## 3 Application of Emerging Technologies in Seeding Selection for Large Yellow Croaker
### Molecular Breeding Technology  
Molecular breeding technology has become an important tool for the genetic improvement of the large yellow croaker. Common methods include Restriction-site Associated DNA Sequencing (RAD-seq), genetic linkage map construction, quantitative trait loci (QTL) mapping, genome-wide association studies (GWAS), whole genome resequencing (WGR), single nucleotide polymorphism (SNP) chips, genomic selection (GS), and genome editing (GE). The combined application of these technologies has significantly enhanced the efficiency and accuracy of breeding large yellow croaker (Table 2). \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Technical Approach** & **Core Principles** & **Characteristics** & **Limitations** \\ \hline
**Quantitative trait gene** & Linkage between molecular markers and QTLs & Requires segregating families with trait variation. & Low resolution; requires construction of linkage maps. \\
**Genome-wide association studies** & Linkage disequilibrium between markers and traits & Utilizes molecular and phenotypic variation in natural populations. & Requires dense markers and deep sequencing of large populations. \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Characteristics of different genomics-assisted nursery technologies. With the continuous development of functional genomics and molecular breeding technologies, genome-wide association studies (GWAS) have become one of the core methods for genetic analysis of complex economic traits in aquatic animals. This technology identifies single nucleotide polymorphisms (SNPs) and candidate genes associated with traits such as growth and disease resistance across the entire genome, providing theoretical and molecular foundations for the selection of superior breeding parents and molecular-assisted breeding [58]. [PERSON] et al. [59] constructed the first physical genome map of the large yellow croaker (total length approximately 727 Mb) based on high-throughput sequencing, laying an important foundation for the discovery of genes related to environmental adaptability and subsequent molecular breeding research. At the same time, the construction of genetic linkage maps and the identification of quantitative trait loci (QTL) have also provided critical support for genetic analysis of important traits. Several studies have constructed genetic linkage maps for the large yellow croaker, identifying multiple QTLs related to growth, disease resistance, and other traits [60]. The map constructed by [PERSON] et al. [61] has a total length of 5451.3 cM, with an average marker interval of 0.54 cM, demonstrating high map density and resolution. Simplified genome sequencing technology, RAD-seq (Restriction-site Associated DNA Sequencing), which is cost-effective and suitable for large-scale SNP mining, has been widely applied in the large yellow croaker. Studies show the existence of two major genetic lineages and the identification of multiple SNPs related to growth traits. [PERSON] et al. [62] analyzed 120 large yellow croakers from five cultured and wild populations using RAD-seq, detecting 7161 high-quality SNP markers. whole genome resequencing (WGR) enables comprehensive analysis of genomic variation between individuals, revealing differences in genetic structures of populations from different waters and genetic characteristics caused by domestication. [PERSON] et al. [63] compared the effects of 0.5\(\times\) and 8\(\times\) sequencing depths in large yellow croaker and found that low-coverage whole genome sequencing (LcWGS) can also be used for genomic selection (GS), showing high practicality. The development and application of SNP chips enable high-throughput genotyping, and the SNP chip for the large yellow croaker has a high proportion of polymorphic sites. [PERSON] et al. [64] performed genotyping on 96 large yellow croakers from five populations using the \"Ningxin No. 1\" SNP chip, finding that 83.38% of the SNPs were polymorphic, with the cross-population effective range ranging from 26.68% to 56.23%.