Development and evaluation of a high-throughput, low-cost genotyping platform based on oligonucleotide microarrays in rice
Liu, Bin, 1957-
AffiliationUniversity of Florida, Gulf Coast Research & Education Center, Wimauma FL, 33598, USA
University of Arizona, Department of Plant Sciences and Bio5 Institute for Collaborative Bioresearch, Tucson AZ, 85721, USA
National Research Centre on DNA Fingerprinting, National Bureau of Plant Genetic Resources, New Delhi, India
Guangdong Academy of Agricultural Sciences (GDAAS), Guangdong, Pr China
International Rice Research Institute (IRRI), Los Banos, The Philippines
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CitationThis article is available from: http://www.plantmethods.com/content/4/1/13
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AbstractBACKGROUND:We report the development of a microarray platform for rapid and cost-effective genetic mapping, and its evaluation using rice as a model. In contrast to methods employing whole-genome tiling microarrays for genotyping, our method is based on low-cost spotted microarray production, focusing only on known polymorphic features.RESULTS:We have produced a genotyping microarray for rice, comprising 880 single feature polymorphism (SFP) elements derived from insertions/deletions identified by aligning genomic sequences of the japonica cultivar Nipponbare and the indica cultivar 93-11. The SFPs were experimentally verified by hybridization with labeled genomic DNA prepared from the two cultivars. Using the genotyping microarrays, we found high levels of polymorphism across diverse rice accessions, and were able to classify all five subpopulations of rice with high bootstrap support. The microarrays were used for mapping of a gene conferring resistance to Magnaporthe grisea, the causative organism of rice blast disease, by quantitative genotyping of samples from a recombinant inbred line population pooled by phenotype.CONCLUSION:We anticipate this microarray-based genotyping platform, based on its low cost-per-sample, to be particularly useful in applications requiring whole-genome molecular marker coverage across large numbers of individuals.
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