Zhang Hao, Li Ting, Zhang Zhenyu, Wang Jie, Yang Haoxiang, Liu Jiachen, Zhu Wanchao, Xue Jiquan, Xu Shutu
Hainan Institute of Northwest A&F University, Sanya, Hainan, China.
The Key Laboratory of Maize Biology and Genetic Breeding in Arid Area of Northwest Region, College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China.
Front Plant Sci. 2025 Aug 15;16:1624954. doi: 10.3389/fpls.2025.1624954. eCollection 2025.
Maize is a cornerstone of global agriculture, essential for ensuring food security, driving economic development, and meeting growing food demands. Yet, how to achieve optimal yield remains a multifaceted challenge influenced by biotic, environmental, and genetic factors whose comprehensive understanding is still evolving.
QTL mapping of eight essential yield traits was conducted across four environments - Sanya (SY) in 2021, and Yangling (YaL), Yulin (YuL), and Weinan (WN) in 2022 - using two types of populations: a KA105/KB024 recombinant inbred line (RIL) population and two immortalized backcross populations (IB1 and IB2) derived from the RILs by crossing with their respective parents. Key candidate genes were identified through the integration of RNA-seq data, gene-based association analysis and classic yield-related genes network dataset.
Greater phenotypic variation was observed in RIL population than that in the IB1 and IB2 populations, while similar phenotype variations between IB1 and IB2 populations. A total of 121 QTLs were identified, including 10 QTLs that regulate multiple traits and 41 QTLs shared among these populations. Notably, 59.5% of the 42 QTLs identified in the IBL population (combined mapping using populations IB1, IB2, and RIL) exhibited an overdominance effect through the simultaneous calculation of additive and dominant effects. Through integrated transcriptome data and interaction networks, 20 genes located in these QTLs were investigated as candidate genes. Among them, () was significantly associated with ear diameter in the association mapping panel AM508.
These findings illuminate the genetic mechanisms underpinning maize yield formation, providing a robust foundation for advancing high-yielding variety development through targeted field breeding strategies.
玉米是全球农业的基石，对于确保粮食安全、推动经济发展以及满足不断增长的粮食需求至关重要。然而，如何实现最佳产量仍然是一个多方面的挑战，受到生物、环境和遗传因素的影响，对这些因素的全面理解仍在不断发展。
利用两种群体——KA105/KB024重组自交系（RIL）群体以及通过与各自亲本杂交从RIL衍生而来的两个永久回交群体（IB1和IB2），在四个环境中对八个重要产量性状进行QTL定位，这四个环境分别是2021年的三亚（SY）以及2022年的杨凌（YaL）、榆林（YuL）和渭南（WN）。通过整合RNA测序数据、基于基因的关联分析和经典的产量相关基因网络数据集来鉴定关键候选基因。
在RIL群体中观察到的表型变异比在IB1和IB2群体中更大，而IB1和IB2群体之间的表型变异相似。总共鉴定出121个QTL，包括10个调控多个性状的QTL以及这些群体中共享的41个QTL。值得注意的是，通过同时计算加性效应和显性效应，在IBL群体（使用群体IB1、IB2和RIL进行联合定位）中鉴定出的42个QTL中有59.5%表现出超显性效应。通过整合转录组数据和相互作用网络，对位于这些QTL中的20个基因作为候选基因进行了研究。其中，（）在关联定位群体AM508中与穗直径显著相关。
这些发现阐明了玉米产量形成的遗传机制，为通过有针对性的田间育种策略推进高产品种开发提供了坚实基础。
