Legume Genomics and Genetics 2026, Vol.17, No.1, 32-48 http://cropscipublisher.com/index.php/lgg 45 7.3 Application of multi-omics integration in drought resistance research Multi-omics integration builds on transcriptomics to provide a more complete view of soybean responses to drought and to reveal pathways and regulators that would be invisible at a single molecular layer. Combined transcriptome-metabolome analyses at the seedling and root levels have shown that drought-tolerant genotypes accumulate higher levels of flavonoids, phenolic acids, and other secondary metabolites, coordinated with upregulation of phenylpropanoid, flavonoid, isoflavonoid, and TCA-cycle genes (Zhao et al., 2021). These datasets have identified pathway structural genes and TFs whose expression correlates strongly with drought-responsive metabolites, thereby nominating them as key levers for engineering metabolic drought defenses. In the drought-tolerant landrace LX, transcriptomic and metabolomic profiling uncovered constitutively higher expression of secondary metabolism genes and corresponding flavonoid accumulation, suggesting a pre-armed biochemical state that can be introgressed into elite backgrounds. Multi-omics dissection of melatonin-treated soybean further demonstrated how exogenous regulators reshape transcript and metabolite profiles in secondary metabolism pathways to enhance drought tolerance, offering additional agronomic levers (Cao et al., 2020). Beyond pairwise integrations, more complex multi-omics frameworks are emerging for dissecting stress-specific and multi-stress architectures. Integrative systems-biology analysis of multiple drought transcriptome datasets has already defined co-expression modules, hub genes, and cis-regulatory elements underpinning drought tolerance, while feature-engineering pipelines incorporate co-functional networks (e.g., SoyNet) and non-omics data to prioritize robust DT genes (Kao et al., 2025). Multi-omics network approaches that combine transcriptome and metabolome data under simultaneous drought and pathogen stress have revealed largely distinct gene-metabolite modules for each stress, emphasizing the need for breeding strategies that account for stress-specific molecular architectures (Husein et al., 2025). In wild soybean, integration of transcriptomics, proteomics, and alternative splicing predictions has uncovered isoform-level regulation as an additional layer of drought adaptation and yielded co-expressed transcript-protein gene sets as high-confidence breeding targets (Kim et al., 2024). Looking forward, coupling these integrative omics platforms with high-throughput phenotyping and machine-learning-based genomic prediction is expected to deliver multi-trait, multi-stress-resilient soybean varieties, with transcriptomics serving as the central scaffold that links genetic variation, molecular networks, and field performance. 8 Summary and Outlook Transcriptomic studies have greatly expanded understanding of how soybean senses, transduces, and mitigates drought stress from germination through reproductive stages. Genome-wide RNA-seq and microarray analyses across roots, leaves, and whole plants have identified thousands of drought-responsive differentially expressed genes (DEGs) involved in hormone signaling, osmotic adjustment, antioxidant defense, photosynthesis, and cell wall remodeling. Comparative analyses of contrasting genotypes at seedling and germination stages uncovered clear molecular distinctions between tolerant and sensitive materials, including broader or more precisely targeted DEG repertoires in tolerant cultivars such as Jindou 21, Heinong 44, and drought-tolerant wild accessions. Weighted gene co-expression network analyses have further organized these DEGs into key modules and pinpointed hub genes and transcription factors, including WRKY, NAC, bZIP, ERF, and NF-Y families, that coordinate downstream responses and represent high-value breeding targets. Another notable achievement is the extension of transcriptomic analysis to critical yield-determining stages and complex stress scenarios. Studies at flowering and seed-filling stages have linked extensive transcriptional reprogramming in ABA biosynthesis, compatible solute metabolism, and ROS scavenging to sharp reductions in photosynthesis and yield under prolonged drought, while also identifying genes and pathways associated with partial recovery after rewatering. Work on combined drought and heat or flooding has delineated overlapping and stress-specific transcriptomic signatures, revealing an energy-saving core program and distinct hormonal and metabolic adjustments for each stress combination. Root-focused transcriptomes and alternative splicing landscapes have highlighted hormone (auxin/ethylene) signaling, carbohydrate and cell wall metabolism, and
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