Computational Molecular Biology 2025, Vol.15, No.5, 227-234 http://bioscipublisher.com/index.php/cmb 233 remains to be seen how they will be verified and whether their effects will be stable in the future. Currently, commonly used methods such as high-throughput sequencing, degradation omics analysis, and qRT-PCR, although they have already been able to depict the interaction relationships between many key mirnas and target genes, the "usable" candidate resources are still being expanded. By the way, although this field is bustling, there are still quite a few problems. Most current research often focuses on a specific organ or a certain point in time, and as a result, some important dynamic changes may be overlooked. Whether the newly discovered miRNA has real capabilities or not, there are still not many experiments to draw a conclusion at present - whether the mechanism is clear or not is another matter. The technical aspect cannot be solely resolved by existing methods. High-throughput validation still needs to be more precise, target prediction tools are not always reliable, and there are currently few studies that have effectively integrated omics data. Coupled with the influence of environmental factors and genotype differences, it is still somewhat difficult to directly apply the research results to the fields. But then again, these mirnas themselves are treasures. Drought-resistant regulatory modules may become key resources in molecular breeding in the future. Whether they are used for labeling, gene editing or drought tolerance screening, the directions are quite clear. Especially for some mirnas that are only expressed in the root system or specific genotypes, they are even more worthy of close attention. The tasks to be done next are also very clear: the new mirnas need to continue to undergo functional verification. The verification methods should be more reliable, and it would be best to combine the relevant information of these mirnas with the breeding system. Only in this way can the selection and breeding process of drought-resistant corn be truly advanced. Acknowledgments We are grateful to Dr. Z. Hu for his assistance with the serious reading and helpful discussions during the course of this work. Conflict of Interest Disclosure The authors affirm that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest. References Aravind J., Rinku S., Pooja B., Shikha M., Kaliyugam S., Mallikarjuna M., Kumar A., Rao A., and Nepolean T., 2017, Identification characterization and functional validation of drought-responsive MicroRNAs in subtropical maize inbreds, Frontiers in Plant Science, 8: 941. https://doi.org/10.3389/fpls.2017.00941 Cheng J.H., and Wang W., 2025, Research progress on heat-resistant breeding of fresh-eating corn: screening and utilization of heat-resistant germplasm resources, Maize Genomics and Genetics, 16(3): 119-128. https://doi.org/10.5376/mgg.2025.16.0012 Evers M., Huttner M., Dueck A., Meister G., and Engelmann J., 2015, miRA: adaptable novel miRNA identification in plants using small RNA sequencing data, BMC Bioinformatics, 16: 370. https://doi.org/10.1186/s12859-015-0798-3 Islam W., Idrees A., Waheed A., and Zeng F., 2022, Plant responses to drought stress: microRNAs in action, Environmental Research, 215: 114282. https://doi.org/10.1016/j.envres.2022.114282 Jiao P., Wang C., Chen N., Liu S., Qu J., Guan S., and Ma Y., 2022, Integration of mRNA and microRNA analysis reveals the molecular mechanisms underlying drought stress tolerance in maize (Zeamays L.), Frontiers in Plant Science, 13: 932667. https://doi.org/10.3389/fpls.2022.932667 Li M.H., 2025, ATAC-seq reveals chromatin accessibility changes during maize seed development, Maize Genomics and Genetics, 16(4): 182-201. https://doi.org/10.5376/mgg.2025.16.0017 Li J., Song Q., Zuo Z., and Liu L., 2022, MicroRNA398: a master regulator of plant development and stress responses, International Journal of Molecular Sciences, 23(18): 10803. https://doi.org/10.3390/ijms231810803 Liu X., Zhang X., Sun B., Hao L., Liu C., Zhang D., Tang H., Li C., Li Y., Shi Y., Xie X., Song Y., Wang T., and Li Y., 2019, Genome-wide identification and comparative analysis of drought-related microRNAs in two maize inbred lines with contrasting drought tolerance by deep sequencing, PLoS ONE, 14(7): e0219176. https://doi.org/10.1371/journal.pone.0219176 Samad A., Sajad M., Nazaruddin N., Fauzi I., Murad A., Zainal Z., and Ismail I., 2017, MicroRNA and transcription factor: key players in plant regulatory network, Frontiers in Plant Science, 8: 565. https://doi.org/10.3389/fpls.2017.00565
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