Association mapping and genomic prediction for ear rot disease caused by Fusarium verticillioides in a tropical maize germplasm

被引:10
|
作者
Kuki, Mauricio Carlos [1 ]
Barth Pinto, Ronald Jose [1 ]
Bengosi Bertagna, Filipe Augusto [1 ]
Tessmann, Dauri Jose [1 ]
do Amaral Junior, Antonio Teixeira [2 ]
Scapim, Carlos Alberto [1 ]
Holland, James Brendan [3 ,4 ]
机构
[1] Univ Estadual Maringa, Dept Genet & Plant Breeding, BR-87020900 Maringa, Parana, Brazil
[2] Univ Estadual Norte Fluminense, Lab Genet & Plant Breeding, BR-28013602 Campos Dos Goytacazes, Brazil
[3] North Carolina State Univ, USDA ARS, Plant Sci Res Unit, Raleigh, NC 27695 USA
[4] North Carolina State Univ, Dept Crop & Soil Sci, Raleigh, NC 27695 USA
关键词
FUMONISIN CONTAMINATION RESISTANCE; WIDE ASSOCIATION; LEAF-BLIGHT; QUANTITATIVE RESISTANCE; GENETIC ARCHITECTURE; DIALLEL ANALYSIS; COMPLEX TRAITS; SELECTION; PLANT; POPULATION;
D O I
10.1002/csc2.20272
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Fusarium ear rot (FER), caused by Fusarium verticillioides (Sacc.) Nirenberg, is one of the major ear diseases that affect both yield and grain quality in maize (Zea mays L.), especially in tropical environments. Fusarium genetic resistance is a complex trait, controlled by several small-effect genes and strongly influenced by the environment. We applied a comprehensive genome-wide association study and genomic prediction for ear rot and starburst symptoms, using 291,633 high-quality single nucleotide polymorphism (SNPs) markers in 320 tropical maize inbred lines, in two distinct locations in Brazil's southern region. Three SNPs were significantly associated with starburst symptoms, each associated with 6-8% of the phenotypic variance, and with gene models that have expression levels in ears, pericarp, and kernels, corresponding to disease infection period and suggesting some role in FER resistance. No significant SNP was associated with FER, which is an indication that the genetic architecture for this trait is highly polygenic, with potentially many variants having small effects that are not detectable in the association mapping analysis. We observed genomic prediction accuracies ranging from 0.34 to 0.4 for FER and starburst, respectively. Further research is required to validate these significant SNPs and their relationship to genes affecting FER resistance, and also to improve genomic prediction accuracies across different genetic backgrounds.
引用
收藏
页码:2867 / 2881
页数:15
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