Tree Genetics and Molecular Breeding 2024, Vol.14, No.4, 185-193 http://genbreedpublisher.com/index.php/tgmb 187 Table 1 Summary statistics of wild loquat genome assembly and annotation (Adopted from Jing et al., 2022) Assembly feature Value Assembly size 783.7Mb Number of scaffolds 230 Length of largest scaffolds 52.8Mb Scaffold N50 size 41.8Mb Number of contigs 526 Length of largest contig 16.9Mb Contig N50 size 3.9Mb GCcontent 37.76% Sequences anchored to chromosomes 99.88% CEGMA complete percentage in assembly 98.03% BUSCO complete percentage in assembly 98.27% Gene number 45791 Average gene length 3 315.7bp Average coding sequence length 1 246.6bp 3.3 Genes regulating nutritional and quality traits The nutritional and quality traits of loquat are regulated by a complex network of genes. The genome-wide analysis of loquat has identified DEGs involved in flavonoid and carotenoid biosynthesis, which are crucial for fruit quality and nutritional value (Jing et al., 2022). The MADS-box genes, particularly those involved in fruit expansion, such as EjMADS24/46/49/55/61/67/77/86, have been identified as key regulators of fruit quality traits (Li et al., 2023). Additionally, the expression of SWEET genes, particularly EjSWEET1, EjSWEET3, and EjSWEET16, is higher in ripened fruits, suggesting their role in sugar accumulation and quality trait regulation (Li et al., 2022). 4 Functional Genomics Approaches 4.1 Gene validation techniques Gene validation is a critical step in functional genomics, allowing researchers to confirm the roles of specific genes in loquat genetic improvement. Techniques such as TILLING (Targeting Induced Local Lesions IN Genomes), targeted insertional mutagenesis, gene silencing, gene targeting, and genome editing are employed to validate gene functions. These methods enable the detection of genetic changes through gene knock-down, knock-up, and knock-out strategies, providing insights into gene activity patterns and functional redundancy (Kumar et al., 2024). The use of next-generation sequencing (NGS) has further facilitated the identification and mapping of causal mutations, enhancing the resolution of quantitative trait loci (QTL) and assisting in determining functional causative variations in genes (Sahu et al., 2020). 4.2 Omics integration for trait discovery Integrating various omics approaches, such as genomics, transcriptomics, and metabolomics, is essential for discovering traits in loquat. Large-scale transcriptome and metabolome analyses have been conducted to identify differentially expressed genes (DEGs) and differentially accumulated metabolites (DAMs) in loquat during fruit development. These analyses have revealed significant regulation of genes involved in carbohydrate metabolism, plant hormone signal transduction, flavonoid biosynthesis, and carotenoid biosynthesis in cultivated loquats compared to their wild counterparts (Jing et al., 2022). The integration of these omics data provides a comprehensive understanding of the molecular mechanisms underlying trait development and domestication in loquat. 4.3 Phenotyping for functional studies Phenotyping is a fundamental component of functional genomics, providing the observable characteristics that result from gene expression. In loquat, phenotyping involves assessing traits such as fruit quality, size, and flesh color, which are influenced by genetic factors identified through genomic and transcriptomic analyses (Jing et al., 2022). The use of high-throughput phenotyping techniques, combined with genetic mapping and allele frequency
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