Skip to main content
ARS Home » Southeast Area » Stuttgart, Arkansas » Dale Bumpers National Rice Research Center » Research » Publications at this Location » Publication #257026

Title: Development of a research platform for dissecting phenotype-genotype associations in rice (Oryza spp.)

item TUNG, CHIH-WEI - Cornell University
item ZHAO, KEYAN - Stanford University
item WRIGHT, MARK - Cornell University
item ALI, M LIAKAT - University Of Arkansas
item JUNG, JANELLE - Cornell University
item KIMBALL, JENNIFER - Cornell University
item TYAGI, WRICHA - Cornell University
item THOMASON, MICHAEL - Cornell University
item MCNALLY, KENNETH - International Rice Research Institute
item LEUNG, HEI - International Rice Research Institute
item KIM, HYUNJUNG - Cornell University
item AHN, SANG-NAG - Chungnam National University
item REYNOLDS, ANDY - Cornell University
item Scheffler, Brian
item Eizenga, Georgia
item McClung, Anna
item BUSTAMANTE, CARLOS - Stanford University
item MCCOUCH, SUSAN - Cornell University

Submitted to: Rice
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/16/2010
Publication Date: 10/12/2010
Citation: Tung, C., Zhao, K., Wright, M.K., Ali, M., Jung, J., Kimball, J.A., Tyagi, W., Thomson, M.J., McNally, K., Leung, H., Kim, H., Ahn, S., Reynolds, A., Scheffler, B.E., Eizenga, G.C., McClung, A.M., Bustamante, C.D., McCouch, S.D. 2010. Development of a research platform for dissecting phenotype-genotype associations in rice (Oryza spp.). Rice. 3:205–217.

Interpretive Summary: DNA markers called single nucleotide polymorphisms (SNPs) are being used in mammalian research, including human, to understand the genetics causing variation in a range of traits including susceptibility to disease, and tolerance to lactose and alcohol. The objective was to apply SNP technology to rice to enable rice researchers to identify new sources of yield improvement; tolerance to drought, cold, and poor soils; resistance to disease and insect pests; and a variety of other traits. SNP technology is based on hybrids because mammalian species reproduce from crosses between a different male and female, in other words are cross-pollinated. Many crop plants, including rice, are self-pollinated, with a seed being produced from the pollen (male) and ovary (female) on the same plant, thus the SNP technology needed to be adapted for self-pollinated species. The success of adapting SNP technology to rice was demonstrated by genotyping a panel of over 400 rice cultivars and 100 accessions of the rice ancestral species, Oryza rufipogon. Genes controlling plant height, rice blast disease, seed size and the type of starch produced were identified. SNP technology can now be used to dissect many traits of agronomic importance using additional rice cultivars and populations developed from these cultivars. Using SNP technology, genotyping results are obtained more quickly and the results are more accurate. Also, other self-pollinated species in which SNPs have been identified like barley and soybean, should be able to use this SNP technology.

Technical Abstract: We present an overview of a research platform that provides essential germplasm, genotypic and phenotypic data and analytical tools for dissecting phenotye-genotype associations in rice. These resources include a diversity panel of 400 O. sativa and 100 O. rufipogon accessions that have been purified by single seed descent, a custom-designed Affymetrix array consisting of 44,100 SNPs, an Illumina GoldenGate assay consisting of 1536 SNPs, and a suite of low-resolution 384-SNP assays for the Illumina BeadXpress Reader that are designed for applications in breeding, genetics and germplasm management. Our long-term goal is to empower basic research discoveries in rice by linking sequence diversity with physiological, morphological and agronomic variation. This research platform will also help increase breeding efficiency by providing a database of diversity information that will enable researchers to identify useful DNA polymorphisms in genes and germplasm of interest and convert that information into cost-effective tools for applied plant improvement.