Cotton Genomics and Genetics 2025, Vol.16, No.6, 300-309 http://cropscipublisher.com/index.php/cgg 306 6.2 Regulatory and public acceptance issues Beyond technical issues, there are also two "soft barriers" : policy and public attitude. Regulatory standards for genome-edited cotton vary greatly among different countries. Some directly treat it as a genetically modified crop (GMO), while others distinguish between editing and exogenous insertion and offer a more lenient approval process (Saleem et al., 2024). This lack of uniformity has made the commercialization process tortuous. The cumbersome regulatory procedures, the high compliance costs, and the ambiguous definition of intellectual property rights may all slow down the promotion of new varieties. The acceptance at the public level is not one-sided either. Some people think that genome editing is safer and more accurate, but others remain cautious about the potential environmental and food safety risks. Even though non-GMO editing is theoretically more acceptable compared to traditional genetically modified organisms, the cognitive gap in reality still exists, and the market response thus becomes uncertain. 6.3 Data integration and resource gaps The success of precision breeding cannot be achieved without high-quality data support, but this is precisely one of the shortcomings of cotton research. Although we already have multiple versions of genomic maps, truly high-resolution and fully integrated reference genomes are still limited. The systematic collection of phenotypic data is also insufficient, and the coverage of label combinations is inadequate. The complexity of polyploid genomes makes data analysis more like "untangle a tangled mess". To identify key haplotypes or pathogenic targets from them requires not only algorithms but also time and computing power. On the other hand, the insufficiency of computing tools is also slowing down the progress. Stronger algorithmic support is needed in the links of RNA design, off-target prediction and data management. Coupled with the widespread shortage of funds and weak infrastructure in developing regions, many highly promising precision breeding technologies often remain at the laboratory stage (Lassoued et al., 2021). 7 Future Prospects and Opportunities 7.1 Emerging genome editing technologies In the past, CRISPR/Cas9 was almost synonymous with gene editing; But now, it is no longer the sole protagonist. More and more new platforms are joining this technological race. Tools such as Cas12a, Cas13, base editor, and even lead editor are redefining the boundaries of "precision modification" (Molla et al., 2021). These systems can do more than just "knock out" genes. They can achieve the replacement of individual bases, simultaneous editing of multiple genes, and even epigenetic modifications. For cotton breeders, this means more flexible means and greater potential for improvement. Meanwhile, concerns over public acceptance are also prompting researchers to explore alternative approaches. Non-gmo strategies and DNA delivery methods are being actively developed to alleviate regulatory pressure. Coupled with the combination of rapid breeding and genome editing, the process from the laboratory to the field in the future may be significantly shortened. 7.2 Pan-genome and graph-based haplotyping Cotton research is entering a "pan-genome era". A single reference genome has long been unable to cover all genetic diversity, and pan-genomes and graph-based haplotype maps are changing this situation. Through this new analytical framework, researchers discovered thousands of non-reference genes and presence/absence variations (PAVs), and many key genes that were previously overlooked by traditional methods were re-identified (Li et al., 2024). What's more interesting is that graph-based pangenomics can not only observe structural variations but also depict complex haplotype relationships. This is of great significance for trait analysis. It enables breeders to more precisely locate the key alleles that affect fiber quality, stress resistance or yield (Jin et al., 2023). In simple terms, this trend is expanding the genetic "material library", providing more abundant resources for future targeted editing and haplotype selection.
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