Rice Genomics and Genetics 2025, Vol.16, No.4, 211-218 http://cropscipublisher.com/index.php/rgg 216 of functional components more difficult. To verify their effectiveness, genetic modification, RNA interference and some advanced molecular detection techniques are usually employed, all of which are time-consuming and labor-intensive. There is still an old problem, which is how to distinguish truly functional lncrnas from transcriptional noise. Future research can focus on high-resolution lncRNA functional analysis, such as studying the roles of different subtypes, their interaction networks, and their epigenetic regulation. Combining multi-omics methods with advanced gene editing technologies will enable the faster identification of lncrnas that are valuable for agronomic traits. The regulation of flowering time, yield and stress resistance by lncRNA has great application potential in molecular breeding. If lncRNA labeling can be combined with traditional label-assisted selection and its regulatory ability under environmental changes can be utilized, crops can be better improved. Continuing to explore the regulatory network of lncRNA will also provide new genetic resources and innovative tools for sustainable rice breeding. Acknowledgments We are grateful to Dr. H. Zhou 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 Chen X., Sun Y., Guan N., Qu J., Huang Z., Zhu Z., and Li J., 2018, Computational models for lncRNA function prediction and functional similarity calculation, Briefings in Functional Genomics, 18: 58-82. https://doi.org/10.1093/bfgp/ely031 Cho L., Yoon J., and An G., 2017, The control of flowering time by environmental factors, The Plant Journal, 90: 708-719. https://doi.org/10.1111/tpj.13461 Chodurska B., and Kunej T., 2025, Long non-coding RNAs in humans: classification, genomic organization and function, Non-coding RNA Research, 11: 313-327. https://doi.org/10.1016/j.ncrna.2025.01.004 Choi S., Kim H., and Nam J., 2019, The small peptide world in long noncoding RNAs, Briefings in Bioinformatics, 20: 1853-1864. https://doi.org/10.1093/bib/bby055 Dahariya S., Paddibhatla I., Kumar S., Raghuwanshi S., Pallepati A., and Gutti R., 2019, Long non-coding RNA: classification, biogenesis and functions in blood cells, Molecular Immunology, 112: 82-92. https://doi.org/10.1016/j.molimm.2019.04.011 Delás M., and Hannon G., 2017, lncRNAs in development and disease: from functions to mechanisms, Open Biology, 7(7): 170121. https://doi.org/10.1098/rsob.170121 Du A., Tian W., Wei M., Yan W., He H., Zhou D., Huang X., Li S., and Ouyang X., 2017, The DTH8-Hd1 module mediates day-length-dependent regulation of rice flowering, Molecular Plant, 10(7): 948-961. https://doi.org/10.1016/j.molp.2017.05.006 Gao C.X., Zheng X.W., Li H.B., Ussi A.M., Gao Y., and Xiong J., 2020, Roles of lncRNAs in rice: advances and challenges, Rice Science, 27(5): 384-395. https://doi.org/10.1016/j.rsci.2020.03.003 Hori K., Matsubara K., and Yano M., 2016, Genetic control of flowering time in rice: integration of Mendelian genetics and genomics, Theoretical and Applied Genetics, 129: 2241-2252. https://doi.org/10.1007/s00122-016-2773-4 Klapproth C., Sen R., Stadler P., Findeiss S., and Fallmann J., 2021, Common features in lncRNA annotation and classification: a survey, Non-Coding RNA, 7(4): 77. https://doi.org/10.3390/ncrna7040077 Kopp F., and Mendell J., 2018, Functional classification and experimental dissection of long noncoding RNAs, Cell, 172: 393-407. https://doi.org/10.1016/j.cell.2018.01.011 Lee Y., and An G., 2015, Regulation of flowering time in rice, Journal of Plant Biology, 58: 353-360. https://doi.org/10.1007/s12374-015-0425-x Li J.Q., 2024, A systematic review of the molecular mechanisms of cysteine synthase gene GRA78 in regulating rice leaf color, Plant Gene and Trait, 15(6): 314-322. https://doi.org/10.5376/pgt.2024.15.0031 Li J.W., Qian Q.S., and Liu Y.D., 2024, DEP1 and panicle architecture: influencing rice yield through genetic modulation, Plant Gene and Trait, 15(2): 73-84. https://doi.org/10.5376/pgt.2024.15.0009
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