GWAS-Based Mining of Candidate Genes for Low-Nitrogen Tolerance in Maize

基于全基因组关联分析的玉米低氮耐性候选基因挖掘

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Abstract

Nitrogen (N) is an essential yield-limiting factor in maize, and identifying genes that improve nitrogen use efficiency (NUE) is critical for sustainable agriculture and environmental protection. However, the genetic basis of NUE in maize remains poorly understood. In this study, we performed a genome-wide association study (GWAS) using a mixed linear model (MLM) controlling for population structure and kinship, based on an association panel of 282 maize inbred lines genotyped via the Maize 50K GBTS array (53,162 SNPs). Ten NUE-related traits (grain yield, hundred-kernel weight, ear length, ear diameter, kernel row number, kernel number per row, SPAD value, ASI, plant height, ear height) were evaluated under two N levels during the 2024-2025 growing seasons. The GWAS analysis detected 122 significant SNPs in gene regions linked to low N tolerance under the studied conditions. Linkage disequilibrium analysis and functional annotation narrowed down 26 candidate genes, whose GO and KEGG enrichment analyses (Fisher's exact test) identified three core genes (Zm00001d027880, Zm00001d034047, Zm00001d010574). Furthermore, several inbred lines (H1710, 23N272, and 23N41) demonstrating superior low-nitrogen tolerance were identified. The primary subsequent focus in future research for these genetic materials will be their utilization to breed new cultivars with enhanced nitrogen use efficiency.

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