https://scholars.lib.ntu.edu.tw/handle/123456789/396755
Title: | Open access resources for genome-wide association mapping in rice | Authors: | McCouch, S.R. CHIH-WEI TUNG |
Issue Date: | 2016 | Journal Volume: | 7 | Source: | Nature Communications | Abstract: | Increasing food production is essential to meet the demands of a growing human population, with its rising income levels and nutritional expectations. To address the demand, plant breeders seek new sources of genetic variation to enhance the productivity, sustainability and resilience of crop varieties. Here we launch a high-resolution, open-access research platform to facilitate genome-wide association mapping in rice, a staple food crop. The platform provides an immortal collection of diverse germplasm, a high-density single-nucleotide polymorphism data set tailored for gene discovery, well-documented analytical strategies, and a suite of bioinformatics resources to facilitate biological interpretation. Using grain length, we demonstrate the power and resolution of our new high-density rice array, the accompanying genotypic data set, and an expanded diversity panel for detecting major and minor effect QTLs and subpopulation-specific alleles, with immediate implications for rice improvement. © 2016, Nature Publishing Group. All rights reserved. |
URI: | http://www.scopus.com/inward/record.url?eid=2-s2.0-84957536566&partnerID=MN8TOARS http://scholars.lib.ntu.edu.tw/handle/123456789/396755 |
DOI: | 10.1038/ncomms10532 | SDG/Keyword: | bioinformatics; cultivar; data set; genetic differentiation; genome; genotype; germplasm; polymorphism; rice; sustainability; allele; bioinformatics; food crop; gene mutation; genome; germplasm; grain; human; human experiment; single nucleotide polymorphism; access to information; agriculture; anatomy and histology; biology; chromosomal mapping; epistasis; food grain; genetic database; genetic variation; genetics; genome-wide association study; genotype; Oryza; phenotype; plant breeding; plant genome; principal component analysis; quantitative trait locus; Access to Information; Agriculture; Alleles; Chromosome Mapping; Computational Biology; Databases, Genetic; Edible Grain; Epistasis, Genetic; Genetic Variation; Genome, Plant; Genome-Wide Association Study; Genotype; Oryza; Phenotype; Plant Breeding; Polymorphism, Single Nucleotide; Principal Component Analysis; Quantitative Trait Loci |
Appears in Collections: | 農藝學系 |
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