Tree Genetics and Molecular Breeding 2024, Vol.14, No.6, 269-276 http://genbreedpublisher.com/index.php/tgmb 272 Studies have shown that while CRISPR/Cas9 can induce desired mutations, the stability and heritability of these changes can vary, necessitating further research to understand and control these aspects. The potential for large chromosomal deletions, as observed in some CRISPR applications, also raises concerns about genetic stability (Kaur et al., 2020). 4.4 Methods to improve editing efficiency and applications of novel cas variants To improve editing efficiency, researchers are exploring various strategies, including the use of novel Cas variants and advanced delivery methods. The PTG/Cas9 system, for example, has demonstrated a tenfold increase in mutagenesis frequency compared to traditional systems, suggesting that alternative sgRNA expression devices can significantly enhance efficiency (Wan et al., 2021). Additionally, novel Cas variants with improved specificity and reduced off-target effects are being developed, which could further enhance the precision and applicability of CRISPR in kiwifruit. Heat treatment and other environmental manipulations have also been proposed to increase editing efficiency. 5 Role of Multi-omics Integration in Kiwifruit Trait Improvement 5.1 Integration of genomics, transcriptomics, and epigenomics data The integration of genomics, transcriptomics, and epigenomics data is pivotal in understanding the complex biological processes that govern kiwifruit traits. Genomics provides the foundational genetic information, while transcriptomics offers insights into gene expression patterns under various conditions. Epigenomics adds another layer by revealing modifications that affect gene activity without altering the DNA sequence (Yang et al., 2021). Together, these omics approaches enable a comprehensive understanding of the regulatory mechanisms involved in kiwifruit development and trait expression. The integration of these datasets can lead to the identification of key regulatory genes and pathways that are crucial for trait improvement (Chao et al., 2023). 5.2 Construction and application of regulatory networks for key traits Constructing regulatory networks involves mapping the interactions between genes, proteins, and metabolites that influence key traits in kiwifruit. By utilizing multi-omics data, researchers can build detailed models that depict these interactions, providing insights into the molecular basis of traits such as fruit ripening, flavor, and nutritional content (Mahmood et al., 2022). These networks can be used to predict how changes in one part of the network might affect the overall phenotype, thus guiding targeted interventions for trait enhancement. The application of such networks is crucial for developing new kiwifruit varieties with improved qualities (Figure 2) (Shu et al., 2023). Figure 2 Summary of metabolome and transcriptome datasets for the construction of kiwi metabolic regulatory network (Adopted from Shu et al., 2023)
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