Legume Genomics and Genetics 2026, Vol.17, No.1, 32-48 http://cropscipublisher.com/index.php/lgg 43 transport, cell wall/membrane modification, antioxidant activity, and secondary metabolism were enriched in tolerant genotypes, and 10 genes on a drought-QTL-rich region of chromosome 8-including two hub genes with non-synonymous SNPs-were prioritized as key regulators of root-based drought tolerance (Aleem et al., 2020). Other case studies highlight specific candidate genes and modules whose expression tracks drought tolerance across tissues and stages. In seedling leaves and roots of tolerant versus sensitive varieties (HN44/HN65, drought-resistant L14/drought-sensitive L21), core pathways such as phenylpropanoid and isoflavonoid biosynthesis, TCA-cycle-linked energy metabolism, ABA-mediated signaling, and glutathione and ROS detoxification are consistently more strongly induced in tolerant materials (Wang et al., 2022; Xu et al., 2023; Wang et al., 2024). Integrative systems-biology analysis across multiple datasets identified 2168 robust DEGs grouped into modules enriched in photosynthesis, cytokinin dehydrogenase, and systemic acquired resistance, with hub genes such as GLYMA_04G209700 and GLYMA_06G030500 showing high connectivity and proposed roles as central coordinators of drought tolerance (Shahriari et al., 2022). At the single-gene scale, expression analyses repeatedly show strong drought induction of TFs like GmAP2/ERF144, GmERF205, GmNAC3, and GmNAC19, as well as structural genes in ABA, cell wall, and secondary metabolism pathways in tolerant backgrounds, aligning their transcriptional patterns with observed physiological resilience (Park et al., 2025). 6.3 Potential applications of drought resistance genes in molecular breeding The case-study genes and modules identified by transcriptomics offer multiple entry points for molecular breeding of drought-resistant soybean. GWAS-integrated transcriptomics at germination detected 58 QTLs and defined 22 candidate genes within large-effect QTLs; functional annotations highlighted several as strong regulators of drought tolerance, providing markers that can be directly used in marker-assisted selection (MAS) and genomic prediction for early-stage vigor under water deficit (Kong et al., 2025). Similar QTL-expression integration in a PI416937 × Cheongsang RIL population identified five candidate genes, including two involved in ion homeostasis and plasma membrane ATPase regulation and heat-shock protein synthesis, which could be introgressed to improve cell protection under dehydration (Park et al., 2025). Comparative root transcriptomes of wild and cultivated soybean, and multi-omics pipelines that pinpoint hub genes on QTL-rich regions, enable the systematic mining of alleles from wild relatives for pre-breeding and broadening of the genetic base (Aleem et al., 2020). Validated TFs and structural genes can also be deployed through transgenic or genome-editing approaches to create drought-tolerant germplasm. Overexpression of GmAP2/ERF144 and GmERF205 significantly enhanced leaf relative water content, reduced membrane damage, improved root growth, and increased yield under drought in field or simulated conditions, demonstrating their utility as “plug-in” tolerance modules (Wu et al., 2025; Cui et al., 2024). NAC TFs such as GmNAC3 and GmNAC19 improved root architecture, antioxidant capacity, and osmolyte balance when overexpressed in soybean or heterologous systems, suggesting that stacking multiple TFs with complementary modes of action could generate more robust tolerance (Wang et al., 2022; Amin et al., 2025). Integrative data-driven feature-engineering pipelines that combine co-expression networks, co-functional resources (e.g., SoyNet) and multi-omics evidence help prioritize the most promising drought-tolerance genes for such engineering, reducing false positives and focusing breeding resources on high-value targets (Kao et al., 2025). As genomic selection and CRISPR-based editing become routine in soybean improvement, these transcriptome-defined candidate genes and networks will form the backbone of molecular designs for cultivars that maintain yield and water-use efficiency under increasingly frequent drought episodes. 7 Prospects for the Application of Transcriptomics in Soybean Drought Resistance Breeding 7.1 Mining of drought resistance gene resources Transcriptomics has become a central tool for systematically mining drought resistance gene resources in soybean, especially when combined with diverse genetic backgrounds and developmental stages. Comparative RNA-seq of wild and cultivated soybeans, as well as tolerant and sensitive genotypes, has identified thousands of drought-responsive DEGs across roots, leaves, and seeds, which are then filtered by GO/KEGG enrichment and
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