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ARS Home » Southeast Area » Stuttgart, Arkansas » Dale Bumpers National Rice Research Center » Research » Publications at this Location » Publication #260286
Title: Linkage Disequilibrium And Genome-Wide Association Studies In O. sativa

Author
item ZHAO, KEYAN - Cornell University
item WRIGHT, MARK - Cornell University
item TUNG, CHIH-WEI - Cornell University
item REYNOLDS, ANDY - Cornell University
item Eizenga, Georgia
item McClung, Anna
item MCCOUCH, SUSAN - Cornell University
item BUSTAMANTE, CARLOS - Cornell University

Submitted to: Plant and Animal Genome Conference Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: 11/30/2009
Publication Date: 12/11/2009
Citation: Zhao K, Wright M, Tung CW, Reynolds A, Eizenga G, McClung A, McCouch SR, Bustamante CD. 2010. Linkage disequilibrium and genome-wide association studies in O. sativa. In: Proc. of the Plant & Animal Genomes XVIII Conf. 9-13 Jan. 2010. San Diego, California. Available at: http://www.intl-pag.org/18/abstracts/P05b_PAGXVIII_245.html

Interpretive Summary:

Technical Abstract: There is increasing evidence that genome-wide association studies provide a powerful approach to find the genetic basis of complex phenotypic variation in all kinds of species. For this purpose, we developed the first generation 44K Affymetrix SNP array in rice (see Tung et al. poster). We genotyped around 400 rice accessions covering the main subpopulations of O. sativa using our newly development genotype calling algorithm ALCHEMY (see Wright et al. poster). The good density of the array and large sample size enables us to obtain for the first time accurate estimate of the Linkage Disequilibrium (LD) in different subpopulations in rice. We carried out our studies on phenotypes that are important to crop production include yield, abiotic stress tolerance, flowering time, plant stature, grain quality and many other use-related traits. The deep population structure in rice presents big challenges for false positives in association mapping. Taking a combined approach of association mapping adjusting for population structure and admixture mapping that utilizing the admix signal, we have successfully mapped several known loci, as well as some unknown new candidates. Due to the inbred nature of rice, our data and results opens a whole new era for the mapping of more phenotypes with no extra genotyping cost. Our study will provide a powerful resource for the rice genetics research. Online reference for abstract: http://www.intl-pag.org/18/abstracts/P05b_PAGXVIII_245.html