BMC Plant Biology (Nov 2022)

Construction of an SNP fingerprinting database and population genetic analysis of 329 cauliflower cultivars

  • Yuyao Yang,
  • Mingjie Lyu,
  • Jun Liu,
  • Jianjin Wu,
  • Qian Wang,
  • Tianyu Xie,
  • Haichao Li,
  • Rui Chen,
  • Deling Sun,
  • Yingxia Yang,
  • Xingwei Yao

DOI
https://doi.org/10.1186/s12870-022-03920-2
Journal volume & issue
Vol. 22, no. 1
pp. 1 – 11

Abstract

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Abstract 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.

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