Medicinal Plant Research 2024, Vol.14, No.2, 71-84 http://hortherbpublisher.com/index.php/mpr 79 6 Integrative Analysis of Genome and Medicinal Value 6.1 Correlation between genetic traits and medicinal properties The genetic traits of Chrysanthemum morifoliumhave been extensively studied. Previous researchers have used DNA molecular markers such as RAPD, ISSR, and AFLP to construct genetic linkage maps for Chrysanthemum morifolium, obtaining molecular markers closely linked to specific traits, thereby providing technical support for marker-assisted breeding (Zhang et al., 2011). Genetic maps constructed using EST-SSR markers have identified QTL loci associated with traits such as inflorescence and leaf characteristics, which are important for the medicinal quality of chrysanthemum (Fan et al., 2020). The genetic diversity among different cultivars, assessed using SSR markers, has also provided insights into the phylogenetic relationships and the potential medicinal value of various cultivars (Feng et al., 2016b). 6.2 Genomic basis for the production of bioactive compounds The production of bioactive compounds in Chrysanthemum morifoliumis closely linked to its genomic makeup. Transcriptome analysis has revealed numerous genes involved in the biosynthesis of flavonoids, which are key bioactive compounds with medicinal properties (Yue et al., 2018). The identification of structural and regulatory genes in the flavonoid biosynthetic pathway has elucidated the genomic basis for the production of these compounds. Techniques like ultrasonic-assisted extraction have optimized the methods for extracting bioactive compounds, accelerating the process of rapid and comprehensive analysis of these compounds (Yuan et al., 2015). Modern biotechnologies have identified flavonoids and caffeoylquinic acids in chrysanthemum flowers, further elucidating the genomic basis for the production of these compounds (Chen et al., 2020). 6.3 Potential for genetic improvement and biotechnological applications The genetic information obtained fromChrysanthemum morifoliumgenome research provides extensive data for genetic improvement and the breeding of new varieties. The whole-genome assembly of Chrysanthemum seticuspe has identified numerous candidate genes controlling Chrysanthemum traits, which can be applied to cultivated chrysanthemums (Hirakawa et al., 2019). Candidate genes controlling flower characteristics have been cloned, and a series of functional molecular markers have been developed, providing technical support for targeted breeding (Sasaki et al., 2017). Comparative transcriptome analysis between wild and cultivated species has revealed patterns of genome duplication and gene selection, elucidating the evolutionary patterns of Chrysanthemum, which can guide future breeding efforts (Won et al., 2017). The integration of these genomic resources and biotechnological approaches holds promise for breeding Chrysanthemum varieties with superior phenotypic and medicinal properties. 7 Future Directions inChrysanthemum morifoliumResearch 7.1 Emerging trends in genomic research The field of genomic research is rapidly evolving, and the future prospects for Chrysanthemum morifolium are promising. Integrating genomics with transcriptomics, proteomics, and metabolomics will enable a deeper understanding of the complex biological networks and interactions that control plant development, stress responses, and medicinal properties (Won et al., 2017). Combining single-cell transcriptome sequencing technology allows for the acquisition of gene expression information from individual cells within Chrysanthemum morifolium tissues. This approach can be used to distinguish the transcriptomic characteristics of different cell types and identify specific cell types involved in the biosynthesis of bioactive compounds and their regulation (Liu et al., 2015). Further utilizing artificial intelligence (AI) and machine learning to analyze complex genomic data can enhance the understanding of Chrysanthemum morifolium. AI-driven predictive models can identify key genetic markers and pathways associated with desirable traits, facilitating more efficient breeding and genetic engineering efforts (Hirakawa et al., 2019).
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