Dissecting the genetic architecture of yield-related traits by QTL mapping in maize

Introduction 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. Methods 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. Results 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, Zm00001d005740 ( ZmbHLH138 ) was significantly associated with ear diameter in the association mapping panel AM508. Conclusion 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.