (data fit) training set across ranged 0.63–0.72, lowest highest accuracies observed rrBLUP respectively. Tenfold cross validation different approaches, average 0.60 (rrBLUP, BayesB BayesCPi) –0.72 (GBLUP). exhibit higher compared other studied. predictive ability increased dramatically more SNPs included analysis until 2000 markers 0.681, no significant improvement beyond this observed. results are lucrative, all all, high study suggest as a very promising strategy while sheath blight resistance rice increase genetic gain.
منابع مشابه
Identification of QTLs and possible candidate genes conferring sheath blight resistance in rice (Oryza sativa L.)
Sheath blight, caused by the pathogenic fungus Rhizoctonia solani Kühn, is one of the most devastating diseases in rice. Breeders have always faced challenges in acquiring reliable and absolute resistance to this disease in existing rice germplasm. In this context, 40 rice germplasm including eight wild, four landraces, twenty- six cultivated and two advanced breeding lines were screened utiliz...
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ژورنال
عنوان ژورنال: International journal of Bio-resource and Stress Management
سال: 2022
ISSN: ['0976-3988', '0976-4038']
DOI: https://doi.org/10.23910/1.2022.2763