High-throughput single nucleotide polymorphism genotyping for breeding applications in rice using the BeadXpress platform
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Multiplexed single nucleotide polymorphism (SNP) markers have the potential to increase the speed and cost-effectiveness of genotyping, provided that an optimal SNP density is used for each application. To test the efficiency of multiplexed SNP genotyping for diversity, mapping and breeding applications in rice (Oryza sativa L.), we designed seven GoldenGate VeraCode oligo pool assay (OPA) sets for the Illumina BeadXpress Reader. Validated markers from existing 1536 Illumina SNPs and 44 K Affymetrix SNP chips developed at Cornell University were used to select subsets of informative SNPs for different germplasm groups with even distribution across the genome. A 96-plex OPA was developed for quality control purposes and for assigning a sample into one of the five O. sativa population subgroups. Six 384-plex OPAs were designed for genetic diversity analysis, DNA fingerprinting, and to have evenly-spaced polymorphic markers for quantitative trait locus (QTL) mapping and background selection for crosses between different germplasm pools in rice: Indica/Indica, Indica/Japonica, Japonica/Japonica, Indica/O. rufipogon, and Japonica/O. rufipogon. After testing on a diverse set of rice varieties, two of the SNP sets were re-designed by replacing poor-performing SNPs. Pilot studies were successfully performed for diversity analysis, QTL mapping, marker-assisted backcrossing, and developing specialized genetic stocks, demonstrating that 384-plex SNP genotyping on the BeadXpress platform is a robust and efficient method for marker genotyping in rice.
KeywordsOryza sativa Single nucleotide polymorphism Illumina BeadXpress reader
We thank Dennis Lozada, Erwin Tandayu, Pauline Capistrano and Socorro Carandang for excellent technical assistance with the BeadXpress Reader at IRRI. This research was supported in part by the International Rice Research Institute, the German Federal Ministry of Development (BMZ/GTZ), the government of Japan, and by grants from the U.S. National Science Foundation (Award # 0606461) and the U.S. Department of Agriculture (CRIS # 0219056) to S. R. M. and C. B. USDA-ARS support staff, Melissa Jia and Sheron Simpson at Stuttgart, Arkansas and Stoneville, MS, respectively, are acknowledged for DNA preparation of samples for running on RiceOPA 4.0.
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