Genome-wide association study and genomic prediction of Fusarium ear rot resistance in tropical maize germplasm

Fusarium ear rot (FER) is a destructive maize fungal disease worldwide. In this study, three tropical maize populations consisting of 874 inbred lines were used to perform genome-wide association study (GWAS) and genomic prediction (GP) analyses of FER resistance. Broad phenotypic variation and high heritability for FER were observed, although it was highly influenced by large genotype-by-environment interactions. In the 874 inbred lines, GWAS with general linear model (GLM) identified 3034 single-nucleotide polymorphisms (SNPs) significantly associated with FER resistance at the P-value threshold of 1 x 10(-5), the average phenotypic variation explained (PVE) by these associations was 3% with a range from 2.33% to 6.92%, and 49 of these associations had PVE values greater than 5%. The GWAS analysis with mixed linear model (MLM) identified 19 significantly associated SNPs at the P-value threshold of 1 x 10(-4), the average PVE of these associations was 1.60% with a range from 1.39% to 2.04%. Within each of the three populations, the number of significantly associated SNPs identified by GLM and MLM ranged from 25 to 41, and from 5 to 22, respectively. Overlapping SNP associations across populations were rare. A few stable genomic regions conferring FER resistance were identified, which located in bins 3.04/05, 7.02/04, 9.00/01, 9.04, 9.06/07, and 10.03/04. The genomic regions in bins 9.00/01 and 9.04 are new. GP produced moderate accuracies with genome-wide markers, and relatively high accuracies with SNP associations detected from GWAS. Moderate prediction accuracies were observed when the training and validation sets were closely related. These results implied that FER resistance in maize is controlled by minor QTL with small effects, and highly influenced by the genetic background of the populations studied. Genomic selection (GS) by incorporating SNP associations detected from GWAS is a promising tool for improving FER resistance in maize. (C) 2020 Crop Science Society of China and Institute of Crop Science, CAAS. Production and hosting by Elsevier B.V. on behalf of KeAi Communications Co., Ltd.

Automated summary

The study identified multiple SNPs associated with FER resistance in maize, with moderate prediction accuracies observed. Genomic background and minor QTL were found to play a significant role in controlling FER resistance. Incorporating SNP associations from GWAS into genomic selection shows promise for improving FER resistance in maize.