Unveiling Photoperiod-Responsive Regulatory Networks in Tropical Maize Through Transcriptome Analysis

通过转录组分析揭示热带玉米光周期响应调控网络

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Abstract

Background/Objectives: Maize (Zea mays L.), a crop of worldwide importance, owes its adaptability to diverse environments to its genetic variation. However, tropical maize exhibits intrinsic photoperiod sensitivity, limiting its adaptability to temperate regions. Photoperiod sensitivity significantly affects the flowering time and other agronomic traits, but the underlying molecular mechanisms remain poorly understood. In this study, the aim is to elucidate the transcriptional regulatory networks mediating photoperiod responses in tropical maize inbred line Su65, providing insights into improving photoperiod adaptability. Methods: RNA-seq analysis was carried out to investigate photoperiod-responsive genes and pathways in tropical line Su65 exposed to varying photoperiod conditions. Differential expression analysis, functional enrichment, and the construction of protein-protein interaction (PPI) networks were carried out to investigate transcriptional dynamics. Additionally, qRT-PCR was employed to confirm the expression patterns of key candidate genes and generate detailed temporal expression profiles. Results: A total of 1728 differentially expressed genes (DEGs) were identified, with significant enrichment in pathways such as stress responses, redox homeostasis, and secondary metabolite biosynthesis. A set of new key hub genes (such as Zm00001d048531, Zm00001d018821, Zm00001d034892, etc.) were identified through PPI network analysis. Temporal expression profiling of ZmPHYB1, ZmPHYC1, ZmFKF2, ZmGI2, and ZmPRR37a, the key genes involved in circadian rhythms, revealed distinct regulatory patterns of photoperiod-sensitive genes at different time points, highlighting their roles in flowering time regulation and developmental transitions. Conclusions: In this study, critical molecular networks underlying photoperiod sensitivity in tropical maize are uncovered and a foundation is provided for improving photoperiod adaptability through genetic improvement. By integrating RNA-seq and qRT-PCR, the research offers valuable insights into transcriptional dynamics and their role in maize development under photoperiodic regulation.

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