Drought stress poses a major challenge to global agriculture under accelerating climate change. Foxtail millet ( Setaria italica ), a C4 crop native to China, has emerged as both a coarse grain crop in arid regions and a model for studying drought adaptation. This mini review synthesizes recent advances in understanding the multi‐level drought response network of foxtail millet, encompassing root system remodeling, stomatal regulation, osmotic adjustment, and photosynthetic and metabolic reprogramming. These physiological processes are coordinated by interconnected signaling modules involving Ca² ⁺ , reactive oxygen species (ROS), and abscisic acid (ABA), and are transcriptionally fine‐tuned by transcription factors (TFs), non‐coding RNAs, and epigenetic modifications. We also emphasize the genetic and germplasm diversity underlying drought tolerance, highlighting foxtail millet’s potential as a comparative C4 model for functional genomics and climate‐resilient breeding. Despite substantial progress, critical gaps remain in understanding hormone crosstalk, root–shoot signaling, and the integration of metabolic and transcriptional responses. Future research integrating pan‐genomics, multi‐omics, and precision genome editing, combined with translational breeding aimed at enhancing yield stability under climate variability, will deepen mechanistic understanding and accelerate the improvement of drought‐resilient cereal crops.

Grain weight, a highly heritable yield component, is a primary breeding target for enhancing wheat productivity. Unraveling the molecular dynamics underlying grain development is essential for identifying key regulators controlling this trait. In this study, we employed an integrated multi-omics approach to analyze transcriptomic and proteomic profiles in developing grains using pairwise near-isogenic lines with contrasting grain weight across four grain developmental stages. Our analysis revealed that early grain development, particularly at 7 days post-anthesis, serves as a critical window during which differential regulation of genes and proteins involved in carbohydrate biosynthesis and metabolic pathways establishes the final grain weight. By combining weighted gene co-expression network analysis (WGCNA) and K-means clustering, we identified a grain weight-associated module and pinpointed four high-confidence candidate genes. Among these, TaYAK1-2D, which encodes a YAK family protein kinase, was functionally validated as a positive regulator of grain weight through mutational analysis. Sequence analysis revealed two major natural haplotypes of TaYAK1-2D, with TaYAK1-2D-Hap2 being significantly associated with higher grain weight across multiple environments. Our findings not only delineate a crucial metabolic window governing grain weight but also provide both a novel genetic target and a practical haplotype marker for molecular breeding aimed at yield improvement in wheat.