Legume Genomics and Genetics 2024, Vol.15, No.6, 291-302 http://cropscipublisher.com/index.php/lgg 298 weight per plant, indicating regions of the genome that have a significant impact on multiple drought tolerance traits (Ren et al., 2020). 7.4 Lessons learned and practical implications Several important lessons and practical implications emerged from this MAS breeding program. Efficiency of SLAF-seq technology: The use of SLAF-Seq technology proved to be highly effective in constructing a detailed genetic map and identifying QTL associated with drought tolerance. This technology can be applied to other breeding programs aiming to improve stress tolerance in crops. Importance of multi-trait QTL: The identification of QTL that influence multiple traits, such as plant height and seed weight, highlights the potential for developing soybean varieties with comprehensive drought tolerance. These multi-trait QTL can be prioritized in breeding programs to achieve more robust drought-resistant cultivars. Genetic diversity utilization: The study underscores the importance of utilizing genetic diversity in breeding programs. By crossing drought-sensitive and drought-tolerant cultivars, the program was able to identify valuable genetic markers that can be used to enhance drought tolerance in soybean. Field phenotyping: Accurate phenotyping under field conditions is crucial for the success of MAS programs. The use of both irrigated and drought conditions allowed for a comprehensive assessment of the RILs' performance, ensuring that the identified markers are truly associated with drought tolerance (Ren et al., 2020). 8 Challenges and Limitations of MAS in Soybean Breeding 8.1 Limitations in marker development and identification Marker development and identification are critical steps in Marker-Assisted Selection (MAS) for drought tolerance in soybean. One of the primary limitations is the complexity of drought tolerance as a polygenic trait, which involves multiple quantitative trait loci (QTLs) (Ren et al., 2020). The identification of these QTLs requires extensive genetic mapping and phenotyping, which can be resource-intensive and time-consuming. For instance, the study by identified 10 QTLs for drought tolerance in soybean (Dhungana et al., 2021), but the phenotypic variance explained by each QTL was relatively low, indicating the need for further refinement and validation of these markers. Additionally, the effectiveness of identified markers can vary across different genetic backgrounds and environmental conditions, as seen in the study on alfalfa where the performance of MAS-derived populations varied significantly across different genetic backgrounds (Singh et al., 2022). 8.2 Challenges in phenotyping for drought tolerance Phenotyping for drought tolerance presents several challenges, primarily due to the variability in environmental conditions and the complex nature of drought responses. Accurate phenotyping requires controlled environments to simulate drought conditions and measure relevant traits such as leaf wilting, excised leaf water loss, and relative water content (Du et al., 2009). However, field conditions are often unpredictable, making it difficult to obtain consistent and reliable phenotypic data. The study by highlighted the importance of selecting cost-efficient and reliable markers for phenotyping, such as pubescence, stomatal density, and canopy temperature depression, which showed high consistency across different phenological stages. Despite these advancements, phenotyping remains a bottleneck in MAS due to the labor-intensive and time-consuming nature of the process. 8.3 Integration of MAS with other breeding strategies Integrating MAS with other breeding strategies, such as Genomic Selection (GS), can enhance the efficiency and effectiveness of breeding programs. While MAS focuses on specific QTLs, GS uses genome-wide markers to predict the breeding value of individuals, allowing for the selection of superior genotypes based on their overall genetic potential (Ribaut and Ragot, 2006). The study on maize demonstrated the potential of combining MAS with backcrossing to improve grain yield under drought conditions, suggesting that similar approaches could be beneficial for soybean breeding. However, the integration of MAS with GS and other strategies requires careful consideration of the genetic architecture of drought tolerance and the development of robust statistical models to predict breeding values accurately. Additionally, the high cost of genotyping and the need for large training populations can be limiting factors in the widespread adoption of these integrated approaches (Hassan et al., 2023).
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