Bioscience Methods 2024, Vol.15, No.6, 255-263 http://bioscipublisher.com/index.php/bm 260 5.3 Cost and resource constraints The cost of genotyping and the resources required for MAS are significant constraints. Although the cost of genotyping has decreased over time, it still represents a substantial investment, particularly for large-scale breeding programs (Sebastian et al., 2010). The need for high-throughput genotyping platforms and the development of diagnostic markers also adds to the financial burden. Additionally, the integration of MAS into conventional breeding programs requires substantial resources in terms of both time and expertise, which can be a limiting factor for many breeding programs (Jena and Mackill, 2008; Miedaner and Korzun, 2012). 5.4 Potential solutions and future prospects Despite these challenges, there are several potential solutions and future prospects for improving the effectiveness of MAS in soybean breeding. Advances in genomic selection (GS) offer promising alternatives by utilizing a broader range of markers across the genome, which can improve prediction accuracy and selection efficiency (Arruda et al., 2016). The development of high-throughput genotyping platforms and the use of chip-based technologies can also reduce costs and streamline the MAS process (Miedaner and Korzun, 2012). Additionally, the identification of broad-spectrum resistance genes and the pyramiding of multiple resistance genes through MAS can enhance the durability and effectiveness of resistance traits (Maroof et al., 2008; Ludwików et al., 2015). Future research should focus on improving the integration of MAS with conventional breeding methods and developing more robust models to account for genetic and environmental interactions (Jena and Mackill, 2008; Sebastian et al., 2010). By addressing these challenges and leveraging new technologies, MAS can become a more effective tool for improving soybean yield and disease resistance, ultimately contributing to more resilient and productive soybean cultivars. 6 Future Perspectives of MAS in Soybean Breeding 6.1 Integration of MAS with emerging technologies The integration of CRISPR/Cas9 genome editing with marker-assisted selection (MAS) holds significant promise for soybean breeding. CRISPR/Cas9 allows for precise modifications at specific genomic loci, which can be used to introduce or enhance traits identified through MAS. This combination can accelerate the development of soybean varieties with improved yield and disease resistance. For instance, CRISPR/Cas9 can be used to target and modify genes associated with pod shattering resistance, as identified by MAS, to create more robust soybean cultivars (Kim et al., 2020). The use of omics technologies, such as genomics and transcriptomics, can greatly enhance the effectiveness of MAS in soybean breeding. Genomic data can provide a comprehensive understanding of the genetic architecture of important traits, while transcriptomic data can reveal gene expression patterns associated with these traits. By integrating these data with MAS, breeders can more accurately select for complex traits like yield and disease resistance. For example, the identification of yield QTLs through genomic analysis can be combined with MAS to improve soybean yield across different environments (Sebastian et al., 2010; Fallen et al., 2015). 6.2 Digital phenotyping and precision agriculture in MAS Digital phenotyping and precision agriculture technologies can revolutionize MAS by providing high-throughput, accurate phenotypic data. These technologies can monitor plant growth, health, and yield in real-time, allowing for more precise selection of desirable traits. The integration of digital phenotyping with MAS can enhance the selection process for traits like disease resistance and yield, making it more efficient and cost-effective. For instance, digital phenotyping can be used to assess the effectiveness of MAS in selecting for resistance to soybean cyst nematode, thereby improving the overall efficiency of breeding programs (Santana et al., 2014). 6.3 International collaborations and data sharing International collaborations and data sharing are crucial for the advancement of MAS in soybean breeding. By sharing genetic and phenotypic data across borders, researchers can build more comprehensive databases, which can be used to identify and validate markers for important traits. Collaborative efforts can also facilitate the development of standardized protocols and tools for MAS, making it more accessible and effective globally. For example, the success of MAS in breeding programs for other crops, such as wheat and barley, can provide
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