Combination of linkage and association mapping with genomic prediction to infer QTL regions associated with gray leaf spot and northern corn leaf blight resistance in tropical maize

Abstract

Among the diseases threatening maize production in Africa are gray leaf spot (GLS) caused by Cercospora zeina and northern corn leaf blight (NCLB) caused by Exserohilum turcicum. The two pathogens, which have high genetic diversity, reduce the photosynthesizing ability of susceptible genotypes and, hence, reduce the grain yield. To identify population-based quantitative trait loci (QTLs) for GLS and NCLB resistance, a biparental population of 230 lines derived from the tropical maize parents CML511 and CML546 and an association mapping panel of 239 tropical and sub-tropical inbred lines were phenotyped across multi-environments in western Kenya. Based on 1,264 high-quality polymorphic single-nucleotide polymorphisms (SNPs) in the biparental population, we identified 10 and 18 QTLs, which explained 64.2% and 64.9% of the total phenotypic variance for GLS and NCLB resistance, respectively. A major QTL for GLS, qGLS1_186 accounted for 15.2% of the phenotypic variance, while qNCLB3_50 explained the most phenotypic variance at 8.8% for NCLB resistance. Association mapping with 230,743 markers revealed 11 and 16 SNPs significantly associated with GLS and NCLB resistance, respectively. Several of the SNPs detected in the association panel were co-localized with QTLs identified in the biparental population, suggesting some consistent genomic regions across genetic backgrounds. These would be more relevant to use in field breeding to improve resistance to both diseases. Genomic prediction models trained on the biparental population data yielded average prediction accuracies of 0.66-0.75 for the disease traits when validated in the same population. Applying these prediction models to the association panel produced accuracies of 0.49 and 0.75 for GLS and NCLB, respectively. This research conducted in maize fields relevant to farmers in western Kenya has combined linkage and association mapping to identify new QTLs and confirm previous QTLs for GLS and NCLB resistance. Overall, our findings imply that genetic gain can be improved in maize breeding for resistance to multiple diseases including GLS and NCLB by using genomic selection.

Keywords: association mapping; genome-wide association study; gray leaf spot; maize; northern corn leaf blight; quantitative trait loci.

FIGURE 1

Frequency distributions for GLS, NCLB disease, and other agronomic traits, namely, anthesis date, silking date, plant height, and ear height, evaluated across the three locations in western Kenya. (A). Biparental CML511×CML546 DH population of 230 lines. (B). Association panel of 239 sub-tropical and tropical maize lines across the three locations. DS scores were for the last rating time point.

FIGURE 2

Pairwise Pearson correlation analysis for eight traits evaluated in three field trials in the biparental CML511×CML546 DH population. AD, anthesis date; SD, silking date; GLS, gray leaf spot, NCLB, northern corn leaf blight; AUDPC, area under disease progress curve; PH, plant height; and EH, ear height. The x marks indicate values that are not significant at p < 0.05.

FIGURE 3

(A, C) Manhattan plots for the GWAS of GLS and NCLB disease severity in the maize association mapping panel. The dashed horizontal line of the Manhattan plot depicts the significance threshold value of p < 8 × 10⁻⁵. The x-axis indicates the SNP location along the 10 chromosomes, with chromosomes separated by different colors. Q–Q plots (B, D) of the estimated -log₁₀(p) from association panel for GLS-DS and NCLB_DS traits. The black line bisecting the plot in Q–Q plots represents the expected p-values with no associations present. The blue line represents the observed p-values using the simplest model GLM(PCA + G) where the association between a phenotype and markers is directly detected. The pink line represents the observed p-values using the MLM (PCA + K + G) model. The green line represents the observed p-values using the FarmCPU model. G, genotype (fixed); PCA, three principal components (fixed); and K, kinship matrix (random).

FIGURE 4

Box-whisker plots for the accuracy of genomic predictions assessed by five-fold cross-validation within association and DH population. AD, days to anthesis; SD, days to silking; PH, plant height; EH, ear height; GLS, gray leaf spot; AUDPC, area under the disease progress curve; NCLB, northern corn leaf blight.