Computational Molecular Biology 2025, Vol.15, No.5, 245-253 http://bioscipublisher.com/index.php/cmb 25 1 8 Concluding Remarks In tomato research, the role of the CRISPR design algorithm is now almost self-evident, but the changes it has brought about have actually accumulated gradually. Whether it is fruit quality, disease resistance, stress tolerance, or various metabolism-related traits, these tools have been able to make stable targeted modifications within a relatively short period of time. Even in many cases, mutation effects can be observed in the first generation of plants. The use of multiple grnas has also made trait overlay and metabolic engineering easier to expand, making CRISPR increasingly "irreplaceable" in both basic research and breeding projects. However, the genomic structure of tomatoes is not simple, with numerous repetitive sequences, complex regulatory networks, and even epigenetic particularities. These factors often make editing and design less straightforward. Therefore, although the existing tools are already available, algorithms that better suit the characteristics of tomatoes are still needed to further enhance specificity and efficiency. Integrating multi-omics data such as transcriptomics and epigenomes can also help reduce off-targets and further enhance the functional performance after editing. Establishing a dedicated database and design platform for tomatoes is also a necessary step in the long run. The future direction is likely to make the boundary between computational design and experimental verification increasingly blurred, forming a rapid round-trip iterative process. The participation of machine learning, the development of high-throughput screening, and the continuous maturation of multiple editing technologies can all make the selection of gRNA more reliable and the editing results more controllable. With the increasingly close integration of computational biology and experimental biology, the efficiency and accuracy of tomato breeding have the opportunity to reach a new level, respond more quickly to the demands of agricultural production, and better meet consumers' expectations for crop quality. Acknowledgments I thank Editor Huang for his professional guidance on formatting specifications, which ensured that the paper met the journal's academic presentation standards. 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 Alonge M., Lebeigle L., Kirsche M., Jenike K., Ou S., Aganezov S., Wang X., Lippman Z., Schatz M., and Soyk S., 2022, Automated assembly scaffolding using RagTag elevates a new tomato system for high-throughput genome editing, Genome Biology, 23(1): 258. https://doi.org/10.1186/s13059-022-02823-7 Bandyopadhyay A., Kancharla N., Javalkote V., Dasgupta S., and Brutnell T., 2020, CRISPR-Cas12a (Cpf1): a versatile tool in the plant genome editing tool box for agricultural advancement, Frontiers in Plant Science, 11: 584151. https://doi.org/10.3389/fpls.2020.584151 Berman A., Su N., Li Z., Landau U., Chakraborty J., Gerbi N., Liu J., Qin Y., Yuan B., Wei W., Yanai O., Mayrose I., Zhang Y., and Shani E., 2025, Construction of multi-targeted CRISPR libraries in tomato to overcome functional redundancy at genome-scale level, Nature Communications, 16(1): 4111. https://doi.org/10.1038/s41467-025-59280-6 Brooks C., Nekrasov V., Lippman Z., and Van Eck J., 2014, Efficient gene editing in tomato in the first generation using the CRISPR/Cas9 system, Plant Physiology, 166(3): 1292-1297. https://doi.org/10.1104/pp.114.247577 Cao M., Brennan A., Lee C., Park S., and Bao G., 2025, Deep learning based models for CRISPR/Cas off-target prediction, Small Methods, 9(7): 2500122. https://doi.org/10.1002/smtd.202500122 Cardi T., Murovec J., Bakhsh A., Boniecka J., Bruegmann T., Bull S., Eeckhaut T., Fladung M., Galović V., Linkiewicz A., Lukan T., Mafra I., Michalski K., Kavas M., Nicolia A., Nowakowska J., Sági L., Sarmiento C., Yıldırım K., Zlatković M., Hensel G., and Van Laere K., 2023, CRISPR/Cas-mediated plant genome editing: outstanding challenges a decade after implementation, Trends in Plant Science, 28(10): 1144-1165. https://doi.org/10.1016/j.tplants.2023.05.012 Chandrasekaran M., Boopathi T., and Paramasivan M., 2021, A status-quo review on CRISPR-Cas9 gene editing applications in tomato, International Journal of Biological Macromolecules, 190: 120-129. https://doi.org/10.1016/j.ijbiomac.2021.08.169
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