Cauliflower is one of the most important vegetable crops grown worldwide. However, the lack of genetic diversity information and efficient molecular markers hinders efforts to improve cauliflower. This study aims to construct DNA fingerprints for 329 cauliflower cultivars based on SNP markers and the KASP system. After rigorous filtering, a total of 1662 candidate SNPs were obtained from nearly 17.9 million SNP loci. The mean values of PIC, MAF, heterozygosity and gene diversity of these SNPs were 0.389, 0.419, 0.075, and 0.506, respectively. We developed a program for in silico simulations on 153 core germplasm samples to generate ideal SNP marker sets from the candidates. Finally, 41 highly polymorphic KASP markers were selected and applied to identify 329 cauliflower cultivars, mainly collected from the public market. Furthermore, based on the KASP genotyping data, we performed phylogenetic analysis and population structure analysis of the 329 cultivars. As a result, these cultivars could be classified into three major clusters, and the classification patterns were significantly related to their curd solidity and geographical origin. Finally, fingerprints of the 329 cultivars and 2D barcodes with the genetic information of each sample were generated. The fingerprinting database developed in this study provides a practical tool for identifying the authenticity and purity of cauliflower seeds and valuable genetic information about the current cauliflower cultivars.

Molecular markers play a crucial role in marker-assisted breeding and varietal identification. However, the application of insertion/deletion markers (InDels) in grapevines has been limited by the low throughput and separability of gel electrophoresis. To developed effective InDel markers for grapevines, this study reports a novel, effective and high-throughput pipeline for InDel marker development and identification. After rigorous filtering, 11 polymorphic multi-allelic InDel markers were selected. These markers were then used to perform genetic identification of 123 elite grape cultivars using agarose gel electrophoresis and next-generation sequencing (NGS). The polymorphism rate of the InDel markers identified by gels was 37.92%, while the NGS-based results demonstrated a higher polymorphism rate of 61.12%. Finally, the NGS-based fingerprints successfully distinguished 122 grape varieties (99.19%), surpassing the gels, which could distinguish 116 grape varieties (94.31%). Specifically, we constructed phylogenetic trees based on the genotyping results from both gels and NGS. The population structure revealed by the NGS-based markers displayed three primary clusters, consisting of the patterns of the evolutionary divergence and geographical origin of the grapevines. Our work provides an efficient workflow for multi-allelic InDel marker development and practical tools for the genetic discrimination of grape cultivars.