Genome-wide association study and genomic prediction of Fusarium ear rot resistance in tropical maize germplasm
Yubo Liu,
Guanghui Hu,
Ao Zhang,
Alexander Loladze,
Yingxiong Hu,
Hui Wang,
Jingtao Qu,
Xuecai Zhang,
Michael Olsen,
Felix San Vicente,
Jose Crossa,
Feng Lin,
Boddupalli M. Prasanna
Affiliations
Yubo Liu
College of Agronomy, Shenyang Agricultural University, Shenyang 110866, Liaoning, China; International Maize and Wheat Improvement Center (CIMMYT), El Batan, Texcoco, Mexico; College of Biological Science and Technology, Shenyang Agricultural University, Shenyang 110866, Liaoning, China
Guanghui Hu
International Maize and Wheat Improvement Center (CIMMYT), El Batan, Texcoco, Mexico; Maize Research Institute, Heilongjiang Academy of Agricultural Sciences, Harbin 150086, Heilongjiang, China
Ao Zhang
International Maize and Wheat Improvement Center (CIMMYT), El Batan, Texcoco, Mexico; College of Biological Science and Technology, Shenyang Agricultural University, Shenyang 110866, Liaoning, China
Alexander Loladze
International Maize and Wheat Improvement Center (CIMMYT), El Batan, Texcoco, Mexico
Yingxiong Hu
International Maize and Wheat Improvement Center (CIMMYT), El Batan, Texcoco, Mexico; CIMMYT–China Specialty Maize Research Center, Shanghai Academy of Agricultural Sciences, Shanghai 200063, China; Crop Breeding and Cultivation Research Institute, Shanghai Academy of Agricultural Sciences, Shanghai 200063, China
Hui Wang
International Maize and Wheat Improvement Center (CIMMYT), El Batan, Texcoco, Mexico; CIMMYT–China Specialty Maize Research Center, Shanghai Academy of Agricultural Sciences, Shanghai 200063, China; Crop Breeding and Cultivation Research Institute, Shanghai Academy of Agricultural Sciences, Shanghai 200063, China
Jingtao Qu
Maize Research Institute, Sichuan Agricultural University, Wenjiang 611130, Sichuan, China
Xuecai Zhang
International Maize and Wheat Improvement Center (CIMMYT), El Batan, Texcoco, Mexico
Michael Olsen
International Maize and Wheat Improvement Center (CIMMYT), P. O. Box 1041, Village Market, Nairobi 00621, Kenya
Felix San Vicente
International Maize and Wheat Improvement Center (CIMMYT), El Batan, Texcoco, Mexico
Jose Crossa
International Maize and Wheat Improvement Center (CIMMYT), El Batan, Texcoco, Mexico
Feng Lin
College of Biological Science and Technology, Shenyang Agricultural University, Shenyang 110866, Liaoning, China; Corresponding authors.
Boddupalli M. Prasanna
International Maize and Wheat Improvement Center (CIMMYT), P. O. Box 1041, Village Market, Nairobi 00621, Kenya; Corresponding authors.
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 × 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 × 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.
