PubAg

Main content area

Genome-wide association analysis of lead accumulation in maize

Author:
Zhao, Xiongwei, Liu, Yajuan, Wu, Wenmei, Li, Yuhua, Luo, Longxin, Lan, Yuzhou, Cao, Yanhua, Zhang, Zhiming, Gao, Shibin, Yuan, Guangsheng, Liu, Li, Shen, Yaou, Pan, Guangtang, Lin, Haijian
Source:
Molecular genetics and genomics 2018 v.293 no.3 pp. 615-622
ISSN:
1617-4615
Subject:
Zea mays, bioaccumulation, chromosomes, corn, cultivars, field experimentation, genetic improvement, genome-wide association study, genomics, kinship, lead, leaves, models, phenotypic variation, pot culture, prediction, quantitative trait loci, seeds, single nucleotide polymorphism
Abstract:
Large phenotypic variations in the lead (Pb) concentration were observed in grains and leaves of maize plants. A further understanding of inheritance of Pb accumulation may facilitate improvement of low-Pb-accumulating cultivars in maize. A genome-wide association study was conducted in a population of 269 maize accessions with 43,737 single-nucleotide polymorphisms (SNPs). The Pb concentrations in leaves and kernels of 269 accessions were collected in pot-culture and field experiments in years of 2015 and 2016. Significant differences in Pb accumulation were found among individuals under different environments. Using the structure and kinship model, a total of 21 SNPs significantly associated with the Pb accumulation were identified with P < 2.28 × 10⁻⁵ and FDR < 0.05 in the pot-culture and field experiments across 2 years. Three SNPs on chromosome 4 had significant associations simultaneously with the Pb concentrations of kernels and leaves and were co-localized with the previously detected quantitative trait loci. Through ridge regression best linear unbiased prediction Pb accumulation in the association population, the prediction accuracies by cross validation were 0.18–0.59 and 0.17–0.64, depending on the k-fold and the size of the training population. The results are helpful for genetic improvement and genomic prediction of Pb accumulation in maize.
Agid:
5964780