Plant Gene and Trait 2024, Vol.15, No.2, 73-84 http://genbreedpublisher.com/index.php/pgt 77 Zhao et al. (2019) analyzed the generation process and phenotype of transgenic rice plants overexpressing the DEP1 gene. The study found differences in panicle architecture between wild-type (WT) and transgenic plants (TL35 and TL44), with the transgenic plants exhibiting more erect panicles. Additionally, the expression levels of the DEP1 gene were significantly higher in TL35 and TL44 compared to the wild type. These results indicate that overexpression of the DEP1 gene through genome editing can significantly alter panicle architecture and potentially increase rice yield. This provides new insights and methods for optimizing rice cultivation using genome editing technology. 4.2 Success stories: implementations and outcomes in different environments The manipulation of the DEP1 gene has yielded positive results across various environments. For instance, CRISPR-dep1 mutants demonstrated higher yield under low fertilization conditions compared to wild-type plants under high fertilization, indicating its potential for sustainable agricultural practices (Fei et al., 2019). Zhao et al. (2016) introduced the DEP1 allele into high-yielding japonica rice varieties in northern China, resulting in diverse panicle traits with significant improvements in the number of primary and secondary branches and grain number per panicle (Zhao et al., 2016). These findings underscore the diversity and effectiveness of DEP1 gene manipulation in different environmental contexts. In China, the widespread adoption of high-yielding rice varieties containing the DEP1 allele has led to increased grain yield and improved nitrogen use efficiency. This allele has played a crucial role in developing rice varieties that maintain high yields even under low nitrogen conditions, which is essential for sustainable agriculture (Sun et al., 2014). Additionally, combining DEP1 with other yield-related genes, such as Gn1a, has resulted in the cultivation of rice varieties that are both high-yielding and of high quality, demonstrating the versatility and effectiveness of this gene in different agricultural environments (Wu et al., 2022). 4.3 Comparative analysis with traditional breeding techniques Compared to traditional breeding techniques, the genetic manipulation of the DEP1 gene offers more precise and rapid improvements in rice yield. While traditional breeding methods are effective, they often require multiple generations to achieve the desired traits. In contrast, gene editing techniques like CRISPR/Cas9 allow for targeted modifications, leading to immediate and significant enhancements in panicle architecture and yield (Fei et al., 2019). Studies have shown that the yield improvements obtained through DEP1 gene editing are significantly higher and more consistent than those achieved through traditional breeding methods (Xu et al., 2016). Additionally, the use of genetic tools enables the stacking of multiple beneficial traits, which is difficult to achieve solely through traditional methods (Li et al., 2016). The genetic diversity introduced through DEP1 manipulation, as seen in high-yielding japonica rice varieties, provides a broader genetic base for future breeding programs (Zhao et al., 2016). This contrasts with the narrower genetic diversity typically seen in traditional breeding, which can limit the potential for further improvements. 5 Advances in Genomic Technologies for Studying DEP1 5.1 Next-generation sequencing and its role inDEP1 research Next-generation sequencing (NGS) has revolutionized the study of genetic loci such as DEP1 by enabling high-throughput and precise identification of genetic variations. For instance, the identification of 45 SNPs and 26 indels within the DEP1 locus in a collection of high-yielding japonica rice varieties was made possible through NGS technologies. This detailed genetic mapping has provided insights into the genetic diversity of DEP1 and its contribution to panicle traits, such as the number of primary and secondary branches and grain number per panicle (Zhao et al., 2016). Additionally, NGS has facilitated the fine mapping and candidate gene analysis of other related genes, such as DEP3, which also influence panicle architecture and yield (Qiao et al., 2011). Methods such as MutMap and MutMap+ utilize NGS to quickly identify key nucleotide changes in rice mutants by performing whole-genome resequencing of the DNA from mutant progeny. This is crucial for understanding the functional genetic basis of DEP1 (Fekih et al., 2013). These methods allow researchers to directly associate phenotypic variations with genomic data, thereby enhancing the precision of genetic studies.
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