Rice Genomics and Genetics 2025, Vol.16, No.2, 106-115 http://cropscipublisher.com/index.php/rgg 110 4.2 CRISPR-Cas9 and gene editing technology Not all technologies are like CRISPR-Cas9, which can "rewrite the fate of genes as soon as they are used." It relies on a small piece of RNA (guide RNA) carrying the "scissor" protein Cas9, and directly "cuts" after finding the target site. How to repair it next is left to the cells to handle. This method has been widely used in rice, especially in improving yield, disease resistance and stress resistance (Xie and Yang, 2013; Zhang et al., 2014; Arora and Narula, 2017). Although the technology is not complicated, the key is to choose the right target gene, otherwise it will be useless no matter how accurate it is. 4.3 Proteomics and metabolomics methods The transcriptome talks about information, while the proteome and metabolome talk about "execution". Many times, transcriptional changes are only superficial, and what really affects the state of rice is the underlying protein network and metabolite activity. For example, which protein is activated at which time point, and which metabolic pathway is accelerated due to external stimuli, all of these can be figured out through these technologies. Especially when studying rice modified by CRISPR, if you don't look at protein expression and metabolic reactions, you may miss some key changes (Liao et al., 2019; Usman et al., 2020). 4.4 Case study: application of CRISPR-Cas9 in improving drought resistance In some agricultural areas that rely on the weather for food, drought occurs almost every year, and it is a luxury to talk about increasing production at this time. Therefore, instead of blindly pursuing high yields, it is better to make rice able to withstand drought first. Such traits are difficult to obtain through traditional breeding. Not only is the cycle long, but the effect is often limited. The emergence of CRISPR-Cas9 has given researchers a faster way: find genes involved in drought resistance and edit them directly. OsPYL9 is a target that has been targeted. It is related to the ABA (abscisic acid) response and controls some physiological processes that are helpful for drought. Studies have shown that after mutating this gene, the survival rate of rice under drought can be significantly improved, and the antioxidant capacity can also be enhanced (Usman et al., 2020). However, not all gene editing will bring such obvious positive effects. After some changes, the performance becomes worse. Another example is OsSAP, which plays a "boosting" role in drought response. Through gene editing, it was found that it can participate in regulating the removal of ROS (reactive oxygen species), which is particularly important for drought resistance (Figure 2) (Park et al., 2022). Of course, whether it is suitable for use as a breeding target depends on its actual performance. In general, research on genes such as OsPYL9 and OsSAP is promoting the transformation of rice from "unable to withstand" to "able to withstand". Although the application of CRISPR-Cas9 technology cannot solve all problems, it does bring us one step closer to developing more drought-resistant varieties and brings hope for food stability in arid areas. 5 Multi-omics Integration: A Different Way to Look at Rice Traits In the past, rice traits were often studied by looking at a certain type of data, such as only looking at the transcriptome, or only analyzing the phenotype. This approach can easily miss the complex connections behind it. The emergence of multi-omics integration has broken this limitation. Now, scientists can consider different types of data such as genome, transcriptome, proteome, metabolome and phenotype at the same time. This "puzzle-like" research method allows us to understand some complex traits in rice more systematically and specifically. 5.1 Look not only at genes, but also at performance-from "reading DNA" to "seeing how rice grows" In the past, manual analysis of rice phenotypes was not only slow, but also prone to human errors. The emergence of high-throughput phenotyping platforms has solved this long-standing problem. Most of these systems use imaging, optics and other technologies to quickly and stably measure the external traits of a large number of rice plants, which is very helpful for subsequent data integration (Yang et al., 2013). But sometimes, even if we knock out a gene, there is no obvious change in rice. This does not mean that the gene is not important, but it may be because of functional redundancy, that is, other genes quietly "fill in the gap". Tools like CAFRI-Rice are designed for this situation. It can predict which genes may be redundant based on
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