Legume Genomics and Genetics 2024, Vol.15, No.5, 244-256 http://cropscipublisher.com/index.php/lgg 249 that common bean plants grown under nitrogen fixation conditions exhibit better drought resistance and overall stress tolerance compared to those fertilized with synthetic nitrogen (López et al., 2023; Zhu et al., 2024). This highlights the potential of leveraging genomic insights to develop legume varieties with improved SNF and resilience to environmental stresses. 5.4 Future perspectives and challenges in nitrogen fixation improvement Despite significant progress, several challenges remain in enhancing SNF in legumes. One major challenge is the complexity of the genetic and environmental factors influencing SNF, which requires a multidisciplinary approach involving synthetic biology, plant breeding, and agronomy (Santi et al., 2013; Pankievicz et al., 2019). Additionally, translating genomic discoveries from model systems to diverse legume crops necessitates extensive field trials and the development of robust biotechnological tools. Future research should focus on integrating advanced genomic techniques with traditional breeding practices to create legume varieties that can maximize BNF and contribute to sustainable agricultural systems (Kebede et al., 2021). 6 Enhancing Yield through Translational Genomics 6.1 Yield-related traits and genomic interventions Yield-related traits in legumes, such as maturity, plant height, and seed weight, are critical for improving overall crop productivity. Advances in next-generation sequencing and genotyping technologies have enabled the development of dense genetic maps and QTL maps, which are essential for identifying genomic regions associated with these traits. For instance, in soybean, significant SNPs associated with yield and related traits have been identified, facilitating the use of these markers in breeding programs to enhance yield (Ravelombola et al., 2021). Additionally, the integration of genomic resources and breeding approaches, such as marker-assisted selection (MAS) and marker-assisted backcrossing (MABC), has shown promise in improving yield-related traits in legumes like chickpea, pigeonpea, and groundnut (Varshney et al., 2013). 6.2 Genomic selection (GS) and genome-wide association studies (GWAS) for yield improvement Genomic selection (GS) and genome-wide association studies (GWAS) are powerful tools for yield improvement in legumes. GWAS allows for the identification of marker-trait associations (MTAs) by examining the linkage disequilibrium (LD) between SNPs and phenotypic traits across the genome. This approach has been successfully applied in legumes to dissect complex traits and identify significant SNPs associated with yield (Susmitha et al., 2023). GS, on the other hand, uses genome-wide markers to predict the breeding values of individuals, thereby accelerating the selection process and improving the accuracy of breeding programs. Studies have shown that GS can significantly enhance the efficiency of breeding programs by reducing cycle time and increasing genetic gains (Spindel et al., 2015; Wang et al., 2018; Budhlakoti et al., 2022). 6.3 Molecular breeding and marker-assisted selection (MAS) Molecular breeding techniques, including marker-assisted selection (MAS), have revolutionized legume breeding by enabling the precise selection of desirable traits. MAS involves the use of molecular markers linked to specific traits to select individuals with the desired genetic makeup. This approach has been effectively used to improve traits such as drought tolerance, disease resistance, and yield in legumes. For example, MAS has been employed to introgress QTL regions for drought tolerance and disease resistance in chickpea and groundnut, leading to the development of superior cultivars with enhanced resilience and productivity (Figure 3) (Varshney et al., 2013; Thudi et al., 2020). 6.4 Combining yield with quality traits: protein content, oil composition, and anti-nutritional factors Combining yield improvement with quality traits such as protein content, oil composition, and the reduction of anti-nutritional factors is essential for enhancing the nutritional value of legumes. Legumes are valued for their high protein content and other nutritional components, making it crucial to maintain and improve these traits alongside yield. GWAS and GS have been instrumental in identifying and selecting for these quality traits. For instance, GWAS has been used to identify SNPs associated with protein content and oil composition in legumes, enabling the development of high-protein and nutritionally superior varieties (Ravelombola et al., 2021; Susmitha
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