Molecular Plant Breeding 2024, Vol.15, No.5, 247-258 http://genbreedpublisher.com/index.php/mpb 255 (2020) and Liu et al. (2022) identified multiple QTLs associated with growth traits, which are frequently correlated with yield. By extending these QTL mapping techniques, it becomes feasible to identify QTLs specifically associated with yield and related traits. Integrating QTL mapping with GS offers a powerful strategy to improve yield in E. ulmoides. The effectiveness of GS in capturing the heritability of complex traits in Eucalyptus (Resende et al., 2012) and its potential to enhance tree breeding efficiency (Grattapaglia and Resende, 2011) suggest that similar strategies could be applied for yield traits in E. ulmoides. By combining QTL information with GS models, breeders can make more informed selection decisions, resulting in significant improvements in yield and overall breeding efficiency. 8 Practical Implications for Breeding Programs 8.1 Breeding strategies Integrating QTL mapping and GS in breeding programs for E. ulmoides can significantly enhance breeding strategies. QTL mapping identifies specific genomic regions associated with desirable traits, such as growth, yield, and secondary metabolite production, which can be targeted for selection (Li et al., 2014; Li et al., 2015; Jin et al., 2020; Liu et al., 2022). By combining this with GS, which utilizes genome-wide markers to predict breeding values, breeders can capture the effects of multiple minor alleles, thus improving the accuracy and efficiency of selection (Goddard and Hayes, 2007; Grattapaglia and Resende, 2011). This dual approach optimizes breeding programs by reorganizing field designs, increasing the number of lines evaluated, and leveraging extensive genomic and phenotypic data across diverse environments to maximize genetic gain (Merrick et al., 2022). 8.2 Economic and ecological impact The economic and ecological impacts of integrating QTL mapping and GS in the breeding of E. ulmoides are significant. E. ulmoides is highly regarded for its medicinal properties, rubber production, and ecological advantages, such as wind sheltering and sand fixation (Liu et al., 2022; Du et al., 2023). Enhanced breeding strategies can yield superior varieties characterized by higher productivity, enhanced quality, and greater resistance to environmental stresses, thereby increasing economic returns for farmers and industries (Li et al., 2014; Li et al., 2015). Additionally, the ecological advantages of E. ulmoides, such as soil stabilization and biodiversity preservation, can be further enhanced through the cultivation of robust and resilient varieties, contributing to sustainable environmental management (Jin et al., 2020; Liu et al., 2022). 8.3 Policy and regulatory considerations The implementation of advanced breeding techniques like QTL mapping and GS in E. ulmoides breeding programs requires careful consideration of policy and regulatory frameworks. Policymakers must ensure that regulations facilitate the use of molecular breeding methods while safeguarding genetic diversity and preventing the monopolization of genetic resources (Merrick et al., 2022). Furthermore, guidelines should be established for the ethical use of genomic data and the protection of intellectual property rights associated with newly developed varieties (Grattapaglia and Resende, 2011). Collaboration among researchers, breeders, and regulatory bodies is crucial to create an environment conducive to the adoption of these technologies, ensuring that the benefits of improved E. ulmoides varieties are widely accessible and contribute to both economic and ecological sustainability (Goddard and Hayes, 2007; Grattapaglia and Resende, 2011; Merrick et al., 2022). 9 Concluding Remarks In this study, we integrated QTL mapping and GS to enhance the breeding efficiency of E. ulmoides. The construction of high-density genetic maps using SNP markers and GBS has established a robust foundation for identifying QTLs associated with growth traits. Specifically, a high-density genetic map was constructed, covering 90%of the E. ulmoides genome and identifying 44 QTLs related to growth traits. Furthermore, an updated genetic linkage map revealed 89 QTLs based on 10 years of growth trait measurements, further elucidating the genetic mechanisms underlying these traits. The integration of these maps with GS techniques, which utilize genome-wide markers to predict breeding values, shows promise in improving the accuracy and efficiency of breeding programs.
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