Assignment of SNP allelic configuration in polyploids using competitive allele-specific PCR: application to citrus triploid progeny

Abstract

Polyploidy is a major component of eukaryote evolution. Estimation of allele copy numbers for molecular markers has long been considered a challenge for polyploid species, while this process is essential for most genetic research. With the increasing availability and whole-genome coverage of single nucleotide polymorphism (SNP) markers, it is essential to implement a versatile SNP genotyping method to assign allelic configuration efficiently in polyploids. This work evaluates the usefulness of the KASPar method, based on competitive allele-specific PCR, for the assignment of SNP allelic configuration. Citrus was chosen as a model because of its economic importance, the ongoing worldwide polyploidy manipulation projects for cultivar and rootstock breeding, and the increasing availability of SNP markers. Fifteen SNP markers were successfully designed that produced clear allele signals that were in agreement with previous genotyping results at the diploid level. The analysis of DNA mixes between two haploid lines (Clementine and pummelo) at 13 different ratios revealed a very high correlation (average = 0·9796; s.d. = 0·0094) between the allele ratio and two parameters [θ angle = tan(-1) (y/x) and y' = y/(x + y)] derived from the two normalized allele signals (x and y) provided by KASPar. Separated cluster analysis and analysis of variance (ANOVA) from mixed DNA simulating triploid and tetraploid hybrids provided 99·71 % correct allelic configuration. Moreover, triploid populations arising from 2n gametes and interploid crosses were easily genotyped and provided useful genetic information. This work demonstrates that the KASPar SNP genotyping technique is an efficient way to assign heterozygous allelic configurations within polyploid populations. This method is accurate, simple and cost-effective. Moreover, it may be useful for quantitative studies, such as relative allele-specific expression analysis and bulk segregant analysis.