Triticeae Genomics and Genetics, 2025, Vol.16, No.2, 72-78 http://cropscipublisher.com/index.php/tgg 75 5 Comparison of Editing Effects in Different Genetic Backgrounds 5.1 Research findings from the Crop Science Institute, Chinese Academy of Agricultural Sciences Researchers from the Chinese Academy of Agricultural Sciences found that after editing TaGW2 homologous genes in different wheat varieties, the grains became larger and the thousand-grain weight (TGW) was significantly improved. However, the increase was different for different varieties. For example, when single mutations were made in the A, B and D genomes, the mutation effect of the B and D genomes was the best. The two varieties Paragon and Bobwhite performed best in this regard. The study also found that if two or even three homologous genes were mutated, the improvement of TGW would be more obvious, reaching 16% to 21%. This difference may be related to the gene expression level of the variety itself. This shows that genetic background plays a big role in the results of gene editing (Simmonds et al., 2016; Wang et al., 2018; Zhang et al., 2018). 5.2 Multi-gene editing experiments conducted by CSIRO, Australia CSIRO, Australia, and its partners conducted multi-gene editing experiments. They used CRISPR/Cas9 to simultaneously edit TaGW2 and other agronomic trait-related genes in hexaploid wheat. The experimental results showed that after knocking out all three homologous TaGW2 genes, the grains became larger, TGW was also greatly improved, and these traits could be stably inherited (Figure 2). More importantly, this editing system can continue to work for several generations. They also hybridized these edited lines with other wheat varieties to further transfer these excellent traits. This shows that this method can be used in different genetic backgrounds and is a very efficient breeding method (Wang et al., 2018). Figure 2 The effects of single-, double-, and triple- KO mutations in the TaGW2 gene homoeologues on the grain morphometric and TGW traits in Bobwhite. The image of twenty seeds from wild-type, single-, double- and triple- mutant plants (scale bar 1 cm). b-e Box and whisker plots show the distribution of TGW (b), grain area (c), grain width (d), and grain length (e) for wild-type and mutant wheat lines. The datasets from Bobwhite and the T0 progeny plants carrying wild-type TaGW2 alleles were combined because they did not show statistical differences. The mean value for each genotype is shown as a red circle. The genotypes of the TaGW2 homoeologues are shown in all panels with lower and uppercase letters corresponding to the mutant and wild-type alleles, respectively, for the A, B, and D genome homoeologues (color figure online) (Adopted from Wang et al., 2018)
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