MPB_2025v16n1

Molecular Plant Breeding 2025, Vol.16, No.1, 63-72 http://genbreedpublisher.com/index.php/mpb 68 2022; Xuan et al., 2022). For example, core modules and significant hub genes such as GLYMA_04G209700 and GLYMA_02G204700 have been identified as potential candidates for improving drought tolerance. Predictive modeling can further enhance our understanding by simulating the interactions between different molecular components and predicting the outcomes of genetic modifications (Jogaiah et al., 2013). 5.2 Advanced tools and technologies for functional validation High-throughput screening and phenotyping platforms are crucial for identifying and validating drought-tolerant soybean genotypes. These platforms enable the rapid assessment of large numbers of genotypes under controlled drought conditions, facilitating the identification of key traits and genetic markers associated with drought tolerance (Dubey et al., 2019; Zhao et al., 2020). For instance, genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs) and candidate genes related to drought tolerance during the germination stage. These high-throughput approaches provide valuable data for breeding programs aimed at developing drought-resilient soybean varieties. CRISPR libraries and synthetic biology approaches offer powerful tools for functional validation and genetic engineering of drought tolerance traits in soybean. CRISPR/Cas9 technology allows for precise editing of target genes, enabling the validation of candidate genes identified through omics studies. For example, the overexpression and knockout of specific miRNAs, such as gma-miR398c, have been shown to significantly impact drought tolerance by regulating the expression of peroxisome-related genes. Synthetic biology approaches can further enhance drought tolerance by designing and constructing novel genetic circuits and pathways that improve stress resilience (Dubey et al., 2019; Zhou et al., 2020). By integrating these advanced approaches, researchers can gain a deeper understanding of the molecular and physiological mechanisms underlying drought tolerance in soybean, ultimately leading to the development of more resilient crop varieties. 6 Practical Applications and Future Directions 6.1 Breeding strategies for drought-tolerant soybeans Marker-assisted selection (MAS) has emerged as a powerful tool in breeding drought-tolerant soybean varieties. By identifying and utilizing specific quantitative trait loci (QTLs) associated with drought tolerance, breeders can significantly enhance the efficiency and precision of selecting desirable traits. For instance, studies have identified multiple QTLs related to drought tolerance traits such as leaf wilting coefficient, excised leaf water loss, and seed yield under drought conditions (Du et al., 2009; Ren et al., 2020). The integration of MAS with traditional breeding methods allows for the rapid development of soybean cultivars with improved drought resistance, reducing the time and labor required for phenotypic selection (Pathan et al., 2007; Du et al., 2009). Conventional breeding has played a crucial role in improving soybean drought tolerance over the past decades. However, it faces limitations due to the complex nature of drought tolerance traits, which are often quantitatively inherited and influenced by environmental factors (Pathan et al., 2007; Manavalan et al., 2009). In contrast, biotechnological approaches, including genetic engineering and functional genomics, offer new opportunities to enhance drought tolerance. For example, the use of candidate genes and genetic transformation techniques has shown promise in developing drought-resistant soybean lines (Manavalan et al., 2009). Combining conventional breeding with biotechnological tools can lead to more robust and resilient soybean varieties (Pathan et al., 2007; Manavalan et al., 2009; Dubey et al., 2019). 6.2 Challenges and opportunities in developing drought-resilient varieties One of the primary challenges in breeding drought-tolerant soybeans is the variability in environmental conditions and field heterogeneity. Drought tolerance is a complex trait influenced by multiple factors, including soil type, water availability, and climatic conditions (Manavalan et al., 2009; Valliyodan et al., 2016). This variability makes it difficult to achieve consistent results across different locations and growing seasons. To address this challenge, researchers are employing high-throughput phenotyping and next-generation mapping approaches to better understand the genotype-environment interactions and identify stable QTLs for drought tolerance (Ren et al., 2020; Valliyodan et al., 2016).

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