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ARS Home » Southeast Area » Stuttgart, Arkansas » Dale Bumpers National Rice Research Center » Research » Publications at this Location » Publication #234176

Title: A genome-wide SNP panel for genetic diversity, mapping and breeding studies in rice

item Zhao, Kenyan
item Wright, Mark
item Reynolds, Andy
item Tyagi, Wricha
item Kimball, Jennifer
item Eizenga, Georgia
item Mcclung, Anna
item Mcclung, Anna
item Ali, Md. Liakat
item Hancock, Teresa
item Wood, Daniel
item Bustamante, Carlos
item Mccouch, Susan

Submitted to: Plant and Animal Genome Conference Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 1/1/2009
Publication Date: 1/10/2009
Citation: Zhao, K., Wright, M., Reynolds, A., Tyagi, W., Kimball, J., Eizenga, G.C., McClung, A.M., Ali, M., Hancock, T., Wood, D., Bustamante, C.D., McCouch, S.R. 2009. A genome-wide SNP panel for genetic diversity, mapping and breeding studies in rice. In: Proceedings of Plant and Animal Genome Conference XVII, January 10-14, 2009, San Diego, CA. P. 146.

Interpretive Summary:

Technical Abstract: A genome-wide SNP resource was developed for rice using the GoldenGate assay and used to genotype 400 landrace accessions of O. sativa. SNPs were originally discovered using Perlegen re-sequencing technology in 20 diverse landraces of O. sativa as part of OryzaSNP project ( An additional 12 SNPs targeted functional polymorphisms associated with grain quality, disease resistance and plant morphological characters of particular interest to the plant breeding community. A set of 1,536 SNPs were selected from the discovery dataset based on their high frequency in the indica, tropical japonica and temperate japonica sub-groups and relatively even distribution along rice chromosomes. A panel of 400 O. sativa landraces was genotyped using this 1,536 Illumina GoldenGate assay. Approximately 80% of the SNPs had high quality scores and data reproducibility was 99.8%, as calculated from sample duplicates. Based on SNP calls in a set of 19 rice varieties common to both the Perlegen and Illumina experiments, we observed 85-99% concordance between platforms, depending on the DNA sample. This was in agreement with error estimates for varieties in the OryzaSNP project. Population structure analysis of the 400 O. sativa accessions in this study agreed with previous discoveries based on SSR markers and provided increased resolution for diversity analysis. Allele frequencies and estimates of regional divergence along the genome were compared for different breeding lines and varietal groups. This SNP resource provides a validated SNP set that will be useful for developing more economical and targeted subsets of SNP arrays for QTL mapping and immediate applications in rice improvement.