Assessment of the potential for genomic selection to improve resistance to fusarium stalk rot in maize

LOHITHASWA HIRENALLUR CHANDAPPA^1*SHOWKATH BABU B M¹SOWMYA M S¹Santhosh Kumari Banakar¹MALLIKARJUNA N¹JADESHA GANIGA¹MALLIKARJUNA M G²Balasundara D C³ANAND PANDRAVADA³

• ¹University of Agricultural Sciences, Bangalore, Bangalore, India
• ²Indian Agricultural Research Institute (ICAR), New Delhi, National Capital Territory of Delhi, India
• ³Corteva Agriscience Bangalore, India, Bangalore, Karnataka, India

Fusarium stalk rot (FSR), caused by Fusarium verticilliodes, is a serious disease in maize.Resistance to FSR is complexly inherited. Thus, an investigation was carried out to predict and validate the genomic estimated breeding values (GEBVs) for FSR resistance. Three doubled haploid (DH) populations induced from F1 and F2 of the cross VL1043 × CM212 and F2 of the cross VL121096 × CM202 were used in the current study. Six different parametric models (Genomic-Best Linear Unbiased Predictors (GBLUP), BayesA, BayesB, BayesC, Bayesian least absolute shrinkage and selection operator (BLASSO), and Bayesian Ridge Regression (BRR) were employed to estimate the prediction accuracy. The estimates of descriptive statistics and genetic variability parameters, which include mean, standardized range, genetic variance, phenotypic and genotypic coefficients of variations, broad sense heritability, and genetic advance as per cent mean (GAM), were relatively higher in DHF2s than those in DHF1s. Further, the accuracy of predicted GEBV for FSR resistance was assessed using five-fold and independent validation. The training population size and marker density were optimized by considering different proportions of training set (TS) and validation set (VS) and varying marker density from 40 to 100%. Prediction accuracies displayed an increasing trend with an increase in the proportion of training set size and marker density in all three DH populations. The TS:VS proportion of 75:25 in DHF1 (VL1043 × CM212) and DHF2 (VL121096 × CM202), and 80:20 in DHF2 of VL1043 × CM212 resulted in greater prediction accuracy than other TS:VS proportions. Study of linkage disequilibrium (LD) decay pattern across all the populations indicated that the number of markers employed were sufficient to conduct a genomic prediction (GP) study in two DHF2 populations of crosses VL1043 × CM212 and VL121096 × CM202. Prediction accuracies of 0.24 and 0.17 were recorded for FSR resistance in independent validation when DHF2 of cross VL121096 × CM202 was used for validation and DHF1 and DHF2s from the cross VL1043 × CM212 as training sets. A significant positive correlation of FSR resistance between DHs selected based on their GEBVs and those selected based on test cross performance indicated the efficiency of genomic prediction models.