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◆ Genome biology2026-01-29· Biology

Genetic dynamics drive maize growth and breeding

Chengxiu Wu, Zedong Geng, Weikun Li, Junli Ye, Xiaoyuan Hao, Jieting Xu, Minliang Jin, Xiaoyu Wu, Yuanhao Du, Yunyu Chen, Cheng Ma, Yu Gao, Yuehua Chen, Tianjin Xie, Songtao Gui, Yuehua Chen, Jingyun Luo, Yupeng Liu, Wenyu Yang, Jianbing Yan, Jianbing Yan, Wanneng Yang, Wanneng Yang, Yingjie Xiao

原始摘要(英文原文)· Original abstract
BACKGROUND: Phenotypic diversity arises from the process of development and is shaped by genomic variation in plants. However, the genetic basis of growth dynamics remains poorly understood in maize. RESULTS: Here, we analyze 679 maize inbred lines derived from a synthetic CUBIC population with approximately 2.8 million SNPs, leveraging high-throughput phenotyping to capture 1,002,240 RGB images across 18 growth stages. We quantify 67 image-based traits (i-traits), revealing distinct dynamic patterns throughout development. Genome-wide association studies identify 857 quantitative trait loci (QTLs) influencing growth variation, with 88.6% classified as period-specific dynamic QTLs exhibiting modest effects, and 11.4% as conservative QTLs with sustained effects. Notably, 1.5% of cryptic pleiotropic QTLs spanning different growth stages suggest genetic relocations during development. These QTLs enhance heritability estimates for mature traits by an average of 6.2%. We further characterize the novel function of key genes linked with these QTLs, including BRD1 with the pleiotropic effects on plant height and perimeter of convex hull and ZmGalOx1 with the broad-spectrum regulation of plant architecture. Developmental rewiring of epistatic networks shapes maize growth, underscoring the vitality of temporal genetic regulation. Trajectory modeling of i-traits across periods decodes the growth variation patterns, supporting the ontogenic hypothesis driven predictive breeding strategies. CONCLUSION: The findings elucidate the genetic architecture underlying growth dynamics from a spatial-temporal perspective, offering novel insights for maize improvement.
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