Lettuce is one of the economically important leaf vegetables and is cultivated mainly in temperate climate areas. Cultivar identification based on the distinctness, uniformity, and stability (DUS) test is a prerequisite for new cultivar registration. However, DUS testing based on morphological features is time-consuming, labor-intensive, and costly, and can also be influenced by environmental factors. Thus, molecular markers have also been used for the identification of genetic diversity as an effective, accurate, and stable method. Currently, genome-wide single nucleotide polymorphisms (SNPs) using next-generation sequencing technology are commonly applied in genetic research on diverse plant species. This study aimed to establish an effective and high-throughput cultivar identification system for lettuce using core sets of SNP markers developed by genotyping by sequencing (GBS). GBS identified 17 877 high-quality SNPs for 90 commercial lettuce cultivars. Genetic differentiation analyses based on the selected SNPs classified the lettuce cultivars into three main groups. Core sets of 192, 96, 48, and 24 markers were further selected and validated using the Fluidigm platform. Phylogenetic analyses based on all core sets of SNPs successfully discriminated individual cultivars that have been currently recognized. These core sets of SNP markers will support the construction of a DNA database of lettuce that can be useful for cultivar identification and purity testing, as well as DUS testing in the plant variety protection system. Additionally, this work will facilitate genetic research to improve breeding in lettuce.

Plant variety protection is essential for breeders’ rights granted by the International Union for the Protection of New Varieties of Plants. Distinctness, uniformity, and stability (DUS) are necessary for new variety registration; to this end, currently, morphological traits are examined, which is time-consuming and laborious. Molecular markers are more effective, accurate, and stable descriptors of DUS. Advancements in next-generation sequencing technology have facilitated genome-wide identification of single nucleotide polymorphisms. Here, we developed a core set of single nucleotide polymorphism markers to identify cabbage varieties and traits of test guidance through clustering using the Fluidigm assay, a high-throughput genotyping system. Core sets of 87, 24, and 10 markers are selected based on a genome-wide association-based approach. All core markers could identify 94 cabbage varieties and determine 17 DUS traits. A genotypes database was validated using the Fluidigm platform for variety identification, population structure analysis, cabbage breeding, and DUS testing for plant cultivar protection.

Genetic diversity analysis and cultivar identification were performed using a core set of single nucleotide polymorphisms (SNPs) in cucumber (Cucumis sativus L.). For the genetic diversity study, 280 cucumber accessions collected from four continents (Asia, Europe, America, and Africa) by the National Agrobiodiversity Center of the Rural Development Administration in South Korea and 20 Korean commercial F1 hybrids were genotyped using 151 Fluidigm SNP assay sets. The heterozygosity of the SNP loci per accession ranged from 4.76 to 82.76%, with an average of 32.1%. Population genetics analysis was performed using population structure analysis and hierarchical clustering (HC), which indicated that these accessions were classified mainly into four subpopulations or clusters according to their geographical origins. The subpopulations for Asian and European accessions were clearly distinguished from each other (F_ST value = 0.47), while the subpopulations for Korean F1 hybrids and Asian accessions were closely related (F_ST = 0.34). The highest differentiation was observed between American and European accessions (F_ST = 0.41). Nei’s genetic distance among the 280 accessions was 0.414 on average. In addition, 95 commercial F1 hybrids of three cultivar groups (Baekdadagi-, Gasi-, and Nakhap-types) were genotyped using 82 Fluidigm SNP assay sets for cultivar identification. These 82 SNPs differentiated all cultivars, except seven. The heterozygosity of the SNP loci per cultivar ranged from 12.20 to 69.14%, with an average of 34.2%. Principal component analysis and HC demonstrated that most cultivars were clustered based on their cultivar groups. The Baekdadagi- and Gasi-types were clearly distinguished, while the Nakhap-type was closely related to the Baekdadagi-type. Our results obtained using core Fluidigm SNP assay sets provide useful information for germplasm assessment and cultivar identification, which are essential for breeding and intellectual right protection in cucumber.

Pear (Pyrus spp.) is a major fruit crop in the Rosaceae family, and extensive efforts have been undertaken to develop elite varieties. With advances in genome sequencing technologies, single-nucleotide polymorphisms (SNPs) are commonly used as DNA markers in crop species. In this study, a large-scale discovery of SNPs was conducted using genotyping by sequencing in a collection of 48 cultivated pear accessions. A total of 256,538 confident SNPs were found on 17 chromosomes, and 288 SNPs were filtered based on polymorphic information content, heterozygosity rate, and genome distribution. This subset of SNPs was used to genotype an additional 144 accessions, consisting of P. pyrifolia (53), P. ussuriensis (27), P. bretschneideri (19), P. communis (26), interspecific hybrids (14), and others (5). The 232 SNPs with reliable polymorphisms revealed genetic variations between and within species in the 192 pear accessions. The Asian species (P. pyrifolia, P. ussuriensis, and P. bretschneideri) and interspecific hybrids were genetically differentiated from the European species (P. communis). Furthermore, the P. pyrifolia population showed higher genetic diversity relative to the other populations. The 232 SNPs and four subsets (192, 96, 48, and 24 SNPs) were assessed for variety identification. The 192 SNP subset identified 173 (90.1%) of 192 accessions, which was comparable to 175 (91.1%) from the 232 SNPs. The other three subsets showed 81.8% (24 SNPs) to 87.5% (96 SNPs) identification rates. The resulting SNPs will be a useful resource to investigate genetic variations and develop an efficient DNA barcoding system for variety identification in cultivated pears.