High-throughput SNP genotyping with the GoldenGate assay in maize

Abstract

Single nucleotide polymorphisms (SNPs) are abundant and evenly distributed throughout the genomes of most plant species. They have become an ideal marker system for genetic research in many crops. Several high throughput platforms have been developed that allow rapid and simultaneous genotyping of up to a million SNP markers. In this study, a custom GoldenGate assay containing 1,536 SNPs was developed based on public SNP information for maize and used to genotype two recombinant inbred line (RIL) populations (Zong3 x 87-1, and B73 x By804) and a panel of 154 diverse inbred lines. Over 90% of the SNPs were successfully scored in the diversity panel and the two RIL populations, with a genotyping error rate of less than 2%. A total of 975 SNP markers detected polymorphism in at least one of the two mapping populations, with a polymorphic rate of 38.5% in Zong3 x 87-1 and 52.6% in B73 x By804. The polymorphic SNPs in B73 x By804 have been integrated with previously mapped simple sequence repeat markers to construct a high-density linkage map containing 662 markers with a total length of 1,673.7 cM and an average of 2.53 cM between two markers. The minor allelic frequency (MAF) was distributed evenly across 10 continued classes from 0.05 to 0.5, and about 16% of the SNP markers had a MAF below 10% in the diversity panel. Polymorphism rates for individual SNP markers in pair-wise comparisons of genotypes tested ranged from 0.3 to 63.8% with an average of 36.3%. Most SNPs used in this GoldenGate assay appear to be equally useful for diversity analysis, marker-trait association studies, and marker-aided breeding.

A transcriptome-based genetic map of Chinese chestnut (Castanea mollissima) and identification of regions of segmental homology with peach (Prunus persica)

“…The Illumina GoldenGate BeadArray is a medium-density genotyping platform that can interrogate up to 1,536 SNPs per array. The GoldenGate technology is now being used for genetic analysis in several crop species including barley (Rostoks et al 2006), soybean (Hyten et al 2008), and maize (Yan et al 2009;Yan et al 2010) where the rates of successful scoring of SNP data were ≥90 % (Hyten et al 2008;Rostoks et al 2006;Yan et al 2010). We found 1,064 of 1,536 tested SNPs (69 %) to be scoreable and mappable in at least one of two C. mollissima mapping families.…”

“…Although automated clustering using GenomeStudio generally produced one, two, or three distinct clusters corresponding to the expected genotypic classes based on parental genotypes, the data for all SNPs were inspected manually, and genotypic clusters were manually edited when necessary (Yan et al 2010). Genotypes ambiguously located between clusters were scored as missing data.…”

Joint linkage–linkage disequilibrium mapping is a powerful approach to detecting quantitative trait loci underlying drought tolerance in maize

“…SNP assay is the test of choice for genomewide genetic analysis, but unfortunately it usually detects only two alleles at each locus (31,32). This biallelic limitation can be overcome by using haplotypes constructed from multiple SNP markers likely to be within the same gene or from SNPs within 10 kb, the average size of LD blocks in maize.…”

Genomic Tools for the Enhancement of Vegetable Crops: A Case in Eggplant

“…SSRs are generally considered as dispersed markers, even though in some species tend to concentrate more frequently in heterochromatic regions and it is unlikely to cover all the genomic regions assessing just SSRs (Hong et al, 2007;Shirasawa et al, 2010). On the other hand, it has been reported that the validation of SNPs by high-throughput SNP genotyping, like genotyping-bysequencing (GBS), RAD tag sequencing or similar, can be 100-fold faster and 75% less expensive than SSRs detection through an agarose or polyacrylamide gels or capillary sequencing (Jones et al, 2007;Yan et al, 2010). For all these reasons SNPs markers have quickly replaced SSRs in the last few years.…”