Abstract
BackgroundFixed arrays of single nucleotide polymorphism (SNP) markers have advantages over reduced representation sequencing in their ease of data analysis, consistently higher call rates, and rapid turnaround times. A 6 K SNP array represents a cost-benefit “sweet spot” for routine genetics and breeding applications in rice. Selection of informative SNPs across species and subpopulations during chip design is essential to obtain useful polymorphism rates for target germplasm groups. This paper summarizes results from large-scale deployment of an Illumina 6 K SNP array for rice.ResultsDesign of the Illumina Infinium 6 K SNP chip for rice, referred to as the Cornell_6K_Array_Infinium_Rice (C6AIR), includes 4429 SNPs from re-sequencing data and 1571 SNP markers from previous BeadXpress 384-SNP sets, selected based on polymorphism rate and allele frequency within and between target germplasm groups. Of the 6000 attempted bead types, 5274 passed Illumina’s production quality control. The C6AIR was widely deployed at the International Rice Research Institute (IRRI) for genetic diversity analysis, QTL mapping, and tracking introgressions and was intensively used at Cornell University for QTL analysis and developing libraries of interspecific chromosome segment substitution lines (CSSLs) between O. sativa and diverse accessions of O. rufipogon or O. meridionalis. Collectively, the array was used to genotype over 40,000 rice samples. A set of 4606 SNP markers was used to provide high quality data for O. sativa germplasm, while a slightly expanded set of 4940 SNPs was used for O. sativa X O. rufipogon populations. Biparental polymorphism rates were generally between 1900 and 2500 well-distributed SNP markers for indica x japonica or interspecific populations and between 1300 and 1500 markers for crosses within indica, while polymorphism rates were lower for pairwise crosses within U.S. tropical japonica germplasm. Recently, a second-generation array containing ~7000 SNP markers, referred to as the C7AIR, was designed by removing poor-performing SNPs from the C6AIR and adding markers selected to increase the utility of the array for elite tropical japonica material.ConclusionsThe C6AIR has been successfully used to generate rapid and high-quality genotype data for diverse genetics and breeding applications in rice, and provides the basis for an optimized design in the C7AIR.
Highlights
Fixed arrays of single nucleotide polymorphism (SNP) markers have advantages over reduced representation sequencing in their ease of data analysis, consistently higher call rates, and rapid turnaround times
This paper describes the efficacy of the C6AIR for QTL mapping, genetic diversity analysis, SNP fingerprinting of breeding lines, tracking of introgressions, and checking for recovery of recurrent parent background during markerassisted backcrossing
The custom-designed Infinium iSelect array consisted of 6000 attempted bead types, including 1571 SNP markers from legacy BeadXpress 384-SNP sets (Thomson et al 2012) and 4429 SNPs selected from whole genome sequence data to be polymorphic within and between diverse germplasm groups and mapping parents
Summary
Fixed arrays of single nucleotide polymorphism (SNP) markers have advantages over reduced representation sequencing in their ease of data analysis, consistently higher call rates, and rapid turnaround times. A number of medium- or high-resolution SNP arrays in rice have been deployed, primarily for genome-wide association studies, including a 44 K SNP chip (Zhao et al 2011), 50 K SNP chips (Chen et al 2013b; Singh et al 2015), and the 700 K high-density rice array (HDRA, McCouch et al 2016). These arrays provide automated platforms to dissect phenotype-genotype associations, while at the same time offering valuable datasets that can be used to validate high-quality SNP markers that are informative within and between key germplasm groups. The subsequent development of lower resolution detection platforms, including KASP, TaqMan, and Fluidigm that target individual SNPs, and the low-density SNP arrays, have made use of the wealth of information published from the higher-density arrays to extract informative SNPs and invariant SNP flanking sequences that convert well to other assays (McCouch et al 2010; Tung et al 2010; Chen et al 2013a)
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