Association analysis for resistance to Striga hermonthica in diverse tropical maize inbred lines

Abstract

Striga hermonthica is a widespread, destructive parasitic plant that causes substantial yield loss to maize productivity in sub-Saharan Africa. Under severe Striga infestation, yield losses can range from 60 to 100% resulting in abandonment of farmers' lands. Diverse methods have been proposed for Striga management; however, host plant resistance is considered the most effective and affordable to small-scale famers. Thus, conducting a genome-wide association study to identify quantitative trait nucleotides controlling S. hermonthica resistance and mining of relevant candidate genes will expedite the improvement of Striga resistance breeding through marker-assisted breeding. For this study, 150 diverse maize inbred lines were evaluated under Striga infested and non-infested conditions for two years and genotyped using the genotyping-by-sequencing platform. Heritability estimates of Striga damage ratings, emerged Striga plants and grain yield, hereafter referred to as Striga resistance-related traits, were high under Striga infested condition. The mixed linear model (MLM) identified thirty SNPs associated with the three Striga resistance-related traits based on the multi-locus approaches (mrMLM, FASTmrMLM, FASTmrEMMA and pLARmEB). These SNPs explained up to 14% of the total phenotypic variation. Under non-infested condition, four SNPs were associated with grain yield, and these SNPs explained up to 17% of the total phenotypic variation. Gene annotation of significant SNPs identified candidate genes (Leucine-rich repeats, putative disease resistance protein and VQ proteins) with functions related to plant growth, development, and defense mechanisms. The marker-effect prediction was able to identify alleles responsible for predicting high yield and low Striga damage rating in the breeding panel. This study provides valuable insight for marker validation and deployment for Striga resistance breeding in maize.

Figure 1

(A) Cross-validation plot showing the optimal number of clusters. (B) Population structure plot of the inbred lines (k = 3). C) Principal component analysis based on 150 maize inbred lines using the 16,735 SNP markers. D) Phylogenetic tree showing the genetic relationship among 150 diverse maize inbred lines.

Figure 2

Manhattan plot indicating SNPs associated with (A) Grain yield, (B) Striga damage score at 10 WAP (C) Emerged Striga plants at 10 WAP. The graph refers to the quantile–quantile (Q-Q) plot of the P-values observed and expected from the association analysis under Striga infestation.

Figure 3

Allelic effects of haplotype blocks associated with Grain yield (A,B) blue colour, Striga damage ratings (C–E) green colour, emerged Striga plants (F,G) gray colour under Striga infestation.