International Journal of Molecular Evolution and Biodiversity, 2025, Vol.15, No.2, 64-72 http://ecoevopublisher.com/index.php/ijmeb 69 gene resources (Kieu et al., 2021). These technological breakthroughs not only improve the success rate of breeding disease-resistant varieties, but also open up new ideas for reducing the use of chemical pesticides and ensuring the healthy growth of crops (Milczarek et al., 2017). In the future, with the continuous integration of breeding strategies, the coordinated application of genomic selection with traditional methods and molecular breeding methods will have broader development prospects. 6 Challenges and Solutions in Breeding Complex Traits with Genomic Selection 6.1 Challenges posed by potato’s complex genome to GS As a self-fertile tetraploid crop, potato has a complex genomic structure that poses significant obstacles to genomic selection technology. There may be multiple alleles at each locus, and the complex dosage effects and interactions between different genotypes make it more difficult to accurately predict breeding values (Pandey et al., 2023). In addition, there is generally a large genetic differentiation between breeding populations, and this difference limits the generalization ability of genomic prediction models between different populations (Slater et al., 2016). To make matters more complicated, QTLs that control important agronomic traits are mostly micro-effect loci, which are widely distributed and have overlapping effects, further increasing the technical difficulty of multi-trait improvement. These problems require researchers to continuously innovate in multiple links such as model construction, marker screening, and algorithm optimization. 6.2 Limitations in data quality and phenotypic measurement The acquisition of high-quality phenotypic data has become a key factor restricting the application of GS. Accurate phenotypic determination requires a lot of resources, and existing technologies often cannot meet the needs of large-scale breeding populations (Bradshaw, 2017). The unbalanced distribution of marker numbers and phenotypic data limits the ability of the model to capture complete genetic variation (Wang et al., 2018). Noise interference introduced by environmental variation also makes it difficult to accurately assess genetic potential (Stich and Van Inghelandt, 2018). 6.3 Strategies for resolution: multi-omics integration and big data analysis Integrating multi-omics data provides new ideas for solving the above challenges. By combining multidimensional data such as genome, transcriptome and metabolome, the genetic basis of complex traits can be more comprehensively analyzed (Pandey et al., 2022). The application of advanced statistical models and machine learning algorithms has significantly improved big data processing and information extraction capabilities. Optimizing training population construction strategies and selection methods is expected to further improve genetic gain and prediction reliability (Varshney et al., 2017). These technological innovations point the way to breaking through the bottleneck of the application of genomic selection in complex trait breeding. 7 Economic and Social Impacts of Genomic Selection 7.1 Driving innovation in the seed industry Genomic selection technology is reshaping the modern seed industry. By accelerating the screening process of excellent genotypes, this technology significantly shortens the research and development cycle of new varieties. Compared with traditional breeding methods, GS can more efficiently aggregate target traits such as high yield, disease resistance and high quality (Crossa et al., 2017). This technological innovation not only solves the pain points of long traditional breeding cycles and low efficiency, but also promotes the coordinated development of genotyping and phenotyping analysis technologies, providing key technical support for the transformation and upgrading of the seed industry. 7.2 Contributions of breeding outcomes to global food security Against the backdrop of continued population growth and intensified climate change, food security issues are becoming increasingly urgent. Genomic selection (GS) technology, with its advantages in breeding stress-resistant and high-yield crops, is gradually becoming an important tool to address this challenge. By accelerating the development of new varieties, GS technology has significantly improved the ability of staple crops such as potatoes to cope with stresses such as drought, high temperature, and pests and diseases (Xu et al., 2019). Compared with traditional methods, GS can more effectively increase the genetic gain of complex traits and help
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