Genomics and Applied Biology 2026, Vol.17, No.1, 1-15 http://bioscipublisher.com/index.php/gab 5 was most suitable for cultivar identification, and a genetic similarity value of at least 90% was established as the criterion for consistency in tea. This study provides a clear and operable industry standard for tea cultivar identification. DNA fingerprint is an extended application of cultivar identification. It involves analyzing specific DNA sequences or polymorphic sites in the plant genome to generate unique genetic characteristics that serve as a “genetic ID” for the variety. Li et al. (2025a) collected SNPs from 377 cassava samples. After screening and optimization, they selected 35 369 SNP loci to design the Cassava 35K chip based on GenoBaits technology. Among these, 203 loci with the highest polymorphism (i.e., showing the greatest variation among different varieties) were selected to construct cassava DNA fingerprint. This dataset can clearly distinguish representative cassava germplasms, providing a powerful tool for cassava variety identification and varietal rights protection. Genetic relatedness analysis involves comparing genotypes across multiple germplasms to assess the similarity of their genetic backgrounds, thereby inferring the degree of kinship between samples. This analysis reveals the population structure and genetic diversity of crops, assisting breeders in germplasm selection. Gene chips can capture SNP information from numerous samples and loci, facilitating genetic relationship analysis (Anglin et al., 2024; Liu et al., 2024). Leber et al. (2024) used the TaBW 35K SNP array to genotype 755 bread wheat germplasm resources from different regions, conducting principal component analysis (PCA), hierarchical clustering analysis, and admixture kinship analysis to rapidly assess the genetic background of breeding materials and guide cross-breeding combinations. They found that the genetic diversity of these germplasm resources was higher than that of 632 previously studied landraces and 17 high-quality sequenced wheat germplasms, with the additional genetic diversity mainly originating from landraces in Turkey, Iran, and Pakistan. Guo et al. (2019) developed a GBTS platform in maize. Specifically, a 20 K SNP panel, with markers evenly distributed across maize genome, was developed from a 55 K SNP array (Xu et al., 2017) with improved genome coverage. From this single marker panel, 20 K, 10 K, 5 K, and 1 K SNP markers can be generated by sequencing the samples at the average sequencing depths of 50×, 20×, 7.5×, and 2.5×, respectively. All panels clearly delineated the eight major maize heterotic groups in a phylogenetic tree of 96 lines. The average nucleotide differences between groups aligned with established heterotic patterns, validating the platform's utility for genetic relationship analysis. They also confirmed that selecting the most cost-effective 1K panel could reduce genotyping costs. This research served as a foundation for the development of an mSNP strategy. Later, Guo et al. (2021) developed and validated the mSNP strategy, successfully creating three different types of markers (40K mSNPs, 251K SNPs, and 690K haplotypes) based on a 40K maize mSNP panel. By adjusting sequencing depth, they generated multiple marker panels ranging from 1K to 40K in density, successfully classifying 867 maize inbred lines into the known eight heterotic groups and identifying a new sweet corn population. This strategy meets the demand for obtaining rich, multidimensional genetic information at low cost. 3.2 Crop breeding Marker-assisted selection (MAS) is a technique that utilizes molecular markers (e.g., DNA sequences, proteins) to identify functional genes associated with desirable crop traits. Its principle relies on the genetic linkage between a target gene and its neighbouring molecular markers, enabling gene localization through marker detection (Asif et al., 2024). The widespread application of MAS helps shorten the breeding cycle. For instance, at early developmental stages (such as the seedling or even seed stage), materials carrying target beneficial genes (e.g., dwarfing genes, optimal disease resistance gene combinations) can be screened via gene chip. Xiang et al. (2023) developed a 0.1K liquid-phase gene chip based on 101 functional or closely linked wheat markers. They used it to genotype 174 wheat germplasm resources and, through genotype-phenotype association analysis, confirmed that the chip could accurately select for dwarfing genes and stripe rust resistance genes. This facilitates the avoidance of inbreeding, management of germplasm with unclear origins, and tracing of breeding lineages. Beyond genotyping, many studies utilized gene chips to map quantitative trait loci (QTL) associated with important agronomic traits. Xu et al. (2023) genotyped the wheat varieties JS16 and BN64, along with a population of 171 recombinant inbred lines (RILs) derived from their cross, using a 15K SNP chip. Further genotyping of
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