Legume Genomics and Genetics 2024, Vol.15, No.1, 13-22 http://cropscipublisher.com/index.php/lgg 21 4 Challenges and Prospects Genome-wide association studies (GWAS) is a technology widely used in plant genetics and breeding research, especially in leguminous crops. It has brought many breakthroughs, but it also faces a series of technical and methodological challenges. At the same time, with the advancement of science and technology and the deepening of research, GWAS and its application prospects in leguminous crop breeding are still very broad, and are of great significance for increasing global food production and agricultural sustainability. The big data generated by GWAS requires powerful computing power for processing and analysis, which is a big challenge for research institutions with limited resources. With the development of sequencing technology, the amount of data has increased dramatically, and how to effectively store, manage and analyze these data has become an urgent problem that needs to be solved (Sonah et al., 2015). High-quality genotypic and phenotypic data are the key to successful GWAS studies. However, the accurate recording of phenotypic data is greatly affected by environmental factors, which may lead to instability and poor reproducibility of research results. The genetic background of leguminous crops is diverse, and population structure and genetic relationships may have a significant impact on GWAS analysis, increasing the risk of false-positive results. More sophisticated statistical models need to be developed to control these confounding factors. Future research needs to develop more efficient algorithms and statistical models to handle big data problems in GWAS and improve the accuracy and efficiency of analysis. The introduction of machine learning and artificial intelligence technologies may provide new ideas for solving these problems (Cichy et al., 2015). The development of high-throughput and automated phenotypic collection technologies will help improve the quality and quantification of phenotypic data, allowing GWAS to more accurately associate specific genetic variants. By integrating multi-omics data such as transcriptomics, proteomics, and metabolomics, GWAS can reveal the molecular mechanisms of trait formation at a deeper level and provide more comprehensive genetic information for breeding. GWAS and molecular breeding technologies are of great significance in addressing global food security challenges by improving crop yield, resistance and adaptability. The application of GWAS technology in leguminous crops can not only accelerate the breeding of new varieties, but also improve the efficiency and sustainability of agricultural production. By precisely improving crop traits and reducing the use of chemical fertilizers and pesticides, molecular breeding technology can help promote the development of ecological agriculture and protect biodiversity. Acknowledgments The author extends sincere thanks to two anonymous peer reviewers for their invaluable feedback on the manuscript. Conflict of Interest Disclosure The author affirms that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest. References Aleena F., Nagendra P.S., Mohar S., Paras S.G., Durgesh K., Udita B., Deepak B., Nidhi V., Dinesh C.J., Dinesh P.S., Vandana T., Dhammaprakash W., Rakesh B., Amit K.S., Swarup K.P., and Debasis C., 2022, The ricebean genome provides insight into Vigna genome evolution and facilitates genetic enhancement, Plant Biotechnology Journal, 21(8): 1522-1524. https://doi.org/10.1111/pbi.14075 Chen Z.J., Lancon-Verdier V., Signor C.L., She Y.M., Kang Y., and Jerome V., Genome-wide association study identified candidate genes for seed size and seed composition improvement in M. truncatula, Sci. Rep., 11: 4224. https://doi.org/10.1038/s41598-021-83581-7 Cichy K.A., Wiesinger J.A., and Mendoza F.A., 2015, Genetic diversity and Genome-wide association studies of cooking time in dry bean (Phaseolus vulgaris L.), Theoretical and Applied Genetics, 128: 1555-1567. https://doi.org/10.1007/s00122-015-2531-z
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