数字农科院2.0

Complex Genetic System Involved In Fusarium Ear Rot Resistance In Maize As Revealed By GWAS, Bulked Sample Analysis, And Genomic Prediction

文献类型： 外文期刊

作者： 郭子锋;;邹枨;;刘小刚;;王山荭;;李文学;;Jeffers D; 范兴明;;徐明良;;徐云碧

作者机构：

关键词： Bulked Sample Analysis; Fusarium Verticillioides; Genome-Wide Association Study; Genomic Selection; Maize

期刊名称： PLANT DISEASE

ISSN： 0191-2917

年卷期： 2020 年 104 卷 6 期

页码：

收录情况： JCR（2021版）

摘要： Fusarium ear rot (FER) caused by Fusarium verticillioides is one of the most prevalent maize diseases in China and worldwide. Resistance to FER is a complex trait controlled by multiple genes highly affected by environment. In this paper, genome-wide association study (GWAS), bulked sample analysis (BSA), and genomic prediction were performed for understanding FER resistance using 509 diverse inbred lines, which were genotyped by 37,801 high-quality single-nucleotide polymorphisms (SNPs). Ear rot evaluation was performed using artificial inoculation in four environments in China: Xinxiang, Henan, and Shunyi, Beijing, during 2017 and 2018. Significant phenotypic and genetic variation for FER severity was observed, and FER resistance was significantly correlated among the four environments with a generalized heritability of 0.78. GWAS identified 23 SNPs that were associated with PER resistance, 2 of which (1_226233417 on chromosome 1 and 10_14501044 on chromosome 10) were associated at threshold of 2.65 x 10(-7) [-log(0.01/37,801)]. Using BSA, resistance quantitative trait loci were identified on chromosomes 3, 4, 7, 9, and 10 at the 90% confidence level and on chromosomes 3 and 10 at the 95% confidence level. A key region, bin 10.03, was detected by both GWAS and BSA. Genomic prediction for FER resistance showed that the prediction accuracy by trait-related markers was higher than that by randomly selected markers under different levels of marker density. Marker-assisted selection using genomic prediction could be an efficient strategy for genetic improvement for complex traits like FER resistance.

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