Stage-Specific Defense Reprogramming in Proso Millet Against Head Smut: Insights from Time-Series Transcriptomic and...

Smut disease is a major constraint on proso millet (Panicum miliaceum L.) production. Our previous metabolomic work in the cultivar 'Chishu 13' outlined a two-stage defense strategy involving energy metabolism at jointing and phenylpropanoid activation at heading, yet the transcriptional regulation underlying this metabolic shift remained unknown. In this follow-up study, we performed RNA-seq on the same biological samples used in our prior metabolomics analysis to directly link transcriptomic changes to metabolic outcomes. We compared asymptomatic inoculated (IA) and symptomatic inoculated (IS) plants across four developmental stages (seedling, tillering, jointing, and heading) using time-series profiling, weighted gene co-expression network analysis (WGCNA), and multi-omics integration. Transcriptional reprogramming was minimal during early infection but escalated sharply from jointing (5498 differentially expressed genes) to heading (6818 DEGs), matching the previously observed metabolic divergence. K-means clustering revealed two distinct transcriptional programs: TCA cycle and oxidative phosphorylation pathways dominated at jointing, while phenylpropanoid biosynthesis and plant-pathogen interaction pathways peaked at heading. By combining WGCNA with temporal clustering, we identified 337 high-confidence Stage 1 and 408 Stage 2 candidate genes. Seven hub genes encoding TCA cycle enzymes correlated positively with citrate and succinate accumulation only in IA plants at jointing, whereas eight phenylpropanoid-related hub genes strongly associated with L-phenylalanine and cinnamic acid levels in IA plants at heading. These coordinated transcriptional-metabolic modules were disrupted in IS plants, and RT-qPCR confirmed phenotypic-group-specific expression of key hub genes. This study presents a temporally resolved transcriptional atlas of proso millet response to Anthracocystis destruens, extending beyond prior single-time-point multi-omics studies by integrating matched transcriptomic and metabolomic time-series data to establish a dynamic multi-omics framework for smut resistance. We demonstrate that effective defense requires precise sequential coordination of energy and phenylpropanoid metabolism, providing validated hub genes as targets for molecular breeding.